Migration and Residential of - Nuclear Regulatory …Migration and Residential Location of Workers...

17 Migration and Residential Location of Workers at Nuclear

' Power Plant Construction Sites

[ . Forecasting Methodology

Prepared by S. Malhotra, D. ~ a n k i e d '. :'

Pacific Northwest Laboratory Operated by Battelle Memorial lnstitute

Prepared for U.S. Nuclear Regulatory Commission

b

NOTICE

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Migration and Residential Location of Workers at Nuclear Power Plant Construction Sites

Forecasting Methodology

Manuscript Completed: March 1981 Date Published: April 1981

Prepared by S. Malhotra, D. Manninen

Pacific Northwest Laboratory Richland, WA 99352

Prepared for Division of Safeguards, Fuel Cycle and Environmental Research Office of Nuclear Regulatory Research U.S. Nuclear Regulatory Commission Washington, D.C. 20555 NRC FIN B2265

A0 S TR ACT

The pr imary o b j e c t i v e o f t h i s s tudy was t o improve the accuracy o f

socioeconomic impact assessments by p rov id ing an improved methodology f o r

p r e d i c t i n g the number o f i nm ig ra t i ng workers and t h e i r r e s i d e n t i a l loca-

t i o n pa t te rns a t f u t u r e nuclear power p l a n t cons t ruc t ion p ro jec ts . Pro-

cedures f o r es t imat ing several o ther var iab les which have important

imp1 i c a t i o n s w i t h respect t o socioeconomic impact assessment ( i .e., r e l o -

c a t i o n o f dependents, i n t e n t i o n t o remain i n t he area, type o f housing

selected, m a r i t a l s tatus, and average f a m i l y s i z e ) were a lso developed.

The analys is was based on worker survey data f rom 28 surveys which

were conducted a t 13 nuclear power p l a n t cons t ruc t ion s i t e s . These sur-

vey data were examined t o i d e n t i f y pa t te rns o f v a r i a t i o n i n var iab les o f

i n t e r e s t across s i t e s as we l l as across various worker groups. I n addi-

t i o n , considerable secondary data r e f l e c t i n g var ious reg iona l and p r o j e c t

c h a r a c t e r i s t i c s were gathered f o r each s i t e . These data were used t o

est imate the e f f e c t s o f f a c t o r s under ly ing the observed v a r i a t i o n i n

c r a f t - s p e c i f i c migrant p ropor t ions and the r e s i d e n t i a l l o c a t i o n pa t te rns

o f i nm ig ra t i ng workers across s i t e s and surveys. The r e s u l t s o f these

analyses were then used as a bas is f o r the s p e c i f i c a t i o n of t h e fo re-

cas t i ng procedures.

iii

TABLE OF CONTENTS

Page

ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i i i

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . i x

ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . x i

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

CHAPTER I : DATA . . . . . . . . . . . . . . . . . . . . . . . . . 9

DATA SOURCES . . . . . . . . . . . . . . . . . . . . . . . . . 9

Survey Data . . . . . . . . . . . . . . . . . . . . . . . 9

Secondary Data . . . . . . . . . . . . . . . . . . . . . 10

QUALITY AND GENERALIZABILITY OF THE DATA . . . . . . . . . . . 11

Response Rates . . . . . . . . . . . . . . . . . . . . . 11

Extensiveness o f t h e Data . . . . . . . . . . . . . . . . 11

V a r i a t i o n i n Regional and P r o j e c t C h a r a c t e r i s t i c s . . . . 12

CHAPTER 11: PROFILE ANALYSIS - SUMMARY OF RESULTS . . . . . . . . 15

FOCUSOF THE PROFILE ANALYSIS . . . . . . . . . . . . . . . . 15

SUMWRY OF RESULTS . . . . . . . . . . . . . . . . . . . . . . 18

Mig ran t P ropo r t i ons . . . . . . . . . . . . . . . . . . . 20

I n t e n t i o n t o Remain i n t h e Area . . . . . . . . . . . . . 20

Re loca t i on o f Dependents . . . . . . . . . . . . . . . . 21

R e s i d e n t i a l Loca t i on . . . . . . . . . . . . . . . . . . 22

T y p e o f H o u s i n g . . . . . . . . . . . . . . . . . . . . . 22

Demographic C h a r a c t e r i s t i c s o f Movers . . . . . . . . . . 23

IMPLICATIONS FOR FORECASTING . . . . . . . . . . . . . . . . . 24

The Need t o Conduct a M u l t i v a r i a t e Ana l ys i s . . . . . . . 26

The Importance o f Workforce Composi t ion . . . . . . . . . 27

The I d e n t i f i c a t i o n o f Exp lana to ry Va r i ab l es . . . . . . . 27

J u s t i f i c a t i o n f o r Adopt ing a C r a f t - S p e c i f i c U n i t of Ana l ys i s . . . . . . . . . . . . . . . . . . . 29

Other Cons idera t ions . . . . . . . . . . . . . . . . . . 30

CHAPTER 111: MULTIVARIATE ANALYSES . . . . . . . . . . . . . . . 33

M I GRANT PROPORT ION . . . . . . . . . . . . . . . . . . . . . . 33

Model . . . . . . . . . . . . . . . . . . . . . . . . . . 34

. . . . . . . . . . . . . . . . . E m p i r i c a l S p e c i f i c a t i o n 35

. . . . . . . . . . . . . . . . . . . . . . . . . Resu l t s

. . . . . . . . . . . . . . . . . . . . . . . . . Summary

. . . . . . . . . . . . . . . . . . . . . RESIDENTIAL LOCATION

. . . . . . . . . . . . . . . . . . . Model S p e c i f i c a t i o n

. . . . . . . . . . . . . . . . . . . . . . . . . Resu l t s

. . . . . . . . . . . . . . . . . . . . . . . . . Summary

. . . . . . . . CHAPTER I V : DESCRIPTION OF FORECASTING PROCEDURES

PREDICTINGMIGRANT PROPORTIONS . . . . . . . . . . . . . . . . PREDICTING PERSONAL AND HOUSEHOLD CHARACTERISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . OF MOVERS

. . . . . . . . . . . . . . . . Re loca t i on o f Dependents

I n t e n t i o n t o Remain i n t h e Area . . . . . . . . . . . . . T y p e o f H o u s i n g . . . . . . . . . . . . . . . . . . . . . M a r i t a l S ta tus . . . . . . . . . . . . . . . . . . . . . Average Fami ly S ize . . . . . . . . . . . . . . . . . . .

PREDICTING RESIDENTIAL LOCATION PATTERNS . . . . . . . . . . . . . . . . . . . . . . . . . VALIDITY OF FORECASTING PROCEDURES

M ig ran t P ropo r t i ons . . . . . . . . . . . . . . . . . . . Personal and Household C h a r a c t e r i s t i c s o f Movers . . . . R e s i d e n t i a l Loca t i on . . . . . . . . . . . . . . . . . .

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . APPENDIX A: THE DATA COLLECTION EFFORT . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . SURVEY DATA

Survey A d m i n i s t r a t i o n . . . . . . . . . . . . . . . . . . Nature of t h e Data Co l l ec ted . . . . . . . . . . . . . . Ex ten t o f V a r i a t i o n i n Regional and P r o j e c t

C h a r a c t e r i s t i c s . . . . . . . . . . . . . . . . . . . . Prepa ra t i on o f t he Survey Data F i l e s . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . SECONDARY DATA

. . . . Problems Encountered i n Secondary Data C o l l e c t i o n

Major Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SURVEY INSTRUMENTS

APPENDIX B: CONSTRUCTION WORKER SURVEYS.. A MEANS FOR . . . . . . . . . . . . . . SUCCESSFUL IMPLEMENTATION

PRESURVEY GROUNDWORK . . . . . . . . . . . . . . . . . . . . . The Employment H ie ra rchy . . . . . . . . . . . . . . . .

. . . . . . . . . . . Ob ta in i ng t h e Necessary Cooperat ion

SAMPLING ISSUES . . . . . . . . . . . . . . . . . . . . . . .

VIABLE METHODS OF SURVEY ADMINISTRATION . . . . . . . . . . . 123

The Safety Meeting Option . . . . . . . . . . . . . . . . 124

The Supervisor Opt ion . . . . . . . . . . . . . . . . . . 125

The Paycheck D i s t r i b u t i o n Option . . . . . . . . . . . . 126

RESPONSE RATE AND FOLLOW-UP . . . . . . . . . . . . . . . . . 128

DEVELOPMENT OF THE SURVEY INSTRUMENT . . . . . . . . . . . . . 129

OTHERISSUES . . . . . . . . . . . . . . . . . . . . . . . . . 130

SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

APPENDIX C: MIGRANT PROPORTION MULTIVARIATE ANALYSIS . . . . . . 133

DETERMINANTS OF MIGRANT PROPORTIONS . . . . . . . . . . . . . 133

EMPIRICAL SPECIFICATION . . . . . . . . . . . . . . . . . . . 135

D e f i n i t i o n o f Var iab les . . . . . . . . . . . . . . . . . 137

F i n a l S p e c i f i c a t i o n . . . . . . . . . . . . . . . . . . . 142

RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . 143

Construct ion Worker Equat ion . . . . . . . . . . . . . . 143

Nonconstruct ion Worker Equat ion . . . . . . . . . . . . . 151

DEFINITION OF VARIABLES . MIGRANT PROPORTIONS . . . . . . . . 154

APPENDIX D: RESIDENTlAL LOCATION MULTIVARIATE ANALYSIS . . . . . 159

FACTORS INVOLVED I N RESIDENTIAL LOCATION DECISIONS . . . . . . 159

RESIDENTIAL LOCATION MODEL . . . . . . . . . . . . . . . . . . 161

D e f i n i t i o n o f Var iab les . . . . . . . . . . . . . . . . . 163

F i n a l S p e c i f i c a t i o n . . . . . . . . . . . . . . . . . . . 165

RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . 166

Regional A t t rac t i veness . . . . . . . . . . . . . . . . . 168

Housing A v a i l a b i l i t y . . . . . . . . . . . . . . . . . . 169

Workforce Composition and Other P r o j e c t C h a r a c t e r i s t i c s . . . . . . . . . . . . . . . . . . . . . 170

Cont ro l Var iab les . . . . . . . . . . . . . . . . . . . . . 170

D i f fe rences i n Dis tance Exponents . . . . . . . . . . . . 170

DEFINITION OF VARIABLES - RESIDENTIAL LOCATION . . . . . . . . 174

APPENDIX E: VALIDITY OF THE FORECASTING PROCEDURES . . . . . . . 177

MIGRANT PROPORTIONS . . . . . . . . . . . . . . . . . . . . . 177

Explained V a r i a t i o n . . . . . . . . . . . . . . . . . . . 177

Robustness o f t h e C o e f f i c i e n t s . . . . . . . . . . . . . 178

Consistency o f Explained Variance and Residuals . . . . . 183

Pred ic ted and Actual Overa l l M igran t Propor t ions . . . . 183

RESIDENTIAL LOCATION . . . . . . . . . . . . . . . . . . . . . 185

Robustness o f t h e C o e f f i c i e n t s . . . . . . . . . . . . . 187

Consistency o f Expla ined Variance and Residuals . . . . . 187

P r e d i c t e d and Ac tua l R e s i d e n t i a l Loca t i on Pa t t e rns . . . 187

PERSONAL AND HOUSEHOLD CHARACTERISTICS OF MOVERS . . . . . . . 190

LIST OF TABLES

Table Page

2 8 Workforce Composition at Time of Survey by Craft . . . . . . . . . . . . . . . . . . . . . . . . . Groups

Mi grant Proportion Regress ion Results - Construction . . . . . . . . . . . . . . . . . . . . . . . Migrant Proportion Regression Results - Non-construction . . . . . . . . . . . . . . . . . . . . . Residential Location Regression Results . . . . . . . . . . Distance Coefficients as Estimated Based Upon the . . . . . . . . . . . . . . . Residential Location Equation

Availability and Nature of Survey Data . . . . . . . . . . Regional and Power Plant Project Characteristics . . . . . Survey Response Rates and the Stage of Project Completion at the Time of the Survey . . . . . . . . . . . . . . . . . A Summary of Secondary Data Collected - Project Characteristics . . . . . . . . . . . . . . . . . . . . . . A Summary of Secondary Data Collected - Regional and . . . . . . . . . . . . . . . . . Community Characteristics

Hierarchy of Employment Relationships at Construction Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . Migrant Proportion Regression Results - Construction . . . Migrant Proportion Regression Results - Non-construction . . . . . . . . . . . . . . . . . . . . . Residential Location Regression Results . . . . . . . . . . Distance Coefficients as Estimated Based Upon the Residential Location Equation . . . . . . . . . . . . . . . Construction Worker Migrant Proportion Regression Results for Subsets of Sites . . . . . . . . . . . . . . . . . . . Nonconstruction Worker Migrant Proportion Regression Results for Subsets of Sites . . . . . . . . . . . . . . . A Comparison of Predicted and Actual Migrant Proportions Using Various Equation Estimates . . . . . . . . . . . . . Summary of Explained and Unexplained Variation in the Estimated Equations - Migrant Proportions . . . . . . . . . Overall Migrant Proportions - A Comparison of Actual and Predicted Values . . . . . . . . . . . . . . . . . . . Residenti a1 Location Regression Results for Subsets of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary of Explained and Unexplained Variation in the Estimated Equation - Residential Location . . . . . . . . .

E-8 Propor t ions o f Movers L i v i n g a t Various Distances f rom t h e S i t e - A Comparison o f Actual and Pred ic ted Values . . 191

E-9 P ropo r t i on o f Movers w i t h Fami ly Present - A Comparison o f Actual and Pred ic ted Values . . . . . . . . . . . . . . 192

E-10 Percent Temporary - A Comparison o f Actual and Pred ic ted Values . . . . . . . . . . . . . . . . . . . . . . . . . . 194

E-11 Housing Choice o f Movers by Type - A Comparison o f Actual and Pred ic ted Values . . . . . . . . . . . . . . . . . . . 195

E-12 Percent Marr ied - A Comparison o f Actual and Pred ic ted Values . . . . . . . . . . . . . . . . . . . . . . . . . . 196

ACKNOWLEDGEMENTS

Th is i s t he f i n a l r e p o r t o f a s tudy o f l abo r f o r c e m ig ra t i on and

r e s i d e n t i a l choice o f workers a t nuc lear power p l a n t cons t ruc t i on s i t e s

which was conducted by B a t t e l l e Human A f f a i r s Research Centers.

P r i n c i p a l I n v e s t i g a t o r s Suresh Malhotra and Diane Manninen acknowl-

edge t h e c o n t r i b u t i o n s and va luab le ass is tance o f Michael Mertaugh, Peter

Meserve, Duncan M i t c h e l l , Gary Gordon, and Jean Dennis a t var ious stages

o f t h i s study. We a lso apprec iate r e c e i v i n g comments from D r . C la rk

Pr ichard, David Barna, Don Cleary, and Michael Kaltman o f t he U.S.

Nuclear Regulatory Commission and J. W i l l i a m C u r r i e and Richard C. Adams

o f t h e P a c i f i c Northwest Labora tor ies throughout t h e p r o j e c t .

Th i s r e p o r t cou ld n o t have been completed w i thou t the pa t ience and

o rgan i za t i ona l a b i l i t y o f Susan Stream, who typed the umpteen d r a f t s .

The l a s t minute s e c r e t a r i a l he lp o f Karen DePoppe i s a lso acknowledged.

INTRODUCTION

The purpose of this project was to enhance the accuracy of socio-

economic impact assessments of large construction projects by providing

an improved methodology for predicting the number of inmigrating workers

and their residential location patterns (SEAFORM) .l This was accom-

plished by conducting a study of labor force migration and residential

choice of workers at nuclear power plant construction sites. Specifi-

cally, in this study we developed methods by which information regarding

local labor availability prior to plant construction, anticipated con-

struction worker requirements, and various regional characteristics could

be used to predict:

the number of workers who will move to the area to work at the construction sites; and

e the residential location pattern of the inmigrating workers.

In addition, an attempt was made to develop guidelines for predicting:

the intention of these workers to remain in the area;

the number of workers who will relocate their families;

e the type of housing that these workers will select; and

e marital status and average family size of the inmigrating workers.

The initial phase of the study involved an extensive data collection

effort. The survey data which were used in this study include the responses of over 49,000 workers from 28 surveys conducted at 13 nuclear

power plant construction sites. These data were obtained in two differ-

ent ways. Worker surveys were conducted at four nuclear power plant

construction sites specifically for this study. In addition, we were

able to increase the number of sites in our analysis by including data

from similar surveys which were conducted by utilities at nine additional

sites.

Considerable secondary data were also collected for this study.

These secondary data include projected craft-specific labor requirements,

l ~ e s ~ i t e the limited scope of our study, in keeping with the practice of other attempts to develop impact assessment models, we use the acronym SEAFORM to describe our socioeconomic impact assessment forecasting methodology.

as w e l l as numerous r e g i o n a l and p r o j e c t c h a r a c t e r i s t i c s , f o r each o f t h e

s i t e s i n t h e s tudy. These da ta were ob ta i ned f rom a number o f sources,

i n c l u d i n g u t i l i t i e s and con t rac to r s , c o l l e c t i v e ba rga in i ng agreements,

s t a t e agencies, census p u b l i c a t i o n s , and va r i ous o t h e r pub l i shed sources.

I n t h e a n a l y s i s phase o f t h e study, t h r e e separate analyses were

performed. These analyses inc lude :

a p r o f i l e ana l ys i s ;

s m u l t i v a r i a t e ana l ys i s ; and

a development o f f o r e c a s t i n g procedures.

The s p e c i f i c purpose o f t he p r o f i l e a n a l y s i s was t o examine cons t ruc-

t i o n worker su rvey da ta i n a sys temat i c f a s h i o n i n an a t tempt t o i d e n t i f y

p a t t e r n s o f v a r i a t i o n across s i t e s and across va r i ous groups o f workers

a t t h e same s i t e w i t h r espec t t o a number o f v a r i a b l e s c r i t i c a l t o e s t i -

mat ing socioeconomic impacts. These v a r i a b l e s inc lude :

( 1 ) m ig ran t p r o p o r t i o n ;

( 2 ) i n t e n t i o n o f movers t o remain i n t h e area;

( 3 ) r e l o c a t i o n o f dependents;

( 4 ) r e s i d e n t i a l l o c a t i o n pa t t e rns ;

( 5 ) t ype o f hous ing se lec ted ; and

( 6 ) demographic c h a r a c t e r i s t i c s o f movers.

The r e s u l t s o f t h i s a n a l y s i s served seve ra l purposes. F i r s t , t h e

r e s u l t s o f t h e a n a l y s i s were u s e f u l f o r ( 1 ) c o n f i r m i n g t h e e x t e n t t o

which t h e ev idence o f s i m i l a r i t y i n v a r i a b l e p r o f i l e s across s i t e s j u s t i -

f i e s t h e p r a c t i c e o f a s s e r t i n g s i m i l a r impacts o f c o n s t r u c t i o n i n one

area on t h e b a s i s o f case s t u d i e s conducted i n o t h e r areas; and ( 2 ) p ro-

v i d i n g t y p i c a l va lues o f p r o f i l e v a r i a b l e s which m igh t be u s e f u l i n eva l -

u a t i n g t he accuracy o f socioeconomic impact assessments. I n a d d i t i o n ,

t h e p r o f i l e a n a l y s i s r e s u l t s were u s e f u l i n f o r m u l a t i n g t h e m u l t i v a r i a t e

a n a l y s i s and i n t h e development o f f o r e c a s t i n g procedures. 2

ZA complete d i s c u s s i o n o f t h e p r o f i l e a n a l y s i s p o r t i o n o f t h i s s t u d y i s con ta ined i n an appendix which, because o f i t s leng th , i s presented as a separate volume--Volume 11- - to t h i s r e p o r t . The appendix volume e n t i t l e d " P r o f i l e Ana l ys i s o f Worker SurveysM i s s e l f - c o n t a i n e d and can be read independent l y o f t h i s r e p o r t .

The m u l t i v a r i a t e ana lys is was conducted i n an attempt t o exp la in the

observed v a r i a t i o n i n migrant p ropor t ions and r e s i d e n t i a l l o c a t i o n pa t-

te rns o f movers across the s i t e s and surveys included i n our study. I n

p a r t i c u l a r , t h i s analys is involved i d e n t i f y i n g the f a c t o r s t h a t i n f l uence

workers' r e l o c a t i o n decisions, d e f i n i n g var iab les t o measure these fac-

to rs , and i s o l a t i n g from among these var iab les , those which bes t exp la in

the observed v a r i a t i o n i n migrant p ropor t ions and r e s i d e n t i a l l o c a t i o n

pa t te rns across s i t e s .

L o g i t regression techniques were used t o exp la in the observed v a r i -

a t i o n i n migrant p ropor t ions among var ious c r a f t groups as a f u n c t i o n o f

t h e f o l lowing fac to rs : (1 ) income p o t e n t i a l associated w i t h employment

a t the s i t e ; ( 2 ) c r a f t - s p e c i f i c labor f o r c e requirements; ( 3 ) l o c a l

a v a i l a b i l i t y o f labor ; (4) competing demand f o r labor i n the region; ( 5 ) reg iona l c h a r a c t e r i s t i c s ; and ( 6 ) var ious c o n t r o l var iables. S i m i l a r l y ,

a mod i f ied g r a v i t y model was used t o exp la in the r e s i d e n t i a l l o c a t i o n

pa t te rns o f movers. The g r a v i t y model was mod i f ied t o a l low the d is tance

exponent t o vary across s i t e s and surveys. This was done by spec i f y i ng

the d is tance exponent as a func t i on o f f a c t o r s such as d i f fe rences i n

workforce composition, housing a v a i l a b i l i t y and o ther measures o f t he

a t t rac t i veness o f the l o c a l area.

The r e s u l t s o f t he p r o f i l e and m u l t i v a r i a t e analyses were then used as a bas is f o r the development o f f o recas t i ng procedures. Procedures f o r

p r e d i c t i n g the ex ten t o f worker i nm ig ra t i on and the r e s i d e n t i a l l o c a t i o n

pa t te rn o f i nm ig ra t i ng workers a t f u t u r e nuclear power p l a n t cons t ruc t ion

s i t e s were developed based upon the equations which were est imated i n the

m u l t i v a r i a t e p o r t i o n o f our analys is . Guidel ines f o r es t imat ing several

o ther important f a c t o r s which are c r i t i c a l t o socioeconomic impact

assessment (i.e., r e l o c a t i o n o f dependents, i n t e n t i o n t o remain i n t he

area, type o f housing selected, m a r i t a l s tatus, average f a m i l y s i z e ) were

a lso developed based upon our p r o f i l e ana lys is r e s u l t s .

This r e p o r t presents a d e t a i l e d d e s c r i p t i o n o f these fo recas t i ng

procedures, as w e l l as a summary o f t he analyses which l e d t o t h e i r

development. Whenever possib le, background in fo rmat ion and techn ica l

d e t a i l s are contained i n appendices. The main body o f the t e x t i s

d i v ided i n t o 4 chapters. Chapter I presents a b r i e f d iscussion o f the

data used i n t h i s study. The p r o f i l e ana lys is and m u l t i v a r i a t e ana lys is

results are summarized in Chapters I 1 and 111. The final chapter pre-

sents a detailed description of the forecasting procedures. The major

results of this study are summarized in the following section entitled

"Conclusions."

CONCLUSIONS

In~proved procedures f o r p r e d i c t i n g t h e number o f workers who w i l l

move t o an area t o work a t a f u t u r e n u c l e a r power p l a n t c o n s t r u c t i o n

s i t e , as w e l l as t h e r e s i d e n t i a l d i s t r i b u t i o n o f these i n m i g r a t i n g

workers i n communit ies s u r r o u n d i n g t h e s i t e were developed i n t h i s

s tudy . These f o r e c a s t i n g procedures were based upon t h e m i g r a t i o n and

r e s i d e n t i a l l o c a t i o n p a t t e r n s o f workers a t t e n n u c l e a r power p l a n t con-

s t r u c t i o n s i t e s . The performance o f t h e f o r e c a s t i n g procedures was

t e s t e d on t h e s i t e s i n ou r sample and t h e procedures were found t o pe r-

form remarkab ly we1 1. The mean a b s o l u t e d e v i a t i o n between a c t u a l and

p r e d i c t e d va lues o f o v e r a l l m i g r a n t p r o p o r t i o n s was o n l y 2.9 percentage

p o i n t s and t h e root-mean-square d e v i a t i o n was o n l y 3.7 percentage

p o i n t s . S i m i l a r l y , t h e mean a b s o l u t e d e v i a t i o n between p r e d i c t e d and

a c t u a l p r o p o r t i o n s o-f movers 1 i v i n g a t 5- mi le d i s t a n c e i n t e r v a l s o f t h e

s i t e exceeded 5 percentage p o i n t s i n t h e case o f o n l y 2 o f t h e 9 d i s t a n c e

bands.

I n a d d i t i o n t o t h e procedures f o r p r e d i c t i n g m i g r a n t p r o p o r t i o n s and

r e s i d e n t i a l l o c a t i o n p a t t e r n s a t f u t u r e n u c l e a r power p l a n t c o n s t r u c t i o n

s i t e s , procedures were a l s o developed f o r p r e d i c t i n g t h e i n t e n t i o n of

workers t o remain i n t h e area, t h e number o f movers who r e l o c a t e t h e i r f a m i l i e s , t h e t y p e o f hous ing t h a t workers w i l l s e l e c t , and t h e m a r i t a l

s t a t u s and average f a m i l y s i z e o f i n m i g r a t i n g workers . The a p p l i c a t i o n

o f t h e proposed procedures i n e s t i m a t i n g t h e socioeconomic impacts asso-

c i a t e d w i t h f u t u r e c o n s t r u c t i o n p r o j e c t s can be expected t o p r o v i d e

g r e a t e r accuracy than was p r e v i o u s l y p o s s i b l e .

I n t h e process o f deve lop ing these procedures a much b e t t e r under-

s t a n d i n g o f t h e f a c t o r s u n d e r l y i n g t h e v a r i a t i o n i n key v a r i a b l e s o f

i n t e r e s t i n socioeconomic impact assessments was achieved. Some o f t h e

ma jo r f i n d i n g s i n t h i s r e g a r d were:

1. Work force c o m p o s i t i o n ( t h e number o f workers f r o m v a r i o u s noncon-

s t r u c t i o n and c o n s t r u c t i o n c r a f t s ) d u r i n g c o n s t r u c t i o n i s an e x t r e m e l y

i m p o r t a n t de te rm inan t o f o v e r a l l m i g r a n t p r o p o r t i o n s and r e s i d e n t i a l

l o c a t i o n p a t t e r n s a t a s i t e . For example, c o n s t r u c t i o n workers have

lower m i g r a n t p r o p o r t i o n s than n o n c o n s t r u c t i o n workers and i n genera l

a l s o l o c a t e c l o s e r t o t h e s i t e . Furthermore, among c o n s t r u c t i o n workers

those workers who a re more s k i l l e d (and t h e r e f o r e a re r e l a t i v e l y more

scarce) have h i g h e r m ig ran t p r o p o r t i o n s and these movers t y p i c a l l y l i v e

c l o s e r t o t h e s i t e than o t h e r c o n s t r u c t i o n workers. S ince workforce

composi t ion v a r i e s across s i t e s as w e l l as a t t h e same s i t e by s tage o f

p r o j e c t complet ion, i t becomes an impor tan t f e a t u r e t o cons ider i n making

socioeconomic impact assessments.

2. The n a t u r e of employment o p p o r t u n i t i e s a t a c o n s t r u c t i o n s i t e

d i f f e r s f o r d i f f e r e n t c o n s t r u c t i o n c r a f t groups. Some more s p e c i a l i z e d

c r a f t s a re r e q u i r e d f o r s h o r t per iods o f t ime, whereas o the r l e s s s k i l l e d

c r a f t s a re r e q u i r e d throughout t h e e n t i r e c o n s t r u c t i o n per iod . D i f f e r -

ences i n t h e income p o t e n t i a l assoc ia ted w i t h a p a r t i c u l a r move a r e a

r e s u l t o f d i f f e r e n c e s i n l a b o r requirements. The expected d u r a t i o n and

c o n t i n u i t y o f employment and t h e expected growth p a t t e r n o f employment

o p p o r t u n i t i e s a t t h e s i t e va ry cons ide rab l y across c r a f t s . These v a r i -

ab les were found t o be an impor tan t source o f t h e observed v a r i a t i o n i n

c r a f t - s p e c i f i c m ig ran t p ropo r t i ons across s i t e s .

3 . The competing demand f o r l abo r a t o t h e r power p l a n t c o n s t r u c t i o n

p r o j e c t s i n t h e r e g i o n ( w i t h i n 50 m i l e s o f t he c o n s t r u c t i o n s i t e ) and t h e

d i s t a n c e f rom t h e h i r i n g h a l l o f t h e un ion l o c a l w i t h j u r i s d i c t i o n over

t h e p r o j e c t p rov ide reasonably good p roxy measures f o r t h e demand and

supp ly o f l a b o r i n t h e area. M ig ran t p ropo r t i ons inc rease w i t h h i ghe r

u t i l i z a t i o n o f l a b o r and w i t h longer d is tances f rom un ion h a l l s . These

p roxy measures o f 1 abor a v a i l a b i l i t y a re e a s i l y ob ta ined and, t he re fo re ,

can be cons idered i n f o r e c a s t i n g o f m ig ran t p ropo r t i ons a t f u t u r e con-

s t r u c t i o n s i t e s .

4. Housing a v a i l a b i l i t y and r e g i o n a l popu la t i on were shown t o be key

cons ide ra t i ons i n b o t h t h e d e c i s i o n o f workers t o move t o an area and

t h e i r r e s i d e n t i a l l o c a t i o n dec is ions . Larger popu la t i ons and g r e a t e r

hous ing a v a i l a b i l i t y a re sources o f a t t r a c t i o n t o p o t e n t i a l workers. The

i n f l u e n c e o f more r u r a l sur roundings i s t o inc rease t h e commuting d i s -

tance o f workers a t t h e s i t e . M ig ran t p ropo r t i ons d e c l i n e because many

workers choose t o commute longer d is tances r a t h e r than move, and those

who do move t o work a t t h e s i t e choose t o l i v e f a r t h e r from t h e i r p l ace

o f work.

Th i s s tudy a l s o made some impor tan t methodolog ica l c o n t r i b u t i o n s t o

socioeconomic impact assessment. It suggested ways i n which da ta f rom a

l i m i t e d number o f s i t e s c o u l d be used t o conduct s t a t i s t i c a l l y v a l i d

analyses t o eva lua te key v a r i a b l e s i n socioeconomic impact assessments.

I n our m ig ran t p r o p o r t i o n ana lys is , we showed t h a t us ing major cons t ruc-

t i o n c r a f t s as t h e u n i t o f a n a l y s i s p rov i ded n o t o n l y g r e a t e r degrees of

freedom b u t was a l s o t h e o r e t i c a l l y supe r i o r f o r ana lyz ing t h e aggregate

behav io r o f c o n s t r u c t i o n workers a t a s i t e . Such an approach a l l ows one

t o use observed d i f f e r e n c e s i n m ig ran t p r o p o r t i o n s among va r i ous worker

groups t o e x p l a i n t h e o v e r a l l m ig ran t p r o p o r t i o n s a t a c o n s t r u c t i o n

s i t e . I n our r e s i d e n t i a l l o c a t i o n a n a l y s i s we adopted a g r a v i t y model

which was m o d i f i e d t o a l l o w d i f f e r e n c e s i n r e g i o n a l and p r o j e c t charac-

t e r i s t i c s t o i n f l u e n c e t h e d i s t a n c e exponent o f t h e model. As a r e s u l t ,

t h e model i s capable o f y i e l d i n g d i f f e r e n c e s i n r e s i d e n t i a l l o c a t i o n p a t -

t e r n s which r e f l e c t a number o f f a c t o r s o t h e r than t h e popu la t i on and

d i s t ance o f communit ies f rom t h e c o n s t r u c t i o n s i t e .

However, d e s p i t e t h e f a c t t h a t t h e f o r e c a s t i n g procedures descr ibed

i n t h i s r e p o r t were developed based upon a l a r g e number o f nuc l ea r power

p l a n t c o n s t r u c t i o n s i t e s , t h e i r g e n e r a l i z a b i l t y extends o n l y t o those

f u t u r e nuc lea r power p l a n t s i t e s whose major c h a r a c t e r i s t i c s a re s i m i 1 a r

t o t h e c h a r a c t e r i s t i c s o f s i t e s i nc l uded i n our sample. Nevertheless,

t h e l a r g e number o f s i t e s , and t h e v a r i a t i o n i n a number o f c r i t i c a l

dimensions among t h e s i t e s i nc l uded i n our study, serve t o make t h e

r e s u l t s of ou r a n a l y s i s g e n e r a l i z a b l e t o a l a r g e number o f f u t u r e con-

s t r u c t i o n s i t e s . I f t h e c h a r a c t e r i s t i c s o f t h e f u t u r e s i t e s a re ve r y

d i f f e r e n t f rom those o f t h e s i t e s i n our sample ( i .e., ve ry remote), then

t he proposed f o recas t i ng procedures would n o t be appropr ia te . However,

t h e methods which were used i n t h i s a n a l y s i s w i l l s t i l l be o f va lue i n

such cases. New equa t ions can be es t imated which i n c l u d e s i t e s w i t h

app rop r i a t e c h a r a c t e r i s t i c s , and these r e s u l t s used t o s p e c i f y t he

d e s i r e d f o r e c a s t i n g procedures.

CHAPTER I

DATA

Fundamental to a study of this nature is the collection of a vast

amount of information. Indeed, the preliminary step in this project

involved an enormous data collection effort--the collection of primary as

well as secondary data. This represents the largest and most comprehen-

sive data set ever assembled for nuclear power plant construction proj-

ects. This chapter briefly describes the data collection effort. The

chapter is divided into 2 sections. The first section introduces the

primary and secondary data sources and the second section briefly dis-

cusses the quality and generalizability of the data. A more detailed

discussion of the data collection effort is presented in Appendix A.

DATA SOURCES

The data set which was assembled for this study consists of informa-

tion on over 49,000 workers from 28 surveys conducted at 13 different

nuclear power plant construction sites. In addition to the survey data

we collected a considerable amount of secondary data regarding the

nuclear power plant projects and the surrounding regions.

Survey Data

The survey data included in the study were obtained in two different

ways. Worker surveys were conducted at four nuclear power plant con-

struction sites specif ical ly for this study.' Cost considerations

'conducting a construction worker survey is not an easy task. This difficulty stems from the very nature of the construction site and the characteristics of the construction workforce. We successfully conducted worker surveys at four nuclear power plant construction sites. Our success in implementing these surveys can, to a large extent, be attributed to careful preparation for the survey activity and attention to detail in survey adminis Tat ion

. The task required an extensive use of time and resources and w s a valuable learning experience. For this reason we felt that it might be helpful to share our experience with others. Appendix 0 , entitled "Construction Worker Surveys: A Means for Success- ful Implementation" systematically addresses the problems associated with conducting construction worker surveys and suggests possible methods to solve these problems. This document may be useful to others conducting worker surveys at large construction projects.

d i d no t permi t us t o survey workers a t more than f o u r s i t e s . However, we

were able t o increase the number o f s i t e s i n our ana lys is by i n c l u d i n g

da ta from s i m i l a r surveys which were conducted by u t i l i t i e s a t n ine addi-

t iona l s i t e s .

We exerc ised extreme caut ion i n s e l e c t i n g the surveys t o be inc luded

i n our da ta set . Only surveys which we regarded as acceptable w i t h

respect t o c e r t a i n c r i t e r i a were included i n the study. These c r i t e r i a

were :

( 1 ) a1 1 workers a t the s i t e were surveyed;

( 2 ) t he survey instrument was appropr iate f o r analyz ing va r iab les o f i n t e r e s t t o our study; and

( 3 ) t h e sampling procedures and response r a t e s o f t he surveys met c e r t a i n minimum standards.

Since the surveys were conducted by several research groups us ing

d i f f e r e n t survey instruments, the data c o l l e c t e d were n o t i d e n t i c a l f o r

a l l s i t e s . However, there was s u f f i c i e n t s i m i l a r i t y i n t he in fo rmat ion

gathered i n these surveys t o address the major quest ions o f t h i s study.

I n general, workers were asked t o p rov ide the f o l l o w i n g in fo rmat ion :

a migrant s ta tus ( i .e. , whether o r n o t the worker moved t o t h e area t o work a t the cons t ruc t i on s i t e ) ;

a whether o r n o t a mover re loca ted h i s fami ly ;

a the i n t e n t i o n t o remain i n the area a f t e r complet ion o f t he p r o j e c t ;

a r e s i d e n t i a l loca t ion ;

a type o f housing selected;

a occupation; and

a var ious demographic c h a r a c t e r i s t i c s ( i .e. , age, m a r i t a l s tatus, number o f c h i l d r e n ) .

Fur the r d e t a i l s regarding survey admin is t ra t ion , t he na ture of t he data

co l l ec ted , survey instruments used and the c h a r a c t e r i s t i c s of t h e s i t e s

a t which the surveys were conducted are contained i n Appendix A.

Secondary Data

Considerable secondary da ta were requ i red f o r t h e m u l t i v a r i a t e anal-

y s i s p o r t i o n o f t h i s study. An extensive data c o l l e c t i o n e f f o r t was

conducted i n an attempt t o o b t a i n va r iab les which would r e f l e c t the many

f a c t o r s under ly ing the observed v a r i a t i o n i n migrant p ropo r t i ons and

r e s i d e n t i a l l o c a t i o n pa t te rns across s i t e s and across var ious c r a f t

groups. In particular, secondary data sources were used to provide vari-

ables which reflect the following factors:

a income potential associated with employment at the site for various craft groups;

a craft-specific labor force requirements;

a availability of labor in the region;

competing demand for labor in the region;

a population and housing availability in the region; and

a other regional and community characteristics.

These data were obtained from a number of different sources including

collective bargaining agreements, utilities and contractors, state agen-

cies, and various published sources. The problems encountered in the

collection of the secondary data, the precise data items collected and

the various data sources are described in Appendix A.

QUALITY AND GENERALIZABILITY OF THE DATA

There are several features of the data set which reflect the high

quality of the data, support the generalizability of our results and

increase the usefulness of this data set for other studies. These

include the following: response rates achieved, amount of information

contained in the survey data, and the extent of variation in relevant regional and project characteristics. Each of these features is high-

lighted briefly below.

Response Rates

In each of the 28 surveys, an attempt was made to survey all workers

at each site at the time of the survey. The response rates ranged from a

high of 94.9 percent to a low of 60.2 percent, with an overall response rate of approximately 81.5 percent. In general, these response rates

were considerably higher than the response rates which are typically

achieved in construction worker surveys. The high response rates of

these census surveys considerably increases the confidence that can be

placed in the results of our analyses based on these data.

Extensiveness of the Data

The data set is also rich in the sense that the surveys contain con-

siderable information on worker characteristics and worker decisions.

The information contained in all 28 surveys was sufficient to allow us to

address quest ions regardi ng2:

' the proportion of workers at a site who moved to the area to work at the site;

the type of housing in which the movers live;

0 the residential location patterns of both movers and nonmovers; and

e the household composition (i.e., average family size and number of school-age children) of inmigrating workers.

Considerably more information was available for some sites, which allowed

us to address a number of other issues. These issues include:

the intention of movers to remain in the area;

0 whether or not movers maintain a permanent residence elsewhere;

relocation of dependents; and

demographic characteristics of nonmovers as well as movers.

Variation in Regional and Project Characteristics Finally, these 13 sites and 28 surveys exhibit a wide range of vari-

ation in a number of important dimensions. For example, considerable

variation can be observed with respect to regional distribution, the

existence of other power plant construction activity in the region, local

community characteristics, stage of project completion, utility and contractor arrangements, extent of unionization, and various power plant

characteristics. Consequently, the data can be expected to yield esti-

mates of critical socioeconomic variables under a variety of situations.

This increases the usefulness of such an analysis, since an examination

of these data is more likely to yield results which are generalizable to

a variety of future nuclear power plant siting situations.

In sumnary, the primary and secondary data collected for this study

represent the largest and most comprehensive data set ever assembled for

nuclear power plant construction projects. Such an extensive data base

2~owever, in the case of 4 surveys which were conducted at 3 different sites, occupational information was not defined in the same way as for the other 24 surveys. As a result, it was necessary to exclude these surveys from all craft-specific analyses in this study.

cou ld be extremely va luable i n addressing a number o f quest ions regard ing

socioeconomic impacts and nuc lear power p l a n t s i t i n g . In t h i s s tudy the

da ta were used t o examine the l abo r f o r c e m ig ra t i on and r e s i d e n t i a l loca-

t i o n dec is ions o f nuc lear power p l a n t cons t ruc t i on workers and t o develop

a methodology f o r f o r e c a s t i n g labor f o r c e m i g r a t i o n pa t te rns a t f u t u r e

cons t ruc t i on s i t e s . However, t he da ta base cou ld a lso be used both i n

p o l i c y - o r i e n t e d analyses and i n t he prepara t ion o f environmental impact

statements.

CHAPTER I1

PROFILE ANALYSIS - SUMMARY OF RESULTS

In the profile analysis portion of this study we conducted a detailed

examination of the construction worker survey data in an attempt to iden-

tify patterns of variation across sites and across various groups of

workers at the same site with respect to a number of variables critical

to estimating socioeconomic impacts. A separate volume entitled "SEAFORM

- Profile Analysis of Worker Surveys Conducted at Nuclear Power Plant Construction Sites" was prepared as an appendix to this report. This

appendix is very extensive and contains a comprehensive presentation of

the data and a more detailed discussion of the results presented here.

In this chapter we summarize the major findings of the profile anal-

ysis. In addition, .we discuss how the insights yielded by this analysis

were useful in the multivariate portion of our analysis, which was a

critical step in our development of procedures for forecasting migrant

proportions and residential location patterns of movers at future power

plant construction sites. The results of this analysis also suggested

means by which one could make improved predictions regarding the reloca-

tion of dependents, intention to remain in the area, type of housing selected and demographic characteristics of movers.

This chapter is divided into 3 sections. The first section describes

the major focus of the profile analysis. The second section presents a

brief summary of results. The final section discusses the implications

of the findings for our multivariate analysis and for the development of

forecast i ng procedures.

FOCUS OF THE PROFILE ANALYSIS

Differences in migrant proportions among various occupational groups

have been observed in past studies.' However, no attempt has been made

l ~ o r example, see Mountain West Research, Inc., Construct ion Worker Profile, Final Report (Washington, D.C.: Old West Regional Commission, 19/5), p. 19.

t o examine d i f ferences i n va r i ab les such as migrant propor t ions, i n ten-

t i o n t o remain i n t he area, r e l o c a t i o n o f dependents, r e s i d e n t i a l loca-

t i o n pat terns, type o f housing, and demographic c h a r a c t e r i s t i c s o f movers

among var ious worker groups i n any systematic way. The i n t e n t o f t h i s

ana lys is was t o determine the ex ten t t o which occupational groups e x h i b i t

d i f f e rences w i t h respect t o va r i ab les which are c r i t i c a l t o socioeconomic

impact assessment and, there fore , t o determine the ex ten t t o which work-

fo rce composit ion cou ld be an important f a c t o r i n understanding the

observed v a r i a t i o n i n t he va r iab les o f i n t e r e s t across s i t e s .

The importance o f cons ider ing workforce composit ion stems f rom the

f a c t t h a t both the demand f o r l abo r a t the cons t ruc t i on s i t e and the

a v a i l a b i l i t y o f l abo r w i t h i n commuting d is tance vary f o r d i f f e r e n t c r a f t

groups. For instance, c r a f t s w i t h more spec ia l i zed s k i l l s are requ i red

f o r jobs o f r e l a t i v e l y l i m i t e d dura t ion , whereas o ther c r a f t s are

requ i red throughout t he e n t i r e cons t ruc t i on phase. Moreover, o ther

oppor tun i t i es f o r employment i n t he area du r ing and upon complet ion o f

the p r o j e c t vary considerably f o r d i f f e r e n t c r a f t s . Since i t i s l i k e l y

t h a t these f a c t o r s i n f l uence workers' r e l o c a t i o n decisions, our ana lys i s

attempts t o measure the ex ten t t o which d i f f e rences i n va r i ab les of

i n t e r e s t are observed among var ious c r a f t groups.

F i r s t , we d i v ided workers i n t o two broad occupational groups--

cons t ruc t i o n and nonconstruct i o n workers .' Each o f these groups was

then f u r t h e r subdivided. I n the case o f t he nonconstruct ion group,

workers were d i v ided i n t o two subgroups. The f i r s t group inc luded a l l

managers, engineers and supervisors. The second group inc luded the

remaining nonconstruct ion workers ( i .e., t h e c l e r i c a l , secu r i t y , and

medical /nurs ing s t a f f ) .

We f u r t h e r d i v ided cons t ruc t i on workers i n t o th ree groups based on

t h e r e l a t i v e s c a r c i t y o f labor among the d i f f e r e n t cons t ruc t i on c r a f t s . 3

This c l a s s i f i c a t i o n o f c r a f t s i n t o s c a r c i t y groups was based on two

* ~ n f o r m a t i o n on workers' c r a f t s was n o t ava i l ab le f o r f o u r o f the surveys i n our sample. Therefore, i t was necessary t o exclude these s i t e s f rom our ana lys is o f v a r i a t i o n among var ious subgroups o f workers.

3 ~ e f i r s t subdivided workers i n t o e i g h t major cons t ruc t i on c r a f t groups. However, t h e extensive v a r i a t i o n i n migrant p ropo r t i ons across c r a f t groups made it extremely d i f f i c u l t t o observe any cons i s ten t pa t- te rns of v a r i a t i o n among groups w i thou t conduct ing a m u l t i v a r i a t e ana lys is .

f a c t o r s : ( 1 ) t he s i z e o f t he c r a f t l abo r markets, and ( 2 ) t he demand f o r

t h e i r serv ices a t nuc lear power p l a n t cons t ruc t i on s i t e s . We def ined our

proxy measure o f r e l a t i v e s c a r c i t y o f l abo r t o be the r a t i o o f t he number

o f manhours o f l abo r requ i red i n each c r a f t t o cons t ruc t a t y p i c a l

nuc lear power p l a n t and t h e t o t a l number o f union members i n t he con-

s t r u c t i o n c r a f t i n t he na t ion . 4

Th i s r a t i o was used t o c l a s s i f y a l l cons t ruc t i on c r a f t s except

laborers and teamsters i n t o two s c a r c i t y groups: a scarce c r a f t group

and a common c r a f t group.5 Laborers and teamsters formed the t h i r d

s c a r c i t y group--an abundant c r a f t group. We t r e a t e d laborers and team-

s t e r s d i f f e r e n t l y f rom the o the r c r a f t s because these jobs do no t r e q u i r e

very spec ia l i zed s k i l l s . These occupat ions do no t have lengthy appren-

t i c e s h i p programs, as i s t he case w i t h o the r cons t ruc t i on c r a f t s . There-

fo re , i t i s re1 a t i v e l y easy t o meet an increase i n t he demand f o r

laborers and teamsters by a t t r a c t i n g workers f rom o the r occupations.

I n a d d i t i o n t o our examination w i t h respect t o var ious worker groups,

we a l so examined poss ib le v a r i a t i o n i n re levan t va r i ab les w i t h respect t o

region. Among the 13 s i t e s inc luded i n our study, f o u r were loca ted i n

nor thern s ta tes and n ine were loca ted i n southern s tates. We examined

t h e data i n an e f f o r t t o determine t h e ex ten t t o which systematic d i f f e r -

ences e x i s t between nor thern and southern s i t e s .

S i x f ac to rs were i d e n t i f i e d as c r i t i c a l f o r accura te ly determin ing

t h e socioeconomic impacts associated w i t h l a r g e cons t ruc t i on p r o j e c t s .

These fac to rs , i n c l u d i n g d e f i n i t i o n o f t he va r i ab les used i n t he anal-

y s i s , are as fo l l ows :

Migrant p ropor t ion- - the p ropo r t i on o f workers who moved t o the area t o work a t t h e s i t e . Workers were c l a s s i f i e d as movers and nonmovers i n two ways, depending upon t h e survey instrument used. Some quest ionnai res asked workers whether o r no t they had

4 ~ e recognize t h a t t h i s measure o f r e l a t i v e s c a r c i t y o f labor i s r a t h e r crude. I d e a l l y , t h i s measure should have been based upon reg iona l e s t i - mates o f t he demand and supply o f t he var ious cons t ruc t i on c r a f t s . Unfor tunate ly , data t o develop such a s c a r c i t y measure were n o t ava i l ab le .

5 ~ h e scarce c r a f t group inc ludes p i p e f i t t e r s , i ronworkers, asbestos workers, and boi lermakers. Carpenters, e l e c t r i c i a n s , opera t ing engineers, sheetmetal workers, b r i ck laye rs , and cement masons comprise the common group.

moved t o the area t o work a t the s i t e . Workers who responded "yes" t o t h i s quest ion were considered t o be movers. Other quest ionnaires asked f o r t he worker 's cu r ren t address and t h e i r address before beginning work a t the s i t e . A comparison o f these responses was used t o c l a s s i f y workers as e i t h e r movers o r nonmovers.

I n t e n t i o n t o remain i n t h e area-- the p ropo r t i on o f movers who are temuorarv (movers who in tend t o leave the area before o r upon completion o f the p r o j e c t ) . Two d i f f e r e n t measures were def ined t o examine t h i s f a c t o r . F i r s t , based upon workers' responses t o a d i r e c t quest ion regarding t h e i r i n t e n t i o n t o remain i n the area, we c l a s s i f i e d movers as e i t h e r permanent o r temporary movers. Temporary movers were def ined t o be those movers who expected t o leave the area e i t h e r before o r on com- p l e t i o n o f t he p ro jec t . Second, as an i n d i r e c t measure, we examined the p ropo r t i on o f movers who main ta in a permanent residence elsewhere as an i n d i c a t i o n o f i n t e n t i o n t o leave the area upon complet ion o f t h e p r o j e c t .

a Relocat ion o f dependents--the p ropo r t i on o f movers w i t h f a m i l y present. I n our ana lys is we examined movers w i t h f a m i l y present as a p ropo r t i on o f a l i movers, r a t h e r than a propor t ion- o f mar r ied movers. Thus, movers w i thout f a m i l i e s inc lude s i n g l e movers as we l l as marr ied movers who d i d no t r e l o c a t e t h e i r f a m i l i e s .

a Res ident ia l l oca t i on- - the p ropo r t i on o f movers and nonmovers l i v i n g a t var ious d is tances f rom the cons t ruc t i on s i t e . Two d i f f e r e n t var iab les were examined. F i r s t we examined the pro- p o r t i o n o f movers and nonmovers l i v i n g i n 5-mi le i n t e r v a l s o f t h e s i t e . Second, we examined the p ropo r t i on of movers and nonmovers 1 i v i n g i n t he l o c a l impact area ( i .e., w i t h i n 15 m i l e s of t he s i t e ) .

Type o f housing-- the p ropo r t i on o f movers l i v i n g i n f o u r d i f f e r - en t housing types. The f o u r housing types which were examined - - . inc lude houses, mobi le homes, apartments, and o the r temporary housing ( i .e., hote ls , motels, boarding and rooming houses).

a Demographic c h a r a c t e r i s t i c s o f movers--marital s ta tus , f a m i l y s ize, number o f school-age c h i l d r e n and income.

The r e s u l t s o f our ana lys is i n d i c a t e t h a t o v e r a l l migrant p ropor t ions

a t a s i t e t y p i c a l l y range from 15 t o 35 percent . More than h a l f o f a l l

movers i n tend t o leave the area before o r upon complet ion of the con-

s t r u c t i o n p r o j e c t . Although these temporary movers are l ess l i k e l y t o

r e l o c a t e t h e i r f a m i l i e s , 50 t o 70 percent o f the workers who move i n t o

the area are l i k e l y t o b r i n g t h e i r f a m i l i e s w i t h them. I n general,

movers l i v e r e l a t i v e l y c lose t o the cons t ruc t i on s i t e . I n f a c t , we found

t h a t 45 t o 85 percent o f the movers 1 i v e i n the l o c a l area ( w i t h i n 15

. . m i l e s o f the s i t e ) compared t o o n l y 10 t o 25 percent o f the nonmovers.

Movers who re loca te t h e i r f a m i l i e s t y p i c a l l y l i v e f a r t h e r away from t h e

s i t e , as do the permanent movers. Most movers and almost a l l movers w i t h

f a m i l i e s choose t o l i v e i n s i n g l e f a m i l y houses and mobi le homes.

The c h a r a c t e r i s t i c s o f the movers d i d no t vary much from s i t e t o

s i t e . About 75 t o 85 percent o f t he movers are marr ied. The average

f a m i l y s i z e o f those movers who re loca te t h e i r f a m i l i e s i s 3.25, and the

average number o f school-age c h i l d r e n among movers i s 0.8. The f a m i l y

income o f movers general l y exceeds $20,000 ( 1978 do1 1 ars ) . We found s i g n i f i c a n t d i f f e rences when we examined p r o f i l e var iab les

by var ious worker groups. F o r t y t o 60 percent o f nonconstruct ion workers

are movers, wh i l e o n l y 10 t o 30 percent o f cons t ruc t i on workers are

movers. The d i f f e r e n c e i s p r i m a r i l y due t o management workers--60 t o 75

percent o f those workers are movers. Nonconstruct ion movers (60 t o 75

percent) are more l i k e l y t o leave the area by the t ime the p r o j e c t i s

completed than cons t ruc t i on movers (40 t o 50 percent) . However, desp i te

the more temporary nature o f t h e i r move, nonconstruct ion workers are more

l i k e l y t o re loca te t h e i r f a m i l i e s than are cons t ruc t i on workers. There

i s no d i f ference i n the r e s i d e n t i a l l o c a t i o n pa t te rns o f cons t ruc t i on and

nonconstruct ion movers, al though cons t ruc t i on movers are more l i k e l y t o

l i v e i n mobi le homes and nonconstruct ion movers are more l i k e l y t o l i v e

i n s i n g l e f a m i l y houses.

Among cons t ruc t i on workers, some s a l i e n t d i f f e rences were observed

between workers from d i f f e r e n t c r a f t s . We found t h a t the migrant propor-

t i o n s t y p i c a l l y range from 15 t o 45 percent among workers f rom scarce

c ra f t s , b u t range from 10 t o 30 percent among workers from common c r a f t s

and o n l y 5 t o 10 percent among workers f rom abundant c r a f t s . The movers

among t h e scarce c r a f t group are more l i k e l y t o leave the 'a rea before o r

upon complet ion o f the p r o j e c t and are less l i k e l y t o re loca te t h e i r

f a m i l i e s . However, t he l o c a t i o n and type o f housing chosen by movers

f rom scarce c r a f t s i s no t very d i f f e r e n t from t h a t o f movers from o ther

c r a f t groups.

F i n a l l y , we d i d observe some evidence o f d i s t i n c t d i f f e rences i n

p r o f i l e var iab les w i t h respect t o region. Overa l l m igrant p ropor t ions a t

t h e southern s i t e s are somewhat h igher than those a t the nor thern s i t e s .

Also, s i g n i f i c a n t l y h igher p ropor t ions o f movers r e l o c a t e t h e i r f a m i l i e s

i n t he South than do movers i n t he North. Although the re i s no apparent

reg iona l d i f f e r e n c e i n the r e s i d e n t i a l l o c a t i o n pa t te rns o f movers, there

i s a s i g n i f i c a n t d i f f e r e n c e i n the type of housing chosen by movers i n

the two regions. A much h igher p ropo r t i on o f movers l i v e i n mobi le

homes, and t o a lesser ex ten t i n s i n g l e f a m i l y houses, i n the South than

i n the North. S i m i l a r l y , lower p ropor t ions of movers l i v e i n apartments,

ho te ls , motels, and rooming houses i n the South than i n t he North.

The above d iscussion has been a general overview o f the major f i n d -

ings of our p r o f i l e analys is . A more d e t a i l e d summary o f s p e c i f i c f i n d -

ings of t he ana lys is o f each p r o f i l e v a r i a b l e i s presented below.

1. Migrant Propor t ions

The major f i n d i n g s o f our p r o f i l e ana lys is o f migrant p ropor t ions are

as fo l l ows :

There i s a l a rge v a r i a t i o n across s i t e s i n terms o f o v e r a l l m igrant p ropor t ions and i n migrant p ropor t ions among var ious worker groups. Typ i ca l l y , o v e r a l l migrant p ropor t ions range f rom 15 t o 35 percent.

0 Migrant p ropor t ions are h igher among nonconstruct ion workers (40 t o 60 percent) than among cons t ruc t i on workers (10 t o 30 percen t ) .

a Higher migrant p ropor t ions among nonconstruct ion workers are due t o management workers (60 t o 75 percent) and n o t t o c l e r i c a l workers (20 t o 35 percent) .

R e l a t i v e s c a r c i t y o f labor exp la ins a considerable amount o f v a r i a t i o n among cons t ruc t i on c r a f t s . Migrant p ropor t ions among workers from scarce c r a f t s (15 t o 45 percent) are h igher than those among workers from common c r a f t s (10 t o 30 percent), which i n t u r n are h igher than migrant p ropor t ions among workers from abundant c r a f t s ( 5 t o 10 percent) .

a A s i g n i f i c a n t d i f f e r e n c e i n migrant p ropo r t i on by reg ion among var ious worker groups i s found o n l y i n the case o f nonconstruc- t i o n workers. Th i s reg iona l d i f f e r e n c e r e f l e c t s the d i f f e r e n c e i n the migrant p ropor t ions among c l e r i c a l workers. Migrant p ropor t ions among c l e r i c a l workers i n the North (10 t o 20 percen t ) a re lower than those i n the South (25 t o 30 percent) .

2. I n t e n t i o n t o Remain i n the Area

The major f i n d i n g s o f our p r o f i l e ana lys is o f t he movers' i n t e n t i o n s

t o remain i n t he area are as fo l l ows :

Temporary movers constitute a significant proportion of the movers at a site. Typically, 50 to 60 percent of all movers expect to leave the area before or upon the completion of the construction project.

a The proportion of movers who could be classified as temporary among nonconstruction workers (60 to 75 percent) is higher than that among construction workers (40 to 50 percent).

Nonconstruction movers, despite the temporary nature of their employment, are less likely to maintain a permanent residence elsewhere than are construction movers. Thus, use of a permanent residence as an indication of intention to remain in the area is appropriate for construction workers but not for nonconstruct ion workers.

3. Relocation of De~endents

The major findings of our profile analysis of relocation of depen-

dents are as follows;

a There is a large variation across sites in terms of the proportions of all movers with family present and in the proportions among various worker groups.

a Typically, overall proportions of movers with family present range from 50 to 70 percent. The overall proportions of movers with family present are higher among sites in the South than among sites in the North.

a Region explains a considerable amount of variation in the proportions of movers with family present. In all cases proportions for various worker groups were higher in the South than in the North.

Proportions of movers with family present are higher among nonconstruction movers (in the North from 60 to 75 percent and in the South from 70 to 85 percent) than among construction movers (in the North 45 to 55 percent and in the South from 50 to 70 percent) .

a In the North, proportions of movers with family present are lower among movers from scarce crafts (40 to 50 percent) than among movers from other crafts (50 to 55 percent). A similar difference between craft groups is not apparent among southern sites.

a Among construct ion movers, relocat ion of dependents is re1 ated to movers' intentions to remain in the area. Among nonconstruction movers, the intended length of stay is not related to the proportion of movers with family present.

4. Res ident ia l Locat ion

The major f i n d i n g s o f our p r o f i l e ana lys is o f r e s i d e n t i a l l o c a t i o n

are as fo l l ows :

The r e s i d e n t i a l l o c a t i o n pa t te rns o f movers and nonmovers are d i f f e r e n t and they both e x h i b i t considerable v a r i a t i o n across s i t e s . The v a r i a t i o n stems f rom d i f f e rences i n the numbers and s izes o f communities i n the regions surrounding the s i t e s .

a Higher p ropor t ions o f movers res ide i n communities c l o s e r t o the s i t e r e l a t i v e t o the propor t ions o f nonmovers r e s i d i n g i n those communities. Typ i ca l l y , h igher p ropor t ions of movers i n r e l a - t i o n t o the p ropo r t i on o f nonmovers l i v e i n communities w i t h i n 20 m i l e s o f the s i t e and v i ce versa i n communities beyond 20 m i l e s from a s i t e .

a I n t h e North nonmovers t y p i c a l l y l i v e much c l o s e r t o t he s i t e than i n t h e South, bu t t he re i s no such reg iona l d i f f e r e n c e i n t he r e s i d e n t i a l l o c a t i o n pa t te rns o f movers.

Even i n the most r u r a l s i t e s 70 percent o f t he movers l i v e w i th- i n 25 m i l e s o f the s i t e .

The o v e r a l l p ropor t ions o f movers 1 i v i n g i n the l o c a l area (45 t o 85 percent) i s s i g n i f i c a n t l y g rea ter than the p ropo r t i ons o f nonmovers l i v i n g i n t he l o c a l area (10 t o 25 percent ) .

The p ropo r t i ons o f movers l i v i n g i n the l o c a l area are s i m i l a r f o r a l l worker groups.

The presence o r absence o f a f a m i l y and movers' i n t e n t i o n s t o remain i n the area i n f l uence r e s i d e n t i a l l o c a t i o n decis ions.

5. Type o f Housing

The major f i n d i n g s o f our p r o f i l e ana lys is o f type o f housing are as

fo l l ows :

There i s considerable v a r i a t i o n i n the type o f housing selected by movers across s i t e s . General ly, 60 t o 90 percent o f movers l i v e i n s i n g l e f a m i l y houses o r mobi le homes.

Typ i ca l ranges o f the propor t ions o f movers l i v i n g i n each of t he four housing types are as fo l lows: s i n g l e f a m i l y houses-- 30 t o 45 percent; mobi le homes--20 t o 45 percent; apartments-- 10 t o 20 percent; and a1 1 o ther types o f housing-- less than 10 percent.

There are s i g n i f i c a n t d i f f e rences i n the type o f housing se lec ted by cons t ruc t i on and nonconstruct ion movers:

- - Lower p ropor t ions o f cons t ruc t i on movers (25 t o 40 per - cen t ) 1 i v e i n s i n g l e fami l y houses than nonconstruct ion movers (50 t o 65 percent) ;

- - Higher p ropo r t i ons o f cons t ruc t i on movers l i v e i n mob i le homes (35 t o 55 percent) than nonconstruct ion movers (10 t o 25 percent ) ;

- - Somewhat lower p ropo r t i ons o f cons t ruc t i o n movers ( 5 t o 20 percent ) 1 i ve i n apartments than nonconstruct i o n movers (10 t o 25 percent ) ;

- - Higher p ropo r t i ons o f cons t ruc t i on movers ( 5 t o 20 per - cen t ) l i v e i n o the r types o f temporary housing than noncons t ruc t i on movers ( l e s s than 10 percent) .

0 There are s i g n i f i c a n t reg iona l d i f f e rences i n t he type o f housing se lec ted by movers. S ing le f a m i l y houses and mob i le homes are more l i k e l y t o be chosen ( o v e r a l l and by a1 1 worker groups) i n t h e South than i n t he North. Correspondingly, apar t- ments and o the r types o f temporary housing are less l i k e l y t o be chosen ( o v e r a l l and by a l l worker groups) i n t h e South than i n t h e North. Overa l l p ropor t ions l i v i n g i n d i f f e r e n t types o f housing are:

- - S ing le f a m i l y houses North South

- - Mobi le homes North South

- - Apartments Nor th South - - Other types o f housing North South

35 t o 40 percent 40 t o 50 percent About 20 percent 35 t o 50 percent 25 t o 35 percent 10 t o 20 percent 10 t o 15 percent 0 t o 5 percent

0 Presence o r absence o f a f a m i l y i s r e l a t e d t o t h e type o f housing selected by movers. T y p i c a l l y , h i ghe r p ropo r t i ons o f movers w i t h f a m i l y present (45 t o 65 percent ) l i v e i n s i n g l e f a m i l y houses compared t o movers w i thou t f a m i l y present (10 t o 20 percent ) . Few movers w i t h f a m i l y present 1 i v e i n h o t e l s / motels, etc., bu t 10 t o 25 percent o f movers w i thout f a m i l y present l i v e i n such temporary quar te rs .

6. Demographic C h a r a c t e r i s t i c s o f Movers

The major f i n d i n g s o f our examination o f t he demographic charac ter-

i s t i c s o f movers are as fo l l ows :

Among cons t ruc t i on movers, t h e p r o p o r t i o n o f movers who are mar r ied i s h igher i n t h e South (85 percent ) than i n t h e Nor th (75 percent ) . No reg iona l d i f f e rence , however, was apparent among t h e nonconstruct ion group.

Average f a m i l y s i z e va r i ed across worker groups. The average f a m i l y s i z e o f cons t ruc t i on movers (3.4) was somewhat h ighe r than t h a t o f noncontruct ion movers (3.1).

Average number o f school-age c h i l d r e n a l s o v a r i e d across worker groups. The average number o f school-age c h i l d r e n was .85 among c o n s t r u c t i o n movers, compared w i t h o n l y .6 among noncons t ruc t i on movers.

e The median f a m i l y income o f a l l movers was approx imate ly $21,000 a year (1978 do1 l a r s ) , w i t h t he average among t h e nonconst ruc- t i o n ($21,700) group be ing h i ghe r than among t h e c o n s t r u c t i o n group ($20,500). S i m i l a r l y , t h e median f a m i l y income among t h e scarce movers ($21,000) was h i ghe r than t han among t h e common and abundant mover group ($19,300).

IMPL ICATIONS FOR FORECASTING

The r e s u l t s o f t h i s p r o f i l e a n a l y s i s have demonstrated t h a t t h e r e i s

a l a r g e v a r i a t i o n i n key v a r i a b l e s ( i .e . , m ig ran t p ropo r t i ons , r e l o c a t i o n

o f dependents, r e s i d e n t i a1 l o c a t i o n , t ype o f hous ing se lec ted ) across

s i t e s and surveys. The r e s u l t s o f t h e a n a l y s i s have a l s o shown system-

a t i c v a r i a t i o n i n these key v a r i a b l e s across worker groups. These d i f -

fe rences across va r i ous worker groups, however, a re n o t s u r p r i s i n g i n

l i g h t o f t h e d i f f e r e n c e s among worker groups w i t h r espec t t o t h e l o c a l

a v a i l a b i l i t y o f workers i n t h e area immediate ly su r round ing t h e cons t ruc-

t i o n s i t e , t h e degree o f s p e c i a l i z a t i o n r e q u i r e d i n t asks performed, and

t h e n a t u r e o f l a b o r requi rements ( p o t e n t i a l f o r employment) a t t h e s i t e .

Consider, f o r example, t h e observed d i f f e r e n c e s i n key v a r i a b l e s

among c o n s t r u c t i o n c r a f t s grouped by r e l a t i v e s c a r c i t y o f l abo r . The

lowes t m ig ran t p r o p o r t i o n s were observed among t he abundant c r a f t group

( l a b o r e r s and teamste rs ) . These c r a f t s do n o t r e q u i r e ex tens i ve p r i o r

t r a i n i n g and t h e i r s k i l l s are n o t s p e c i f i c t o any p a r t i c u l a r t y p e o f

c o n s t r u c t i o n p r o j e c t . As a r e s u l t , workers f rom these c r a f t s a re r e a d i l y

a v a i l a b l e l o c a l l y and, as such, can be e a s i l y r e c r u i t e d f r om t h e l o c a l

l a b o r poo l . There are, o f course, o t h e r more s p e c i a l i z e d c o n s t r u c t i o n

c r a f t s , such as those represen ted i n t h e scarce c r a f t group, and t h e

l o c a l l a b o r supp l y i s l ess l i k e l y t o be a b l e t o p r o v i d e a s u f f i c i e n t

number o f such workers. Therefore, i t i s n o t s u r p r i s i n g t o observe

g r e a t e r numbers o f movers among c r a f t s which a re r e l a t i v e l y scarce.

D i f f e r e n c e s i n o t h e r p r o f i l e va r i ab l es , such as i n t e n t i o n t o remain

i n t h e area, r e l o c a t i o n o f dependents, and t y p e o f hous ing se lec ted , a l s o

l i e i n d i f f e r e n c e s i n employment o p p o r t u n i t i e s f o r va r i ous worker

groups. The c o n s t r u c t i o n i n d u s t r y i s c h a r a c t e r i z e d by a h i g h l a b o r t u r n -

over. Employment f o r c o n s t r u c t i o n workers i s seldom permanent. Rather,

workers are hired fo r specif ic jobs of a limited duration. Especially

among workers from the scarce c r a f t group, i t i s often necessary fo r workers to move from s i t e t o s i t e or to commute ra ther long distances each day to maintain steady employment. Opportunities fo r continued employment a t the construction s i t e , as well as i n the area upon comple- t ion of the project , are fewer among the scarce c r a f t group. Not sur- pr is ingly , we did observe t ha t workers from the scarce c r a f t s are more l i ke ly t o leave the area e i t he r before or on completion of the project , are more l ike ly t o maintain a permanent residence elsewhere, a re less l i ke ly t o relocate t h e i r families, and are more l i ke ly t o l i v e in temporary housing near the construction s i t e . 6

Differences in the ava i l ab i l i t y of labor in the area and the nature of employment opportunities a t the construction s i t e are a lso important factors underlying the extremely d i f fe ren t migrant proportions of the management and c le r ica l groups. Management workers are generally more educated and t he i r jobs have r e l a t i ve ly high sa la r ies . These workers are not l i ke ly t o be readi ly available in the area, especia l ly in the case of

more rural s i t e s . Instead, many of these workers are regular employees of the u t i l i t y or prime contractor and are moved t o the area spec i f ica l ly t o work on the project . Clerical workers, on the other hand, have jobs t ha t require less education and t ra ining and, as a r e s u l t , most of them are hired locally.

Similarly, with respect t o other key variables, the behavior of non-

construction movers i s consistent with differences in the nature of employment opportunities. Since most nonconstruction movers consis t of management ra ther than c le r ica l workers, these workers typ ica l ly are employees of the u t i l i t y or the prime contractor and most l i ke ly will be transferred upon completion of the project. Furthermore, the long term employment potential f o r these workers in t h i s area (especia l ly a rural area) i s ra ther 1 imited. As a ref lect ion of these fac tors , we did observe t ha t most nonconstruction movers expect t o leave the area upon

6 ~ n t e r e s t i n g l y , workers from a1 1 worker groups who moved t o the area t o work a t the construction s i t e locate r e l a t i ve ly near the s i t e . Residen- t i a l location was the only variable in which we did not observe any systematic variat ion among various groups of movers.

complet ion of t h e p r o j e c t . However, d e s p i t e t h e temporary na tu re o f

t h e i r employment, most noncons t ruc t ion movers do r e l o c a t e t h e i r fami-

l i e s . A p o s s i b l e exp lana t i on f o r t h i s i s t h a t a l though t h e i r t enu re a t

t h e s i t e i s l i m i t e d , i t i s n o t n e c e s s a r i l y sho r t . Employment a t t h e s i t e

i s q u i t e s t a b l e and cou ld extend f o r a p e r i o d of up t o t e n years. I n

a d d i t i o n , t h e employment c o n t r a c t s o f management workers a re l i k e l y t o

cover t h e c o s t o f moving t h e i r f a m i l i e s . And, indeed, our a n a l y s i s d i d

show t h a t , compared w i t h c o n s t r u c t i o n movers, noncons t ruc t i on movers were

much more l i k e y t o r e l o c a t e t h e i r f a m i l i e s and t o l i v e i n more permanent,

s i n g l e f a m i l y housing.

The f i n d i n g s o f t h i s p r o f i l e a n a l y s i s have impor tan t i m p l i c a t i o n s f o r

t h e development o f f o r e c a s t i n g procedures. These i m p l i c a t i o n s inc lude :

( 1 ) t h e need t o conduct a m u l t i v a r i a t e ana lys is ; ( 2 ) t h e importance o f

workforce composi t ion i n e x p l a i n i n g t h e observed v a r i a t i o n across s i t e s

and surveys; ( 3 ) t h e i d e n t i f i c a t i o n o f exp lana to ry va r i ab les ; ( 4 ) j u s t i-

f i c a t i o n f o r adop t ing a c r a f t - s p e c i f i c approach t o model development; and

( 5 ) o t h e r cons idera t ions . Each o f these i m p l i c a t i o n s i s discussed i n

g r e a t e r d e t a i 1 below.

The Need t o Conduct a M u l t i v a r i a t e Ana l ys i s

Foremost, t h e r e s u l t s of t h i s p r o f i l e ana l ys i s i n d i c a t e d t h a t t h e r e i s a l a r g e v a r i a t i o n i n m ig ran t p ropo r t i ons and r e s i d e n t i a l l o c a t i o n

p a t t e r n s across s i t e s . Th i s suggests t h a t t h e p r a c t i c e o f making f o r e -

c a s t s a t one s i t e based s o l e l y upon t h e observed va lues a t another s i t e

( o r even t h e average across severa l s i t e s ) can be a dangerous p r a c t i c e .

I n add i t i on , our examinat ion c l e a r l y h i g h l i g h t s t h e need f o r a m u l t i -

v a r i a t e ana l ys i s t o improve our understanding o f t h e f a c t o r s u n d e r l y i n g

t h e v a r i a t i o n i n these v a r i a b l e s across s i t e s as a necessary f i r s t s t ep

i n t h e development o f improved f o r e c a s t i n g procedures.

Another r a t h e r i n t e r e s t i n g f i n d i n g i s t h e ve ry pronounced d i f f e r e n c e

w i t h r espec t t o key v a r i a b l e s which was observed between c o n s t r u c t i o n and

noncons t ruc t ion workers. I n most cases, however, t h i s v a r i a t i o n was seen

t o r e f l e c t bas i c d i f f e r e n c e s i n t h e na tu re o f employment o p p o r t u n i t i e s

between t h e two groups a t c o n s t r u c t i o n s i t e s . Th i s suggests t h a t t he

f a c t o r s u n d e r l y i n g such r e l o c a t i o n dec i s i ons a re n o t t h e same f o r these

two worker groups. The i m p l i c a t i o n o f t h i s f o r purposes o f model devel-

opment i s s imp l y t h a t a separate model should be developed f o r each

group. Combining these two very different groups in the same model is

likely to result in a reduction in the overall predictive power of the

model .

The Importance of Workforce Composition

The results of this analysis have clearly demonstrated a systematic

variation in migrant proportions across worker groups. This implies that

workforce composition could be a very important factor in explaining the

variation in overall migrant proportion across sites. Table 1 presents the proportion of the total workforce in each of ten craft groups at the

time of the survey for the 24 surveys for which information on craft was

available. As can be seen in the table, workforce composition varies

considerably from site to site and at the same site at different stages

of project completion. 7

Because migrant proportions vary considerably for different worker

groups and because workforce composition varies across sites, the vari-

ation in overall migrant proportions may, to a large extent, reflect

differences in workforce composition. Thus, any attempt to explain the

observed variation in migrant proportion across sites should explicitly

include a consideration of workforce composition at the site at the time

of the survey.

The Identification of Explanatory Variables

These findings were also useful in identifying several factors under-

lying the observed variation in migrant proportions across sites and across various worker groups, and therefore were useful in defining vari-

ables to be included in the multivariate portion of our analysis. In

particular the results of the analysis indicate that the availability of

labor in the area and the nature of labor requirements could be important factors in explaining the observed variation in these variables across

sites.

70perating engineers, for example, ranged from 2.7 percent of the total workforce at one site to 29.7 percent at another. Similarly, pipefitters varied from 5.1 to 25.8 percent of the total workforce.

TABLE 1

Workforce Composition a t Time of Survey by Craf t Groups

(Proportion of Total Workforce)

E 0 . l- C, 4 u cc

h.r L a- aJ > En f a V ) - Z

1.0

2.0

3.0

4.0

8.0

9.1

9.2

9.3

9.4

10.1

10.2

10.3

11.1

11.2

11.3

11.4

12.1

12.2

12.3

12.4

13.1

13.2

13.3

13.4

V) V) E V) V) L E 0 L L a Q V) a- C,

a~ Y mu, .F L C, E C, E L V aJ U V) 7 C, L .C C, = L Q e z : 0 L E L aJ V

ik' a G aJ Q C C, aJ LC, E L S F m

aJ c L 0 P a V) 0 L 4 P 0 OF Q) m Q) L C E a aJ E .F L 0 P E c Q C, 0 Q 7

n w m o w W 0 O U A U r"

5.9 14.0 4.3 6.6 5.1 15,3 1.8 20.6 10.8 15.6

18.8 11.9 2.9 8.4 6.6 16.1 3.5 18.9 3.5 9.5

18.0 17.6 4.3 6.7 5.6 13.4 8,6 16.8 4.1 4.8

16.9 15.5 3.7 3.7 13.2 13.2 12.1 14.9 3.7 3.1

22.3 2.4 2.4 2.7 11.5 7.3 9.2 16.7 9.4 16.0

6.2 7.1 .2 18.0 8.9 11.7 5.6 22.2 7.8 12.5

10.3 12.2 2.9 5.1 9.1 20.3 4.7 10-6 7.0 17.8

11.0 3.4 3.1 3.9 13.8 23.1 7.3 17.1 5.1 12.0

14.8 12.1 5.6 5.7 13.0 15.5 6.3 13.8 3.8 9.4

11,4 8.1 2.8 6.0 8.9 24.6 6.6 19.6 4,1 7,8

25.8 6.8 4.3 8.0 10.6 12.8 7.2 14.4 4.0 6.0

17.6 5.4 2.8 9.3 16.5 12.4 5.8 14.5 5.4 10.3

5.5 12.5 .O 18.8 3.6 20.2 3.9 18.8 5.4 11.4

9.2 13.2 3.5 7.8 9.3 15.5 6.4 25.6 3.1 6.5

8.5 2.0 2.3 11.3 17.4 18.7 3.3 15.6 5.6 15.4

24.4 1.9 .O 4.7 18.5 8.7 8.7 11.8 2.9 18.5

5.1 1.5 .O 18.9 3.1 7.7 8.4 35.5 8.4 11.5

9.2 10.9 .2 10.0 5.1 20.4 1.3 24.3 6.5 12.2

13.3 8.8 1.4 6,l 11.1 19.2 5.8 17.0 4.8 12.5

21.4 6.3 2.0 6.3 17.5 10.5 7.8 14.4 3.7 10.2

8.1 7.9 .6 29.7 3.8 7.7 8,2 15.4 5.2 13.4

7.8 6.4 .1 25.5 6.8 7.9 6.5 22.5 5.2 11.2

9.7 11.1 1.3 23.5 5.3 8.4 4.7 16.8 5.8 13.3

9.7 12.5 1.8 18.8 5.2 9.2 4.2 17.9 5,7 15,O

The availability of labor varies considerably across craft groups as

well as across sites, depending upon factors such as the urban/rural

nature of the surrounding area. If there are several large cities within

daily commuting distance of the site, one might not observe large numbers

of workers moving to the area to work at the site. This may be particu-

larly important among workers from the scarce crafts, whose availability

may be somewhat limited in rural areas. The attractiveness of employment

opportunities for various craft groups depends upon the nature of labor

requirements. This includes a variety of factors such as the total num-

ber of workers required, and the expected duration and continuity of

employment. There is considerable variation in these labor requirement

variables both across sites and across crafts. Since it is these vari-

ables which determine the expected value of benefits associated with

employment at a particular site, it is therefore likely that these vari-

ables will also influence workers' relocation decisions.

In addition, the large variation in migrant proportions across sites

and surveys for the same group of workers suggests that there are site

and project specific variables which might also be important in explain-

ing the observed variation across sites and surveys. Thus, this analysis

suggests that any model which is developed to explain the observed variation in migrant proportions should include variables which reflect various regional and project characteristics, as well as variables which

reflect the availability of labor in the area and the relative attrac-

tiveness of employment opportunities at the construction project. How-

ever, these factors typically have not been considered in empirical studies of this nature.

Justification for Adopting a Craft-Specific Unit of Analysis

A very important finding of this analysis is that one observes considerable variation in key variables among different worker groups. This

suggests that occupation may be an important dimension in examining these

issues. The importance of this finding is that it allows one to perform a multivariate analysis using craft-specific worker groups as the unit of

analysis.

Past studies of this nature have been limited by the availability of

data. Construction worker survey data are difficult to obtain and, as a

result, data are not available for a large number of sites. Indeed, past studies have often been limited to at most 14 sites. If the site is used

as the unit of analysis, the data do not provide a sufficient number of observations to conduct a multivariate analysis. However, the results of

our examination indicate that it is possible to identify 7 or 8 major craft groups, with sufficient numbers of workers in each craft group, to

examine variation with respect to each craft group at each site. Adopt- ing this approach provides a sufficient number of observations for a

multivariate analysis, thereby overcoming the data limitations which have

hindered past studies of a similar nature.

An additional advantage of using craft as the unit of analysis stems

from the fact that labor requirements are craft-specific. Thus, it will

be possible to consider the importance of a number of craft-specific

labor requirement variables such as income potential associated with

employment at the site, labor requirements for project construction,

local availability of labor and competing demand for labor for each craft

group, in addition to the importance of regional and project character-

istics, in explaining the observed variation across sites and crafts.

Other Considerations

Finally, examination of the data in early stages of the profile analysis allowed us to define more carefully the terms and definitions used

in subsequent analyses. An examination of past studies indicated that a confusion in terminology has stemmed from a failure to distinguish

between a change of residence and the impact area based on geographic

proximity to the site. 8

In our analyses we attempted to avoid this problem by classifying

workers independently according to 2 different criteria--the first based

on change of residence and the second based on geographical proximity to

8~his confusion stems from the fact that different terms have been used by different groups to refer to the same phenomenon; and, similarly, the same term has been used to refer to entirely different concepts. For example, some past studies have used the term nonlocal worker to refer to workers who moved into the area to work at the site. Others have used the same term to refer to those workers who commute from outside the local impact area.

the s i te . ' I n our r e s i d e n t i a l l o c a t i o n a n a l y s i s we d e f i n e d two impact

areas--a r e g i o n a l impact area and a l o c a l impact area. The l o c a l impact

area was d e f i n e d as t h e area w i t h i n 15 highway m i l e s o f t h e s i t e . The

r e g i o n a l impact area was de f i ned as t h e area w i t h i n a 50-mile r a d i u s o f

t he s i t e . These d e f i n i t i o n s were determined based upon our p r o f i l e ana l-

y s i s r e s u l t s . A s i m i l a r examinat ion o f t h e da ta a ided i n t h e d e f i n i t i o n

o f terms i n our examinat ion o f o t h e r key v a r i a b l e s . 10

The terms and d e f i n i t i o n s which we adopted were an impor tan t ou tpu t

o f our p r o f i l e ana l ys i s . By i d e n t i f y i n g sources o f con fus ion i n t e r m i -

no logy and by us i ng t he da ta t o suggest more p r e c i s e d e f i n i t i o n s o f

terms, we were a b l e t o concep tua l i ze subsequent analyses more c l e a r l y .

Furthermore, adop t ing p r e c i s e d e f i n i t i o n s o f terms commonly used i n

socioeconomic impact assessments i s c r i t i c a l t o ach iev ing a c o n s i s t e n t

s e t o f e m p i r i c a l r e s u l t s f o r purposes o f improv ing f o r e c a s t i n g procedures.

I n conc lus ion, our examinat ion o f seve ra l key v a r i a b l e s has i d e n t i -

f i e d cons iderab le v a r i a t i o n across s i t e s and across d i f f e r e n t worker

groups. These f i n d i n g s suggest t h e need f o r a m u l t i v a r i a t e a n a l y s i s t o

e x p l a i n t h e observed v a r i a t i o n across c r a f t s and s i t e s as a p o s s i b l e

means o f improv ing f o r e c a s t i n g procedures. Focusing upon t h e two most

impor tan t va r i ab l es- - m ig ran t p r o p o r t i o n s and r e s i d e n t i a l l oca t ion- - we

examined t h e observed v a r i a t i o n w i t h i n a m u l t i v a r i a t e a n a l y s i s frame-

work. The r e s u l t s o f t h i s a n a l y s i s a re presented i n t h e f o l l o w i n g

chapter . Resource l i m i t a t i o n s d i d n o t p e r m i t us t o conduct a m u l t i -

v a r i a t e a n a l y s i s o f t h e o t h e r v a r i a b l e s o f i n t e r e s t . However, t h e

91n our examinat i o n o f m ig ran t p r o p o r t i ons we c l a s s i f i e d worker as movers o r nonmovers based upon change o f res idence. We d e f i n e d movers t o be those workers who changed res idence t o work a t t h e c o n s t r u c t i o n s i t e . Workers who d i d n o t change res idence t o work a t t h e s i t e were t h e r e f o r e c l a s s i f i e d as nonmovers. I n our examinat ion o f r e s i d e n t i a l l o c a t i o n we c l a s s i f i e d workers as l o c a l o r non loca l workers based upon geographica l p r o x i m i t y t o t h e s i t e . We d e f i n e d l o c a l workers t o be those workers who l i v e d w i t h i n t h e l o c a l impact area ( i .e. , w i t h i n 15 highway m i l e s o f t h e s i t e ) . Workers who l i v e d o u t s i d e t h e l o c a l area were, o f course, c l a s s i - f i e d as non loca l workers.

loin our examinat ion o f i n t e n t i o n t o remain i n t h e area we c l a s s i f i e d movers and temporary movers, t r a n s i e n t movers, movers w i t h a permanent r es i dence elsewhere, and workweek movers.

differences in these key variables which we observed in our profile anal-

ysis were used to suggest procedures for making improved predictions of

intention to remain in the area, relocation of dependents, type of

housing and personal characteristics of movers.

CHAPTER 111

MULTIVARIATE ANALYSES

The m u l t i v a r i a t e analyses which a re descr ibed i n t h i s chap te r were

t h e key t o deve lop ing procedures f o r f o r e c a s t i n g m ig ran t p ropo r t i ons and

r e s i d e n t i a l l o c a t i o n p a t t e r n s o f movers a t nuc l ea r power p l a n t cons t ruc-

t i o n s i t e s . The need f o r such m u l t i v a r i a t e analyses was c l e a r l y demon-

s t r a t e d by t he l a r g e v a r i a t i o n i n these v a r i a b l e s across s i t e s and su r-

veys which we observed i n t he p r o f i l e a n a l y s i s p o r t i o n o f t h i s study.

The purpose o f t h e analyses was t o i d e n t i f y t h e determinants o f

workers 1 r e l o c a t i o n dec i s i ons and t o es t ima te t h e s i z e o f t h e e f f e c t o f

t h e va r i ous determinants . I n t h i s way i t i s p o s s i b l e t o use these

r e s u l t s t o develop procedures by which one can o b t a i n t h e r e l e v a n t i n f o r -

mat ion rega rd i ng these f a c t o r s a t a f u t u r e c o n s t r u c t i o n s i t e and p r e d i c t

t h e va lues o f v a r i a b l e s o f i n t e r e s t a t t h e proposed s i t e .

Th i s chapter p resen ts a summary o f t h e m u l t i v a r i a t e analyses pe r-

formed i n t h i s s tudy. The chap te r i s d i v i d e d i n t o 2 sec t ions . The f i r s t

s e c t i o n p resen ts a b r i e f d i s cuss ion o f our m ig ran t p r o p o r t i o n a n a l y s i s

and t he second s e c t i o n p resen ts a b r i e f d i s cuss ion o f ou r r e s i d e n t i a l

l o c a t i o n ana l ys i s . A more complete d i scuss ion o f t h e t h e o r e t i c a l j u s t i -

f i c a t i o n f o r t h e models, t h e t e c h n i c a l d e t a i l s o f t h e e m p i r i c a l s p e c i f i -

c a t i o n and es t ima t i on , and a more d e t a i l e d d i scuss ion o f r e s u l t s o f t h e

m ig ran t p r o p o r t i o n and r e s i d e n t i a l l o c a t i o n analyses a re presented i n

Appendices C and D, r e s p e c t i v e l y .

MIGRANT PROPORTION

The purpose o f t h i s a n a l y s i s was t o i d e n t i f y t h e f a c t o r s t h a t i n f l u -

ence t h e m ig ran t p r o p o r t i o n s o f workers a t n u c l e a r power p l a n t cons t ruc-

t i o n s i t e s , t o d e f i n e v a r i a b l e s t o measure these f a c t o r s , and t o i s o l a t e

f rom among these v a r i a b l e s those which b e s t e x p l a i n t h e observed v a r i a -

t i o n i n m ig ran t p r o p o r t i o n s across d i f f e r e n t s i t e s . These f i n d i n g s were

then used t o develop methods f o r f o r e c a s t i n g m ig ran t p r o p o r t i o n s a t

f u t u r e nuc lear power p l a n t c o n s t r u c t i o n p r o j e c t s . Indeed, i n many

respec ts t h e e m p i r i c a l s p e c i f i c a t i o n was d i c t a t e d by t h e f o r e c a s t i n g

procedures.

Mode 1

M ig ran t p r o p o r t i o n was d e f i n e d t o be t h e r a t i o o f t h e number o f

movers t o t h e t o t a l number o f workers a t t h e s i t e . Workers were c l a s s i -

f i e d as movers i f t h e y had changed t h e i r work week res idence t o work a t

t h e c o n s t r u c t i o n s i t e . The u n i t o f a n a l y s i s f o r t h e purpose o f es t ima-

t i n g these equa t ions was workers grouped by c r a f t .

Based upon t heo ry and t h e r e s u l t s o f ou r p r o f i l e a n a l y s i s we spec i -

f i e d m ig ran t p r o p o r t i o n s as a f u n c t i o n o f severa l f a c t o r s . These f a c t o r s

can be expressed as a f u n c t i o n a l r e l a t i o n s h i p o f t h e f o l l o w i n g form:

( 1 ) MPROP = f (INCPOT, LABRQ, COMPDMD, LBAVAIL, RGCHAR,

CONTVAR )

where ;

MPROP = M ig ran t p r o p o r t i o n o f a p a r t i c u l a r c r a f t a t a s i t e ;

INCPOT = A vec to r o f v a r i a b l e s r e f l e c t i n g t h e income p o t e n t i a l assoc ia ted w i t h employment a t t h e s i t e ;

LABRQ = A vec to r o f v a r i a b l e s r e f l e c t i n g l a b o r requi rements a t t he s i t e ;

COMPDMD = A vec to r o f v a r i a b l e s r e f l e c t i n g competing demand f o r l a b o r i n reg ion;

LBAVAIL = A vec to r o f v a r i a b l e s r e f l e c t i n g l o c a l a v a i l a b i l i t y o f l a b o r i n reg ion ;

RGCHAR = A vec to r o f r e g i o n a l c h a r a c t e r i s t i c va r i ab l es ; and

CONTVAR = A vec to r o f c o n t r o l va r i ab l es .

Severa l v a r i a b l e s were d e f i n e d t o cap tu re t h e i n f l u e n c e o f t h e ex-

p l a n a t o r y f a c t o r s shown i n t h e above equat ion. The income p o t e n t i a l

v a r i a b l e s which we d e f i n e d i nc l uded v a r i a b l e s such as h o u r l y wage r a t e ,

over t ime r a t e , f r i n g e b e n e f i t s rece ived, and a v a i l a b i l i t y o f t r a v e l

al lowances. I n a d d i t i o n , we developed severa l v a r i a b l e s i n an e f f o r t t o

cap tu re d i f f e r e n c e s i n l a b o r requi rement p r o f i l e s among d i f f e r e n t c r a f t s

a t each s i t e . These v a r i a b l e s were d e f i n e d t o cap tu re t h e expected

a v a i l a - b i l i t y o f employment a t t h e s i t e over t h e e n t i r e c o n s t r u c t i o n

phase ( i .e. , t h e expected c o n t i n u i t y and d u r a t i o n o f employment), as w e l l

as t o cap tu re d i f f e r e n c e s i n o v e r a l l and peak work fo rce requi rements and

d i f fe rences i n l a b o r requi rements a t t h e t i m e o f t h e survey.

The v a r i a b l e s which were de f i ned t o cap tu re t he concur ren t demand f o r

l abo r i n t h e r e g i o n were based upon c r a f t - s p e c i f i c l a b o r requi rements of

o the r power p l a n t c o n s t r u c t i o n p r o j e c t s w i t h i n d is tances o f 50 and 120

m i l e s o f each c o n s t r u c t i o n s i t e . Va r i ab les which captured t h e change i n

t h e demand f o r l abo r over t h e c o n s t r u c t i o n phase were a l s o examined.

Va r i ab les r e f l e c t i n g t h e l o c a l a v a i l a b i l i t y o f l abo r were much more d i f -

f i c u l t t o ob ta in . Several p rox ies were used t o cap tu re t he v a r i a t i o n i n

t h e l o c a l a v a i l a b i l i t y o f labor . These v a r i a b l e s inc luded r e g i o n a l popu-

l a t i o n , r e g i o n a l unemployment r a t e , and d i s tance f rom t h e s i t e t o t h e

h i r i n g h a l l o f t h e un ion l o c a l w i t h j u r i s d i c t i o n over t he p r o j e c t .

Several r e g i o n a l c h a r a c t e r i s t i c v a r i a b l e s were de f i ned i n an e f f o r t

t o determine t h e r e l a t i v e a t t r a c t i v e n e s s o f t h e area t o i n m i g r a t i n g

workers. Populat ion, average community s i z e and housing a v a i l a b i l i t y

v a r i a b l e s were inc luded among these r e g i o n a l c h a r a c t e r i s t i c v a r i a b l e s .

Several c o n t r o l v a r i a b l e s i n c l u d i n g s i z e and t ype o f r e a c t o r , and dummy

v a r i a b l e s f o r va r i ous worker groups were a l s o inc luded i n t h e es t imated

equat ions. A more d e t a i l e d d iscuss ion o f t h e va r i ab les , i n c l u d i n g t h e i r

d e f i n i t i o n s and expected i n f l u e n c e on m ig ran t p ropor t ions , can be found

i n t h e more t e c h n i c a l d e s c r i p t i o n o f t h e a n a l y s i s conta ined i n Appendix C.

Empi r i ca l S p e c i f i c a t i o n

For t h e purpose o f e x p l a i n i n g t h e v a r i a t i o n i n m ig ran t p ropo r t i ons

across surveys f o r va r ious c r a f t groups, o r d i n a r y l e a s t squares regres-

s i o n was used t o es t imate an equat ion o f t h e f o l l o w i n g form:

( 2 ) Ln MPRoP = a1 + a2 Ln INCPOT + a3 Ln LABRQ 1-MPROP

+ a4 Ln COMPDMD + a5 Ln LBAVAIL

+ a6 Ln RGCHAR + a7 Ln CONTVAR + E

where t he terms a re t h e same as i n equa t ion ( I ) , except:

as = c o e f f i c i e n t s o f v a r i a b l e s inc luded i n t h e equat ion;

E = t h e e r r o r term; and

Ln = t h e n a t u r a l l o g a r i t h m i c t rans fo rmat ion .

Two spec ia l f e a t u r e s o f t h e 1 i nea r r e l a t i o n s h i p shown i n equa t ion ( 2 )

should be noted. F i r s t , a l o g i t t r ans fo rma t i on was used because t he

va lues o f t he dependent va r i ab les , be ing p ropo r t i ons , a re cons t ra i ned

between 0 and 1. This t rans format ion has the e f f e c t o f ensur ing t h a t the

pred ic ted migrant p ropo r t i on values w i l l n o t f a l l ou ts ide the range o f

zero t o one. Second, a l oga r i t hm ic t rans format ion o f t he explanatory

var iab les was used t o capture the non- l inear r e l a t i o n s h i p between the

var iab les and migrant propor t ions.

Because of major d i f f e rences between cons t ruc t i on and nonconstruct ion

workers, as w e l l as the va r iab les t h a t are l i k e l y t o i n f l uence t h e i r

migrant p ropor t ions a t a s i t e , two separate equations were s p e c i f i e d and

estimated. The cons t ruc t i on worker equat ion was est imated us ing the

f o l l o w i n g 7 cons t ruc t i on c r a f t groups as u n i t s o f analys is : (1 ) plumbers

and p i p e f i t t e r s ; ( 2 ) i ronworkers; ( 3 ) boi lermakers; ( 4 ) opera t ing engi-

neers; ( 5 ) e l e c t r i c i a n s ; ( 6 ) carpenters; and ( 7 ) 1 aborers and teamsters.

The nonconstruct ion worker equat ion was est imated us ing the f o l l o w i n g two

occupational groups as u n i t s o f ana lys is : (1) management workers and ( 2 )

c l e r i c a l workers. I n many instances, the s p e c i f i c va r i ab les inc luded i n

t h e nor~const ruc t ion worker equat ion d i f f e r e d from those inc luded i n the

cons t ruc t i on worker equation. This was d i c t a t e d by the d i f f e rences i n

t he na ture o f cons t ruc t i on and nonconstruct ion employment, labor requ i re-

ments a t the s i t e and the a v a i l a b i l i t y o f data on nonconstruct ion workers.

Several a l t e r n a t i v e s p e c i f i c a t i o n s us ing d i f f e r e n t sets o f explana-

t o r y va r iab les were examined t o i d e n t i f y t he va r iab les t o be inc luded i n

the f i n a l equat ions which are presented i n t h i s repo r t . I n general, a l l

va r i ab les w i t h s t rong t h e o r e t i c a l j u s t i f i c a t i o n were inc luded i n the

equat ion. Var iables w i t h i n s i g n i f i c a n t explanatory power were excluded

from the equation. I n t he case o f h i g h l y co r re la ted var iab les , t he v a r i -

able w i t h the h igher explanatory power was included i n the f i n a l s p e c i f i -

c a t ion.

This s e l e c t i o n procedure r e s u l t e d i n the i n c l u s i o n o f 18 va r iab les i n

the cons t ruc t i on worker equat ion and 5 va r iab les i n t he nonconstruct ion

worker equation. The r e s u l t s o f these 2 migrant p ropo r t i on equat ions are

discussed i n the f o l l o w i n g sect ion.

Resul t s

The r e s u l t s o f t he f i n a l s p e c i f i c a t i o n o f the cons t ruc t ion and non-

const ruc t ion worker equat ions are presented i n Tables 2 and 3. Both

equations performed remarkably we l l , exp la in ing 71 and 87 percent o f t he

TABLE 2

M ig ran t P ropo r t i on Regression Resu l ts Cons t ruc t i on

Dependent v a r i a b l e L,, MPROP 1 -MPROP

Mean -1 .43

V a r i a b l e C o e f f i c i e n t t

Income Po ten t i a1

Wage

Overtime

Labor Requirements

C o n t i n u i t y o f Employment

Du ra t i on o f Employment

Du ra t i on o f Employment 1 1 ~

Dura t i on o f Employment 1 1 1 ~

Prepeak Stage

Postpeak Stage

Competing Demand f o r Labor

Employment a t o t h e r power p l a n t s i n t h e r e g i o n

Local A v a i l a b i l i t y o f Labor

D is tance f rom t h e un ion l o c a l

Regional C h a r a c t e r i s t i c s

Regional Popu la t i on

Regional Popu la t i on Growth

Average Community S i ze - 25 mi l e s

Average Community S ize - 10 m i l es

Housing Vacancy Rate

Cont ro l Va r i ab les

Common ( Dumny Va r i ab le )

Scarce (Dumy Va r iab le )

S i ze o f U n i t s

Constant

a ~ h r e e d u r a t i o n o f employment v a r i a b l e s were de f i ned t o es t ima te t h e e f f e c t o f t h i s v a r i a b l e sepa ra te l y f o r workers f rom t h e 3 s c a r c i t y groups.

TABLE 3

Migrant Propor t i on Regression Results Nonconstructi on

Dependent v a r i able Ln MPROP 1 -MPROP

Mean - -26

Variable Coe f f i c i en t 1:


Other nuclear power p lan ts under cons t ruc t i on

Local Avai 1 abi 1 i t y o f Labor

Regional Unemployment Rate

Regional Character i s t i cs

Regional Populat ion

Control Var iables

Occupation (Dummy Var iab le)

Size o f Un i ts

Constant

v a r i a t i o n i n m ig ran t p ropo r t i ons among t h e c o n s t r u c t i o n and nonconstruc-

t i o n groups. Va r i ab le c o e f f i c i e n t es t imates were g e n e r a l l y found t o be

s t a t i s t i c a l l y s i g n i f i c a n t and were o f t h e expected s ign. The es t imated

c o e f f i c i e n t s were a l so found t o be robus t . The s i g n and s i g n i f i c a n c e o f

key v a r i a b l e s were n o t s e n s i t i v e t o t he i n c l u s i o n and exc lus ion o f o t h e r

v a r i a b l e s i n t h e equat ion. Indeed, t h e h i g h exp lana to ry power o f t h e

es t imated equat ions as w e l l as t h e cons is tency o f r e s u l t s , serve t o jus-

t i f y us ing these m u l t i v a r i a t e a n a l y s i s r e s u l t s t o develop procedures f o r

f o r e c a s t i n g m ig ran t p ropo r t i ons a t f u t u r e nuc lear power p l a n t const ruc-

t i o n s i t e s .

1. Cons t ruc t ion Worker Equat ion

As can be seen i n Table 2, a t o t a l o f 18 v a r i a b l e s were inc luded i n

t h e f i n a l s p e c i f i c a t i o n o f t he c o n s t r u c t i o n worker equat ion. O f these 18

va r i ab les , 16 were s t a t i s t i c a l l y s i g n i f i c a n t a t o r above t h e 90 percen t

conf idence l e v e l , and t oge the r t h e 18 v a r i a b l e s exp la ined about 7 1 per-

cen t o f t h e v a r i a t i o n i n m ig ran t p ropo r t i ons . Var iab les rep resen t i ng

each o f t h e exp lana to ry f a c t o r s i d e n t i f i e d i n equa t ion ( 1 ) were i nc l uded

i n t h e f i n a l s p e c i f i c a t i o n . Those v a r i a b l e s which were de f ined t o cap-

t u r e r e g i o n a l c h a r a c t e r i s t i c s and l a b o r requi rements were found t o be t h e

most impor tan t i n e x p l a i n i n g t h e d i f f e r e n c e s i n c r a f t - s p e c i f i c m ig ran t

p ropo r t i ons across surveys. With t h e excep t ion o f t h e d u r a t i o n o f em-

ployment va r i ab les , a l l v a r i a b l e s were o f t h e expected s ign. The v a r i -

ables inc luded i n f i n a l equa t ion and t h e i r c o e f f i c i e n t es t imates a re

b r i e f l y discussed below.

Income P o t e n t i a l . For c o n s t r u c t i o n workers, t h e income p o t e n t i a l

assoc ia ted w i t h employment a t t h e c o n s t r u c t i o n s i t e i s determined n o t

o n l y by t h e i r wage r a t e , b u t a l s o by f a c t o r s such as over t ime r a t e ,

f r i n g e b e n e f i t s rece ived , and t h e a v a i l a b i l i t y o f t r a v e l al lowances. I n

add i t i on , because o f t h e na tu re o f c o n s t r u c t i o n employment ( i .e., t h e

i r r e g u l a r i t y of employment), a number o f o t h e r f a c t o r s can a l s o i n f l u e n c e

income p o t e n t i a l f o r c o n s t r u c t i o n workers. These i nc l ude f a c t o r s such as

t h e expected c o n t i n u i t y and d u r a t i o n o f employment. These va r i ab les ,

however, r e f l e c t d i f f e r e n c e s i n l abo r requi rements assoc ia ted w i t h p r o j -

e c t c o n s t r u c t i o n and a re inc luded as p a r t o f our d iscuss ion o f l a b o r

requi rement va r i ab les .

Among the four va r i ab les def ined t o capture the v a r i a t i o n i n income

p o t e n t i a l across s i t e s and surveys, wage r a t e and overt ime r a t e were

found t o be important i n exp la in ing migrant propor t ions. Both had the

expected p o s i t i v e s ign and were s i g n i f i c a n t , w i t h the overt ime r a t e v a r i -

able showing a h igher explanatory power than the wage r a t e va r iab le .

This supports t he b e l i e f t h a t overt ime i s a key component o f h igh income

among cons t ruc t i on workers, and as a r e s u l t serves as an important f a c t o r

i n a t t r a c t i n g labor from o ther a c t i v i t i e s and areas.

Labor Requirements. With respect t o labor requirements, 3 f a c t o r s

were i d e n t i f i e d as important i n es t ima t ing migrant p ropo r t i on d i f f e r -

e n t i a l s across c r a f t s and s i t e s . These 3 f a c t o r s inc lude t h e expected

growth o f employment oppor tun i t i es a t t he t ime o f the survey, t he

expected c o n t i n u i t y o f employment and the expected du ra t i on o f employment

a t t he s i t e .

With respect t o t he expected growth o f employment o p p o r t u n i t i e s a t

t he t ime o f t he survey, two va r iab les were def ined t o capture whether

employment o p p o r t u n i t i e s a t t he cons t ruc t i on s i t e f o r a p a r t i c u l a r c r a f t

group were a t a prepeak stage (demand f o r labor was expected t o increase)

o r a t a postpeak stage (demand f o r labor was expected t o decrease). The

est imated c o e f f i c i e n t s o f the two va r iab les i n d i c a t e t h a t the greater t he

expected increase i n u t i l i z a t i o n o f labor f o r a p a r t i c u l a r c r a f t , t he

h igher the migrant p ropor t ion ; and, s i m i l a r l y the greater the expected

decrease i n u t i l i z a t i o n o f labor f o r a p a r t i c u l a r c r a f t , t h e lower the

migrant p ropor t ion . This evidence supports t he n o t i o n t h a t migrant pro-

p o r t i o n s increase du r ing increas ing employment per iods (prepeak stage)

and decrease dur ing decreasing employment per iods (postpeak stage).

The p o t e n t i a l f o r g rea ter c o n t i n u i t y o f employment increases the

income a cons t ruc t i on worker might expect t o rece ive a t a nuclear power

p l a n t cons t ruc t i on s i t e . This no t i on was confirmed by the h i g h l y s i g n i f -

i c a n t and p o s i t i v e s ign o f the c o e f f i c i e n t est imate o f the c o n t i n u i t y

va r i ab le . I n o ther words, c r a f t s w i t h g reater c o n t i n u i t y o f employment

were associated w i t h h igher migrant propor t ions. However, a s i m i l a r

assoc ia t ion between p ro jec ted du ra t i on o f employment (du ra t i on o f employ-

ment a lso se rv ing t o increase p o t e n t i a l income associated wi,th t he move)

and migrant p ropor t ions was not found t o e x i s t .

I n f a c t , t he dura t ion v a r i a b l e c o e f f i c i e n t est imate no t o n l y was o f

opposi te sign, b u t was a l so s i g n i f i c a n t . This would suggest t h a t t he re

are fac to rs , o ther than income p o t e n t i a l , which are r e l a t e d t o the dura-

t i o n v a r i a b l e and are no t separa te ly considered i n the est imated equa-

t i o n . These f a c t o r s in f luence migrant p ropor t ions i n the opposi te d i rec-

t i o n . And, t he i n f l uence o f these f a c t o r s i s l a r g e r than the expected

e f f e c t o f t he income p o t e n t i a l associated w i t h the du ra t i on var iab le .

One such f a c t o r might be the r e l a t i o n s h i p between du ra t i on o f employ-

ment f o r p a r t i c u l a r c r a f t s and the r e l a t i v e a v a i l a b i l i t y o f these workers

i n the area i n which the s i t e i s located. Accordingly, we attempted t o

est imate the e f f e c t o f t he dura t ion va r iab le on migrant p ropor t ions sepa-

r a t e l y f o r the scarce, common, and abundant c r a f t groups. I n s p i t e o f

t h i s , we were unable t o ob ta in the expected assoc ia t ion f o r any o f t he

c r a f t groups. However, we d i d observe t h a t the e f f e c t o f expected dura-

t i o n of employment upon migrant p ropor t ions was smal l e r among workers

from the common c r a f t s than among workers from the o ther cons t ruc t ion

c r a f t groups.

Competing Demand f o r Labor. The competing demand f o r workers from

var ious c r a f t s a t o the r power p l a n t cons t ruc t ion p r o j e c t s i n the reg ion

was found t o be r e l a t e d t o migrant propor t ions. The competing demand

c o e f f i c i e n t est imate was found t o be h i g h l y s i g n i f i c a n t and p o s i t i v e .

The competing demand v a r i a b l e which was based upon a 50-mile rad ius sur-

rounding the cons t ruc t i on s i t e entered the equation; however, t he s i m i l a r

va r i ab le based upon on 120-mile rad ius d i d no t prove t o be usefu l i n

exp la in ing the d i f f e rences i n migrant p ropor t ions across c r a f t s . Th is

evidence suggests t h a t power p l a n t cons t ruc t ion p r o j e c t s w i t h i n commuting

d is tance o f the nuclear power p l a n t draw workers from the same labor

pool. However, i n the case o f more d i s t a n t power p l a n t cons t ruc t ion

pro jec ts , the impact o f t h i s f a c t o r on migrant p ropo r t i on i s i n s i g n i f i -

cant. Furthermore, change i n competing demand f o r labor between the year

cons t ruc t i on began on the p r o j e c t and the year i n which the survey was

conducted d i d n o t en ter the f i n a l equat ion.

Local A v a i l a b i l i t y o f Labor. The lack o f data regarding the s i z e of

t h e ava i l ab le labor supply and unemployment r a t e s o f cons t ruc t i on workers

i n the regions i n quest ion l e d us t o de f i ne several proxy va r iab les t o

capture the v a r i a t i o n i n the l o c a l a v a i l a b i l i t y o f labor . However

severa l o f these va r i ab les , such as r e g i o n a l p o p u l a t i o n and average com-

mun i t y s ize , cou ld serve as p rox ies f o r bo th r e g i o n a l a t t r a c t i v e n e s s and

t h e l o c a l a v a i l a b i l i t y o f labor . The supp ly o f l abo r i m p l i c a t i o n s o f

these v a r i a b l e s a re inc luded i n our d i scuss ion o f t h e r e g i o n a l charac te r-

i s t i c v a r i a b l e s .

Du r i ng our p r o f i l e ana lys is , we had observed a r e l a t i o n s h i p between

c r a f t - s p e c i f i c m ig ran t p ropo r t i ons a t a s i t e and t h e d i s t a n c e between t h e

s i t e and t h e h i r i n g h a l l o f t h e un ion l o c a l w i t h j u r i s d i c t i o n over t he

p r o j e c t . Because workers must r e p o r t t o un ion h i r i n g h a l l s f o r j o b

r e f e r r a l , i t can be argued t h a t un ion h i r i n g h a l l s a re l i k e l y t o be

l o c a t e d near c o n s t r u c t i o n employment o p p o r t u n i t i e s and a l s o t h a t workers

a re more l i k e l y t o l i v e near t h e i r h i r i n g h a l l s . Thus, f o r t h e purpose

o f t h i s a n a l y s i s we used d i s tance f rom t h e s i t e t o t h e h i r i n g h a l l o f t h e

un ion l o c a l w i t h j u r i s d i c t i o n over t h e p r o j e c t as a p roxy f o r t h e l o c a l

a v a i l a b i l i t y o f labor . As expected, t h e c o e f f i c i e n t es t ima te was found

t o be p o s i t i v e and s i g n i f i c a n t . S ince t h e f u r t h e r a c o n s t r u c t i o n s i t e i s

l oca ted f rom t h e un ion h i r i n g h a l l o f a p a r t i c u l a r c r a f t t h e lower t h e

l o c a l a v a i l a b i l i t y o f l abo r , one would expect t o observe h i g h e r m ig ran t

p r o p o r t i o n among t h e c r a f t groups which have h i r i n g h a l l s a t g r e a t e r

d i s t a n c e f r om t h e c o n s t r u c t i o n s i t e .

Regional C h a r a c t e r i s t i c s . Regional c h a r a c t e r i s t i c s were i n t r oduced

as measures o f t h e a t t r a c t i v e n e s s o f t h e reg ion . However, as ment ioned

above, some o f these v a r i a b l e s cou ld a l s o be cons idered t o be p r o x i e s of

t h e l o c a l a v a i l a b i l i t y o f labor . S ince oppos i te s igns a r e i m p l i e d by

these two f a c t o r s and t h e r e i s no a p r i o r i reason t o argue which e f f e c t

would be dominant, t h e s i g n o f these v a r i a b l e s cou ld be e i t h e r p o s i t i v e

o r nega t i ve . I f t h e e f f e c t due t o l a b o r supply was l a r g e r than t h e

e f f e c t due t o r e g i o n a l a t t r a c t i v e n e s s , then one would expect t o observe a

nega t i ve a s s o c i a t i o n between these v a r i a b l e s and m ig ran t p ropo r t i ons .

Among t h e 3 r e g i o n a l c h a r a c t e r i s t i c v a r i a b l e s which cou ld serve as

p roxy v a r i a b l e s f o r bo th r e g i o n a l a t t r a c t i v e n e s s and t h e l o c a l a v a i l -

a b i l i t y o f labor- - reg iona l popu la t ion , and average community s i zes w i t h i n

10 and 25 m i l e s o f t h e s i t e- - on l y t h e average community s i z e w i t h i n 25

m i l e s o f t h e s i t e was found t o be n e g a t i v e l y assoc ia ted w i t h m i g r a n t

p ropo r t i on . A s i m i l a r nega t i ve assoc ia t i on was n o t found i n t h e case o f

average community s i z e w i t h i n 10 m i l e s o f t h e s i t e . The oppos i t e s igns

o f these c o e f f i c i e n t s cou ld be i n t e r p r e t e d as suggest ing t h a t average

community s i z e v e r y near t h e s i t e ( w i t h i n 10 m i l e s ) serves more as a

proxy f o r a t t r a c t i v e n e s s because t h e 1 a rges t o f these communities are

i n v a r i a b l y t o o smal l t o p rov ide a s i g n i f i c a n t pool o f c o n s t r u c t i o n

workers. Such i s , o f course, n o t t h e case when one cons iders communities

l oca ted w i t h i n 25 m i l e s o f t h e s i t e . The a t t r a c t i v e n e s s e f f e c t i s c l ea r-

l y dominant i n t h e case o f r e g i o n a l popu la t ion .

The c o e f f i c i e n t es t imates o f t h e two remain ing r e g i o n a l v a r i a b l e s

(hous ing vacancy r a t e and popu la t i on growth) were a l s o found t o be h i g h l y

s i g n i f i c a n t . Housing vacancy r a t e was found t o be t h e most impor tan t

v a r i a b l e i n e x p l a i n i n g t h e m ig ran t p ropo r t i ons across s i t e s . Higher

vacancy r a t e s were assoc ia ted w i t h h i ghe r m ig ran t p ropo r t i ons . Popula-

t i o n growth was found t o be n e g a t i v e l y assoc ia ted w i t h m ig ran t propor-

t i o n s . Th i s r e s u l t appears t o suggest t h a t popu la t i on growth may be

regarded by movers as a nega t i ve q u a l i t y o f a r eg ion . Th i s i s n o t unrea-

sonable, s i nce r a p i d popu la t i on growth can be assoc ia ted w i t h shor tage o f

hous ing and var ious serv ices , which may be impor tan t elements i n t h e

d e c i s i o n process o f i n m i g r a t i n g workers.

Cont ro l Var iab les . Three v a r i a b l e s i n t h i s ca tegory were inc luded i n

t h e f i n a l equat ion. Two were dummy v a r i a b l e s t o cap tu re t he remain ing

mean d i f f e r e n c e s among workers f rom t h e t h r e e s c a r c i t y groups. Only t h e

dummy v a r i a b l e f o r workers f rom common c r a f t was found t o be s t a t i s t i -

c a l l y s i g n i f i c a n t . Th i s suggests t h a t h o l d i n g o t h e r v a r i a b l e s constant,

on average, workers f rom t h e common c r a f t group have lower m ig ran t pro-

p o r t i o n s than workers f rom t h e o t h e r c r a f t groups. The f i n a l c o n t r o l

v a r i a b l e which we inc luded was a v a r i a b l e which r e f l e c t s t h e s i z e ( i n

megawatts) of t h e u n i t s under cons t ruc t i on . The p o s i t i v e and h i g h l y

s i g n i f i c a n t c o e f f i c i e n t es t ima te i n d i c a t e s t h a t l a r g e r p l an t s , on aver-

age, have h ighe r m ig ran t p ropo r t i ons assoc ia ted w i t h c o n s t r u c t i o n than

one migh t have expected.

2. Nonconst ruct ion Worker Equat ion

I n t he case o f t h e noncons t ruc t ion worker equa t ion t h e f i n a l s p e c i f i -

c a t i o n was much s imp le r . As can be seen i n Table 3, o n l y 5 var iab le ;

were inc luded i n t h e f i n a l s p e c i f i c a t i o n . A s i n g l e dummy v a r i a b l e which

was de f i ned t o cap tu re t h e average d i f f e r e n c e s between management and

c l e r i c a l workers was found t o exp la in almost 75 percent o f t he v a r i a t i o n

i n the dependent va r i ab le . However, f o u r o ther var iables- - regional popu-

l a t i o n , reg iona l unemployment ra te , number of o ther nuclear power p l a n t s

under cons t ruc t i on i n t he region, and p l a n t size--also entered the f i n a l

equation. These va r iab les helped t o exp la in o n l y an add i t i ona l 1 2 per-

cent o f t he v a r i a t i o n i n migrant p ropor t ions among nonconstruct ion

workers. A l l f o u r va r i ab les were s i g n i f i c a n t a t o r above the 95 percent

conf idence l e v e l .

The s p e c i f i c va r i ab les which were inc luded i n the nonconstruct ion

worker equat ion d i f f e r e d t o a l a r g e ex ten t from those which were inc luded

i n the cons t ruc t i on worker equation. This, however, i s no t s u r p r i s i n g

when one considers the d i f f e rences i n t he na ture o f employment f o r con-

s t r u c t i o n and nonconstruct ion workers. For example, among nonconstruc-

t i o n workers, migrant p ropor t ions observed a t a s i t e are l e s s l i k e l y t o

be associated w i t h income p o t e n t i a l and much more l i k e l y t o be in f luenced

by the personnel p o l i c i e s o f u t i l i t i e s and engineer ing f i rms. Espec ia l l y

among the management group, a l a rge number o f workers are l i k e l y t o be

brought i n by the u t i l i t y o r prime con t rac to r t o work on the p r o j e c t w i t h

o n l y a small number being h i r e d l o c a l l y . Moreover, t he nonconstruct ion

group i s a very heterogeneous group and, as a r e s u l t , no t y p i c a l income

values could be obtained f o r c l e r i c a l and management groups. Thus,

r e f l e c t i n g both the lack o f adequate data and the importance of personnel

p o l i c i e s i n i n f l u e n c i n g migrant propor t ions, no income p o t e n t i a l v a r i -

ables were inc luded i n es t ima t ing the nonconstruct ion equation.

The s i n g l e most important v a r i a b l e i n t he nonconstruct ion worker

equat ion was the management-clerical dumny. This imp l i es t h a t t h e var ia-

t i o n i n migrant p ropor t ions among nonconstruct ion workers i s most ly due

t o d i f f e rences i n migrant p ropor t ions o f the management and c l e r i c a l

groups. Indeed, as we observed i n our p r o f i l e analys is , t he management

workers had very h igh migrant p ropor t ions and the c l e r i c a l workers very

low migrant propor t ions.

The c o e f f i c i e n t est imates o f t he o v e r a l l unemployment r a t e i n the

reg ion and the reg iona l popu la t ion were both found t o be negat ive and

h i g h l y s i g n i f i c a n t . The unemployment r a t e v a r i a b l e can be i n t e r p r e t e d t o

mean t h a t i f the re i s a h igher a v a i l a b i l i t y o f labor i n t he area, one

woul d expect t o observe lower migrant propor t ions. The reg iona l popul a-

t i o n var iab le , on the o ther hand, could r e f l e c t the general a t t r a c t i v e-

ness o f t he area t o i nm ig ra t i ng workers or could r e f l e c t the s i z e o f the

pool o f l o c a l labor . The observed negat ive c o e f f i c i e n t est imate suggests

t h a t w i t h increas ing reg iona l populat ion, the e f f e c t o f t he associated

l a r g e r number o f l o c a l l y a v a i l a b l e workers i s greater than the e f f e c t o f

t he associated increased a t t rac t i veness o f the area.

The number o f o ther nuclear power p lan ts c u r r e n t l y under cons t ruc t i on

i n t he reg ion was entered i n t o the equat ion as an i n d i c a t i o n o f t he com-

p e t i n g demand f o r labor . However, the est imated c o e f f i c i e n t o f the v a r i-

able had an unexpected negat ive sign. It i s poss ib le t h a t the negat ive

c o e f f i c i e n t o f t h i s v a r i a b l e i s a r e f l e c t i o n o f the stage o f p r o j e c t

complet ion o f t he other power p lan ts . I n general these p lan ts were f a r-

the r along than our s tudy s i t e s . Thus, it i s poss ib le t h a t workers were

t rans fe r red from these p lan ts t o the s i t e s inc luded i n our study. How-

ever, owing t o the p r o x i m i t y o f the s i t e s , many workers d i d n o t have t o

move because they l i v e d w i t h i n commuting d is tance o f both cons t ruc t i on

s i t e s .

F i n a l l y , the s i z e o f the u n i t s under cons t ruc t i on entered the equa-

t i o n and had an expected p o s i t i v e sign. Thus, as was observed i n the

cons t ruc t ion worker equation, l a r g e r p lan ts a lso have greater migrant

p ropor t ion among t h e i r nonconstruct ion workers. This r e l a t i o n s h i p was

found t o be very s i g n i f i c a n t .

Unfor tunate ly , d e t a i l e d labor requirement data were no t a v a i l a b l e f o r

t he nonconstruct ion workforce. Indeed, the o n l y v a r i a b l e which was

a v a i l a b l e f o r t he nonconstruct ion group was the number o f workers on s i t e

a t the t ime o f the survey. This var iab le , however, d i d n o t en ter the

f i n a l nonconstruct ion worker equation.

Summary

I n our m u l t i v a r i a t e ana lys is we were able t o i d e n t i f y t he major

determinants o f the v a r i a t i o n i n migrant p ropor t ions across s i t e s and

across var ious worker groups. The est imated equations explained 71 and

87 percent o f t he v a r i a t i o n i n c r a f t - s p e c i f i c migrant p ropor t ions among

the cons t ruc t ion and nonconstruct ion groups. These est imated equat ions

were, i n turn, used t o s p e c i f y the steps t o fo recas t migrant p ropor t ions

a t f u t u r e nuc lear power p l a n t c o n s t r u c t i o n s i t e s . These f o r e c a s t i n g

s teps a re descr ibed i n d e t a i l i n t h e f o l l o w i n g chapter .

RESIDENTIAL LOCATION

One of t h e c r i t i c a l elements i n e s t i m a t i n g t h e socioeconomic impacts

of l a r g e energy development p r o j e c t s i s de te rmin ing t h e r e s i d e n t i a l loca-

t i o n p a t t e r n s of i n m i g r a t i n g c o n s t r u c t i o n workers. Past a t tempts t o

develop f o r e c a s t i n g procedures have i nvo l ved t h e e s t i m a t i o n o f va r i ous

forms of t h e g r a v i t y model .' These attempts, however, have n o t been

v e r y success fu l because exponent es t imates der i ved f rom t h e g r a v i t y model

have been shown t o v a r y from s i t e t o s i t e , as w e l l as f o r d i f f e r e n t

groups o f workers.' Consequently, these g r a v i t y models have been o f

o n l y l i m i t e d va lue f o r p r e d i c t i v e purposes.

Others have at tempted t o overcome t h e weaknesses o f t h e g r a v i t y model

by p ropos ing 1 i n e a r programming models, such as t h e s p a t i a l a1 l o c a t i o n

component o f t h e SEAM model .3 These models, however, r e q u i r e ex tens i ve

da ta and, as a r e s u l t , have never been va l i da ted . Thus, t h e r e i s no

s imple v a l i d a t e d methodology c u r r e n t l y a v a i l a b l e f o r a c c u r a t e l y p r e d i c t -

i n g r e s i d e n t i a l l o c a t i o n p a t t e r n s o f i n m i g r a t i n g workers a t l a r g e con-

s t r u c t i o n p r o j e c t s . The purpose o f t h i s ana l ys i s was t o develop and

es t ima te a r e s i d e n t i a l l o c a t i o n model t h a t would overcome t h e weaknesses

o f t h e c u r r e n t g r a v i t y models by e x p l i c i t l y i n c o r p o r a t i n g va r i ous reg ion-

a l and p r o j e c t c h a r a c t e r i s t i c s i n t o t h e model.

IJ. A. Chalmers, "The Role o f S p a t i a l Re la t i onsh ips i n Assessing t h e Soc ia l and Economic Impacts o f Large-Scale Cons t ruc t i on P r o j e c t s Y 1 ' Na tu ra l Resources Journa l 17:2 (1970), pp. 209-222; S. H. Murdock, J. S. Wieland and F. L. L e i s t r i t z , "An Assessment o f t h e G r a v i t y Model f o r P r e d i c t i n g Community Set t lement Pa t t e rns i n Rura l ~nergy- Impac ted Areas i n t h e West," Land Economics, 54:4 (1978), pp. 461-471.

2 ~ u r d o c k , e t a1 . , Op. c i t . 3 ~ . J. Stenehjem, Summary D e s c r i p t i o n o f SEAM: The Soc ia l and Economic Assessment Model, Argonne Na t i ona l Laboratory , Energy and Env i ronmenta l Systems D i v i s i o n , A p r i l 1978.

Model S p e c i f i c a t i o n

The g r a v i t y model captures the t rade- of fs between the s i z e of commun-

i t i e s and the d is tance o f communities from t h e i r p lace o f work which

workers face i n making r e s i d e n t i a l l o c a t i o n decisions. The bas ic form o f

the g r a v i t y model i s as fo l l ows :

( 3 ) a

Iij = A * P O P j

DIST~ i j

where:

I i j = the number o f workers r e s i d i n g i n community j, who worked a t s i t e i;

POP = popu la t ion o f community j;

DISTij = d is tance between community j and s i t e i;

a = the exponent o f populat ion;

B = the exponent o f distance; and

A = the constant o f p r o p o r t i o n a l i t y .

I n t he g r a v i t y model, popu la t ion ac ts as a proxy f o r both the a t t r a c-

t iveness o f a community and the a b i l i t y o f the community t o absorb inmi-

grants. Distance, on the o ther hand, ac ts as a proxy f o r the costs (both i n terms o f t ime and money) associated w i t h l o c a t i n g away from one's

p lace o f work. The values o f t he est imated exponents are determined by

the choices made by i n d i v i d u a l s which, i n t u rn , depend upon t h e i r per-

sonal tas tes and preferences, t h e na ture o f t h e i r employment, and the

geography of t he reg ion (i.e., the number, s izes, and types o f communi-

t i e s ava i l ab le i n the area surrounding t h e s i t e s ) . Accordingly, the

exponents are l i k e l y t o vary across s i t e s and perhaps across d i f f e r e n t

groups o f workers a t t he same s i t e . It i s f o r t h i s reason t h a t exponent

est imates obtained from the es t ima t ion o f a g r a v i t y model a t one s i t e do

n o t u s u a l l y perform very w e l l i n p r e d i c t i n g r e s i d e n t i a l l o c a t i o n pa t te rns

a t another s i t e .

Recognizing t h a t t he popu la t ion and d is tance exponents are l i k e l y t o

be in f luenced by var ious reg iona l and p r o j e c t c h a r a c t e r i s t i c s , we spec i f y

a g r a v i t y model i n which a and B are, i n tu rn , f unc t i ons o f several fac-

t o r s such as housing a v a i l a b i l i t y , reg iona l a t t rac t iveness , and workforce

composit ion.

The reduced form o f such a mod i f ied g r a v i t y model can be w r i t t e n as 4 fo l l ows :

(4 ) Ln PMOVE = Ln A + (ao + al REGATT + a2 HAVAIL + a3 WKCOMP

+ a4 CONTVAR) Ln POP + ( B ~ + B~ REGATT

+ B~ HAVAIL + 83 WKCOMP + 1 3 ~ CONTVAR) Ln DIST + c

where the popu la t ion exponent a = a. + al REGATT + a2 HAVAIL +

a3 WKCOMP + a4 CONTVAR and the d is tance exponent B = B, + B~ REGATT + B2 HAVAIL + 83 WKCOMP + B~ CONTVAR and where:

PMOVE = the number o f movers working a t the cons t ruc t i on s i t e and l i v i n g i n a p a r t i c u l a r community as a p ropo r t i on o f a l l movers;

REGATT = a t t rac t i veness o f t h e l o c a l area t o i nm ig ra t i ng workers;

HAVAIL = housing a v a i l a b i l i t y i n the l o c a l area;

WKCOMP = workforce composit ion a t the cons t ruc t i on s i t e ;

CONTVAR = c o n t r o l var iab les ; and

E = the e r r o r term.

Th i s s p e c i f i c a t i o n i s very general and permi ts the exponents o f t he

popu la t ion and d is tance terms o f t he g r a v i t y model t o vary across s i t e s ,

across d i f f e r e n t surveys a t t he same s i t e , and across var ious worker

groups. The ex ten t o f v a r i a t i o n i n the exponents i s , o f course, deter-

mined by d i f f e rences i n t he explanatory f a c t o r s ( i .e., r eg iona l a t t r a c-

t iveness, housing avai l a b i l i ty , workforce composit ion). However, the

f i n a l r e s i d e n t i a l l o c a t i o n equat ion which we est imated was more r e s t r i c t -

ed. The r e s t r i c t i o n s were imposed based upon analyses which were under-

taken p r i o r t o es t ima t ing the mod i f ied g r a v i t y model.

During these p r e l i m i n a r y analyses, we est imated a simple g r a v i t y

model (as s p e c i f i e d i n equat ion 3 ) f o r each o f t he th ree major worker

groups--nonconstruction workers, scarce cons t ruc t ion c r a f t s , and o ther

cons t ruc t i on c ra f t s- - fo r each survey. I n general, we found t h a t the

4 ~ o r t h e d e r i v a t i o n o f the reduced form o f the model, see the d e t a i l e d d e s c r i p t i o n o f t he model contained i n Appendix D.

d i f f e rences i n the r e s i d e n t i a l l o c a t i o n pa t te rns o f the th ree groups were

no t s i g n i f i c a n t l y d i f f e r e n t . Thus, i n our f i n a l s p e c i f i c a t i o n o f r e s i -

d e n t i a l l o c a t i o n equation, we d i d no t permi t the populat ion and d is tance

exponents t o vary across worker groups.

Furthermore, i n our f i n a l s p e c i f i c a t i o n we d i d no t a l low the popula-

t i o n exponent t o vary across s i t e s and surveys. The reason f o r t h i s i s

t h a t although the re i s no s t rong t h e o r e t i c a l basis t o j u s t i f y us ing d i f -

f e r e n t var iab les t o exp la in the v a r i a t i o n s i n popu la t ion and d is tance

exponents, us ing the same se t o f va r i ab les t o de f i ne i n t e r a c t i o n terms

w i t h both populat ion and d is tance (as requ i red by equat ion 4) produces

terms which are h i g h l y co l inear . Accordingly, i n our f i n a l s p e c i f i c a t i o n

we est imated a f i x e d popu la t ion exponent f o r a l l surveys and allowed o n l y

t h e d is tance exponent t o vary across surveys. This r e s t r i c t i o n , however,

i s n o t very severe s ince i n our p re l im ina ry analyses we found on l y minor

v a r i a t i o n i n popu la t ion exponents across surveys.

As a r e f l e c t i o n o f these considerat ions, i n the f i n a l s p e c i f i c a t i o n

o f our r e s i d e n t i a l l o c a t i o n equat ion we est imated a modi f ied form o f

equat ion ( 4 ) . The equat ion which we est imated can be w r i t t e n as fo l l ows :

( 5 ) Ln PMOVE = Ln A + a Ln POP + (fro + B~ REGATT + B * HAVAIL

+ B3 WKCOMP + B~ CONTVAR) Ln DIST + E

The dependent v a r i a b l e f o r the purpose o f t h i s analys is was the num-

ber o f movers working a t t he cons t ruc t ion s i t e and l i v i n g i n a given

community as a propor t ion o f a l l movers. The f i n a l equation'was e s t i -

mated us ing o rd ina ry l e a s t squares regression.

As was t r u e i n the es t imat ion o f our migrant p ropor t ion equations, a

vector o f var iab les was i d e n t i f i e d f o r each o f t he explanatory f a c t o r s

based upon both t h e o r e t i c a l considerat ions and the a v a i l a b i l i t y o f data.

For example, va r i ab les were def ined t o r e f l e c t t he d i s t r i b u t i o n o f popu-

l a t i o n and communities surrounding the cons t ruc t i on s i t e ( i .e., popula-

t i o n o f communities, number o f communities, and average community s izes

f o r var ious distances from the s i t e ) . These va r iab les were inc luded i n

an attempt t o capture the a t t rac t i veness o f t he area t o inmigra t ing

workers. Other reg iona l a t t rac t i veness va r iab les which were a lso

examined. These va r iab les inc luded t h e d is tance t o the nearest SMSA, per

c a p i t a income, popu la t i on change i n t h e l o c a l area, and employment i n t h e

s e r v i c e and r e t a i l t r a d e i n d u s t r i e s . Several v a r i a b l e s were de f i ned i n

an e f f o r t t o cap tu re t h e a v a i l a b i l i t y o f housing i n t h e l o c a l area.

These v a r i a b l e s i nc l uded housing u n i t s per cap i t a , mob i le homes per

cap i t a , vacancy r a t e and percen t owner-occupied housing. Workforce com-

p o s i t i o n v a r i a b l e s were inc luded t o cap tu re d i f f e r e n c e s i n t h e number and

c h a r a c t e r i s t i c s o f movers on s i t e a t t h e t ime o f t h e survey. These v a r i -

ables i nc l uded t o t a l number o f movers, as w e l l as scarce movers, common

and abundant movers, and noncons t ruc t ion movers as a p r o p o r t i o n o f a l l

movers. A r e g i o n a l dummy v a r i a b l e i n d i c a t i n g whether a s i t e was l o c a t e d

i n t h e Nor th o r t h e South was i nc l uded as a c o n t r o l v a r i a b l e . The pre-

c i s e d e f i n i t i o n ~ o f t h e v a r i a b l e s cons idered a re con ta ined i n Appendix D.

Resu l ts

The r e s u l t s of t h e f i n a l s p e c i f i c a t i o n o f t h e r e s i d e n t i a l l o c a t i o n

equat ion a re presented i n Tab le 4. I n general , t he equa t ion performed

q u i t e w e l l , e x p l a i n i n g over 60 pe rcen t o f t h e v a r i a t i o n i n r e s i d e n t i a l

l o c a t i o n p a t t e r n s among t h e 24 surveys inc luded i n t he equat ion. For t h e

most p a r t , v a r i a b l e c o e f f i c i e n t es t imates were found t o be s t a t i s t i c a l l y

s i g n i f i c a n t and were o f t h e expected s ign . The es t imated c o e f f i c i e n t s

were a l s o found t o be robus t . The s i g n and s i g n i f i c a n c e o f key v a r i a b l e s

were n o t s e n s i t i v e t o t he i n c l u s i o n and exc lus ion o f o t h e r v a r i a b l e s i n

t h e equat ion. These r e s u l t s suggest t h a t t h e exp lana to ry v a r i a b l e s

inc luded i n t h e es t imated equat ion do, indeed, cap tu re many o f t h e fac-

t o r s u n d e r l y i n g t h e v a r i a t i o n i n d i s t ance exponents across s i t e s .

As expected, our m u l t i v a r i a t e a n a l y s i s d i d i n d i c a t e t h a t t h e propor-

t i o n o f movers l o c a t i n g i n a p a r t i c u l a r community i s p o s i t i v e l y r e l a t e d

t o community s i z e and n e g a t i v e l y r e l a t e d t o t h e d i s tance f rom t h e con-

s t r u c t i o n s i t e . Both v a r i a b l e s were s i g n i f i c a n t a t t h e 99 percen t c o n f i -

dence l e v e l . E i g h t o t h e r v a r i a b l e s were inc luded i n t h e f i n a l s p e c i f i c a-

t i o n i n an at tempt t o cap tu re d i f f e r e n c e s i n t h e d i s tance exponent as a

f u n c t i o n o f r e g i o n a l a t t r a c t i v e n e s s , hous ing a v a i l a b i l i t y , work fo rce

composit ion, and c o n t r o l va r i ab les . O f these 8 va r i ab les , 7 were s i g n i f -

i c a n t a t o r above t h e 95 percen t conf idence l e v e l .

I n t h e g r a v i t y model e s t i m a t i o n t h e d i s tance c o e f f i c i e n t has a nega-

t i v e s i g n ( i n d i c a t i n g an i nve rse r e l a t i o n s h i p between d i s tance and t h e

TABLE 4

Res iden t ia l Locat ion Regression Results

Dependent v a r i ab le Ln PMOVE Mean -4.999

Var i ab le C o e f f i c i e n t t

Popu la t ion

Distance

Distance I n t e r a c t i o n Terms

Local r e t a i 1 a c t i v i ty

Distance from SMSA

Housing vacancy r a t e

Per c a p i t a mobi le homes

Tota l number o f movers

P ropor t i on scarce

Propor t ion o the r cons t ruc t i on

Region

Constant

dependent v a r i a b l e ) . A h igher d is tance exponent can be i n t e r p r e t e d t o

mean t h a t movers w i l l tend t o l o c a t e nearer the cons t ruc t ion s i t e and a

smal ler d is tance exponent means t h a t movers w i l l tend t o l oca te f a r t h e r

away. I n the mod i f ied g r a v i t y model as s p e c i f i e d i n equat ion (5), the

est imate o f t h e d is tance exponent i s given by the l i n e a r combination o f

the d is tance term and t h e var ious i n t e r a c t i o n terms. Thus, the c o e f f i -

c i e n t est imates o f the i n t e r a c t i o n terms a f f e c t the magnitude o f t he

d is tance exponent-- increasing i t i f the c o e f f i c i e n t i s negat ive and

decreasing i t i f t h e c o e f f i c i e n t i s p o s i t i v e . The c o e f f i c i e n t est imates

o f t he var ious i n t e r a c t i o n terms can, there fore , be examined t o determine

t h e i n f l uence o f these va r iab les upon the d is tance c o e f f i c i e n t . The

r e s u l t s o f t he regress ion equat ion w i t h respect t o each o f the explana-

t o r y f a c t o r s i d e n t i f i e d above are b r i e f l y discussed below.

1. Regional A t t rac t iveness

Several va r i ab les were def ined t o capture the general a t t rac t i veness

o f the area immediately surrounding the s i t e , i n c l u d i n g va r iab les which

were intended t o capture d i s t r i b u t i o n o f popu la t ion and communities sur-

rounding the cons t ruc t i on s i t e .5 Two o f these var iables- - distance from

the nearest SMSA and employment i n r e t a i l t rade i n d u s t r i e s i n t he l o c a l

area--entered the f i n a l equation. The negat ive c o e f f i c i e n t est imate o f

the r e t a i l t r ade v a r i a b l e imp l ies t h a t s i t e s w i t h h igher r e t a i l t r ade

a c t i v i t y i n t h e l o c a l area are more l i k e l y t o have h igher p ropor t ions of

movers l i v i n g c lose t o the s i t e than are s i t e s w i t h lower r e t a i l a c t i v i t y

i n t he l o c a l area. S i m i l a r l y , w i t h respect t o d is tance f rom the nearest

SMSA, t he p o s i t i v e c o e f f i c i e n t est imate i nd i ca tes t h a t those s i t e s a t

g rea ter d is tances from t h e nearest SMSA have smal ler d is tance exponents

and the re fo re lower p ropor t ions o f movers l i v i n g i n communities near t h e

cons t ruc t i on s i t e . S i tes which are loca ted nearer SMSA's, on the o ther

hand, have correspondingly h igher p ropor t ions o f movers l i v i n g i n commun-

i t i e s immediately surrounding t h e cons t ruc t ion s i t e . These r e s u l t s are

S ~ o summarize the popu la t ion and community c h a r a c t e r i s t i c s o f a s i t e , we def ined popu la t ion s izes, numbers o f communities and average community s izes f o r var ious d is tance i n t e r v a l s from the s i t e . These var iables, however, d i d n o t en ter our f i n a l equation.

cons i s ten t w i t h what one would expect t o observe. The est imated c o e f f i c i e n t

o f the r e t a i l t rade v a r i a b l e was s i g n i f i c a n t a t the 95 percent conf idence

l e v e l . I n t he case o f the d is tance from the nearest SMSA, however, t he 1 =

c o e f f i c i e n t was n o t found t o be s i g n i f i c a n t l y d i f f e r e n t from zero a t t h e 90

percent conf idence l eve l .

2. Housing A v a i l a b i l i t y

The a v a i l a b i l i t y o f housing i n the l o c a l area i s c l e a r l y a f a c t o r i n the

r e s i d e n t i a l l o c a t i o n decis ions o f i nm ig ra t i ng workers. Accordingly, we con-

sidered t h e f o l l o w i n g housing a v a i l a b i l i t y va r i ab les i n t h i s analys is : hous-

i n g vacancy r a t e ; percent owner-occupied housing; number o f housing u n i t s per

capi ta; and number o f mobi le homes per cap i ta . Two o f these var iab les , namely

vacancy r a t e and number o f mobi le homes per capi ta, entered the f i n a l equa-

t i o n . As expected, both c o e f f i c i e n t est imates were negat ive and h i g h l y s ig-

n i f i c a n t . Thus, these r e s u l t s i n d i c a t e t h a t h igher vacancy r a t e s and mobi le

homes per c a p i t a i n t he l o c a l area are associated w i t h h igher p ropor t ions o f

movers l i v i n g i n nearby communities.

3. Workforce Composition

I n add i t ion , several va r i ab les were examined i n an attempt t o capture the

r e s i d e n t i a l l o c a t i o n preferences o f d i f f e r e n t groups o f workers. This was

done by i n t roduc ing va r iab les def ined t o r e f l e c t d i f f e rences i n workforce

composit ion a t the s i t e a t t he t ime o f t he survey. Three such variables--

t o t a l number o f movers a t the s i t e , p ropo r t i on o f movers from the scarce

c r a f t s , and p ropo r t i on o f movers from the common and abundant crafts- -were

inc luded i n the f i n a l equation. Our r e s u l t s i n d i c a t e t h a t t he t o t a l number o f

movers i s an important var iab le . As the t o t a l number o f movers increases,

h igher p ropor t ions o f movers tend t o l oca te nearer t he cons t ruc t i on s i t e .

S i m i l a r l y , i f the p ropo r t i on o f cons t ruc t i on movers i s h igher (compared w i t h

nonconstruct i o n movers), then one observes h igher p ropor t ions o f movers 1 i v i n g

nearer the cons t ruc t i on s i t e . Among cons t ruc t i on movers, i f the p ropo r t i on o f

movers from scarce c r a f t s i s higher, then h igher p ropor t ions o f movers are

l i k e l y t o l i v e c lose r t o the s i t e . This i s most l i k e l y a r e f l e c t i o n o f the

d i f f e rences i n the p o t e n t i a l du ra t i on o f employment a t t he s i t e among the

var ious worker groups. C lear ly , movers whose employment p o t e n t i a l a t the s i t e

i s o f a shor te r du ra t i on tend t o l i v e c loser t o the s i t e than o ther workers.

4. Contro l Var iables

F i n a l l y , we examined the e f f e c t o f several con t ro l va r i ab les upon the

d is tance exponent. Only one--region--was shown t o be s i g n i f i c a n t . This sug-

gests t h a t ho ld ing o ther va r i ab les constant, on average, movers i n the South

tend t o l i v e f a r t h e r from the cons t ruc t i on s i t e than movers i n the North.

Perhaps a b e t t e r understanding o f these r e s u l t s can be achieved by exam-

i n i n g the d is tance exponents imp l i ed by the est imated equation. The c o e f f i -

c i e n t est imates were used t o est imate d is tance exponents f o r each o f the 24

surveys inc luded i n our analys is . These est imates are presented i n Table 5.

The d is tance exponents thus computed ranged from approximately 1.2 t o 1.6. It

i s important t o note t h a t d is tance exponents vary n o t o n l y across s i t e s , b u t

a l so a t t h e same s i t e a t d i f f e r e n t stages o f p r o j e c t completion. The reason

f o r t h i s i s t h a t although most va r i ab les inc luded i n the equat ion are s i t e -

s p e c i f i c var iab les , t he workforce composit ion var iab les are survey- speci f ic .

Thus, as workforce composit ion changes, so a l so does the d is tance exponent.

Comparing est imated exponents fo r those s i t e s a t which m u l t i p l e surveys were

conducted, i t can be seen t h a t d is tance exponents, i n general, increase as

cons t ruc t i on on the p r o j e c t progreses toward peak employment. This r e l a t i o n-

ship i s perhaps bes t i l l u s t r a t e d by a comparison o f t he th ree surveys con-

ducted a t S i t e 10. One w i l l note t h a t the est imated d is tance exponent o f t he

second survey (10.2) which was conducted dur ing peak employment was h igher

than the est imated d is tance exponent o f t he f i r s t survey (10.1) which was

conducted du r ing the prepeak stage. Furthermore, one w i l l observe t h a t as

employment decreased dur ing the postpeak stage (10.3), t h e est imated d is tance

exponent a l so decreased. This imp l ies t h a t as employment decreases a t a s i t e ,

t he movers l i v i n g nearer the s i t e are the f i r s t t o leave. This i s cons is ten t

w i t h the evidence found du r ing our p r o f i l e ana lys is t h a t temporary movers are

more l i k e l y t o l oca te c loser t o the s i t e than are permanent movers.

Summary

I n our m u l t i v a r i a t e ana lys is we were able t o incorporate var ious reg iona l

and p r o j e c t c h a r a c t e r i s t i c s i m p l i c i t l y i n t o the es t imat ion o f t he g r a v i t y

model, a l l ow ing the d is tance exponent t o vary from s i t e t o s i t e . Thus, i n

us ing the est imated equat ion t o fo recas t r e s i d e n t i a l l o c a t i o n pa t te rns , one

w i l l be able t o est imate a d is tance exponent a t a f u t u r e cons t ruc t i on s i t e

TABLE 5

Distance Coef f ic ients as Est imated Based Upon the Res ident ia l Locat ion Equation

Survey I d e n t i f i c a t i o n

Number

Est imated D i stance

C o e f f i c i e n t

which will differ from those observed at the sites included in our analysis 1 based upon the differences in regional and project characteristics at the

proposed site. The forecasting steps which were developed based upon these

multivariate analysis results are described in detail in the following chapter. - f 1

CHAPTER I V

DESCRIPTION OF FORECASTING PROCEDURES

I n our m u l t i v a r i a t e analyses we were ab le t o i d e n t i f y t h e f a c t o r s impor-

t a n t i n e x p l a i n i n g t h e observed v a r i a t i o n i n m ig ran t p ropo r t i ons and res iden-

t i a l l o c a t i o n p a t t e r n s across surveys (and i n t h e case o f m ig ran t p ropo r t i ons

across var ious c r a f t groups). These est imated equat ions were then used as a

b a s i s f o r s p e c i f y i n g procedures f o r f o r e c a s t i n g mig ran t p ropo r t i ons and r e s i -

d e n t i a l l o c a t i o n p a t t e r n s o f movers a t f u t u r e nuc lea r power p l a n t c o n s t r u c t i o n

s i t e s . Because o f l i m i t e d resources we were unable t o conduct m u l t i v a r i a t e

analyses o f t h e v a r i a t i o n i n o t h e r impor tant personal and household charac te r-

i s t i c s o f movers. However, t h e d i f f e r e n c e s i n these va r i ab les which we ob-

served i n our p r o f i l e ana l ys i s were used t o suggest procedures f o r making

improved p r e d i c t i o n s o f t h e p ropo r t i ons o f movers who are l i k e l y t o r e l o c a t e

t h e i r f a m i l i e s , t he type o f housing se lec ted by movers, t h e i r i n t e n t i o n t o

remain i n t h e area and personal c h a r a c t e r i s t i c s ( m a r i t a l s t a tus and average

f a m i l y s i z e ) o f movers.

Th i s chapter p resen ts a d e t a i l e d d e s c r i p t i o n o f how one would use these

procedures t o make fo recas ts a t f u t u r e nuc lear power p l a n t c o n s t r u c t i o n

s i t e s . The chapter i s d i v i d e d i n t o 4 sec t ions . The f i r s t 3 sec t ions descr ibe

t he procedures f o r p r e d i c t i n g mig ran t p ropor t ions , personal and household

c h a r a c t e r i s t i c s of movers, and t h e r e s i d e n t i a l l o c a t i o n p a t t e r n s o f movers.

Each s e c t i o n inc ludes a s tep- by- step d e s c r i p t i o n o f t h e f o r e c a s t i n g proce-

dures, i n c l u d i n g i d e n t i f i c a t i o n o f da ta t o be co l l ec ted , da ta sources, d e f i n i -

t i o n of va r iab les , and t h e s teps i n t h e computat ion o f t h e v a r i a b l e o f i n t e r -

es t . The f i n a l s e c t i o n p resen ts a b r i e f d iscuss ion o f t h e v a l i d i t y o f these

f o r e c a s t i n g procedures.

PREDICTING MIGRANT PROPORTIONS

The procedures descr ibed here f o r p r e d i c t i n g o v e r a l l m ig ran t p ropo r t i ons

a t nuc lear power p l a n t c o n s t r u c t i o n s i t e s a re based on t h e m ig ran t p r o p o r t i o n

equat ions which were presented i n t h e p rev ious chapter . Two equat ions were

est imated. The c o n s t r u c t i o n worker equat ion was est imated us ing 7 major con-

s t r u c t i o n c r a f t s as u n i t s o f ana lys is . The noncons t ruc t ion worker equat ion

was est imated us ing two worker groups--management and c l e r i c a l - - a s u n i t s of

ana lys is . The r e s u l t s o f these equat ions thus can be used t o p r e d i c t m ig ran t

p ropo r t i ons f o r 9 separate groups o f workers a t a s i t e .

The e i g h t h c o n s t r u c t i o n c r a f t g roup- - cons is t ing o f workers f r om a l l o t h e r

c o n s t r u c t i o n c ra f ts- - was n o t inc luded i n t h e es t imated c o n s t r u c t i o n worker

equat ion. ' A1 though t h e i n d i v i d u a l c r a f t s inc luded i n t h i s group t y p i c a l l y

do n o t represen t l a r g e numbers o f workers a t nuc lea r power p l a n t c o n s t r u c t i o n

s i t e s , as a s i n g l e group t h e y can c o n s t i t u t e a r a t h e r l a r g e number o f workers

a t a p a r t i c u l a r s i t e (among t h e surveys i n our sample t h e s i z e o f t h i s group

ranged f rom 20 t o 268 workers) . As such, i t i s impor tan t t o cons ider t h i s

group i n e s t i m a t i n g o v e r a l l m ig ran t p ropo r t i ons .

A separate equa t ion was est imated f o r t h e purpose o f p r e d i c t i n g m ig ran t

p r o p o r t i o n s f o r t h i s group. Seven reg ress ion equat ions were es t imated i n

which t h e m ig ran t p r o p o r t i o n o f t he o the r c o n s t r u c t i o n c r a f t group was ex-

pressed as a f u n c t i o n o f t h e m ig ran t p r o p o r t i o n o f each o f t h e 7 major con-

s t r u c t i o n c r a f t groups. The one equat ion which bes t exp la ined t h e v a r i a t i o n

i n m ig ran t p r o p o r t i o n s o f t h e o t h e r c o n s t r u c t i o n c r a f t group- - the l a b o r e r and

teamster equation--was used t o develop procedures f o r f o r e c a s t i n g t h e mig ran t

p ropo r t i ons o f t h e o t h e r c o n s t r u c t i o n c r a f t group a t f u t u r e c o n s t r u c t i o n

s i t e s . 2

l ~ h e reason t h a t t h i s group i s t r e a t e d d i f f e r e n t l y f rom t h e 7 major con- s t r u c t i o n c r a f t groups i s t h a t t h e group i s comprised of smal l numbers of workers f r om severa l d i f f e r e n t c o n s t r u c t i o n c r a f t s ( i .e., sheetmetal workers, asbestos workers, pa in te r s , b r i c k l a y e r s ) . I n d i v i d u a l l y these c r a f t s were t o o smal l t o be inc luded i n t he c o n s t r u c t i o n worker equat ion. However, as a s i n - g l e group t hey represen t a r e l a t i v e l y heterogeneous group and severa l explana- t o r y v a r i a b l e s cou ld n o t be determined f o r t h e group. Thus, t h e c o n s t r u c t i o n worker equa t ion can n o t be used t o p r e d i c t t h e m ig ran t p r o p o r t i o n s o f t h i s p a r t i c u l a r group.

2 ~ h e r e s u l t s o f t h e est imated equat ion are as f o l l o w s :

MPROP, = (2.86 x TEAM) - .07

where: MPROP, = t h e mig ran t p r o p o r t i o n o f t h e o the r c o n s t r u c t i o n c r a f t group; and

TEAM = t h e m ig ran t p r o p o r t i o n o f l abo re rs and tea.msters.

The es t imated equat ion exp la ined 50 percen t o f t h e v a r i a t i o n i n t h e m ig ran t p r o p o r t i o n s o f t h e o t h e r c o n s t r u c t i o n c r a f t group among t h e surveys inc luded i n t h e ana lys is .

Accord ing ly , t o es t imate o v e r a l l m ig ran t p ropo r t i ons and t h e r e f o r e t o t a l

number o f movers a t a f u t u r e nuc lea r power p l a n t s i t e us ing our methodology,

one must f i r s t es t imate t h e m ig ran t p ropo r t i ons o f 8 c o n s t r u c t i o n and 2 non-

c o n s t r u c t i o n c r a f t groups. Ove ra l l m ig ran t p r o p o r t i o n can then be determined

by t he weighted average o f these i n d i v i d u a l c r a f t m ig ran t p r o p o r t i o n e s t i -

mates. It migh t be noted t h a t t h e accuracy o f o v e r a l l m ig ran t p r o p o r t i o n

p r e d i c t i o n s , thus determined, w i l l be g rea te r than t h e accuracy o f t h e m ig ran t

p r o p o r t i o n p r e d i c t i o n s a t t h e c r a f t l e v e l . The s teps invo lved i n f o r e c a s t i n g

o v e r a l l m ig ran t p ropo r t i ons and t h e t o t a l number o f movers a t a f u t u r e con-

s t r u c t i o n s i t e a re descr ibed i n d e t a i 1 below.

Step 1 - Spec i f y t h e yea r ( s ) f o r which t h e p r o j e c t i o n ( s ) i s t o be made.

The proposed f o r e c a s t i n g procedures es t imate mig ran t p ropo r t i ons f o r a

p a r t i c u l a r p o i n t i n t ime. Thus, be fo re p r e d i c t i n g mig ran t p ropo r t i ons i t i s

necessary t o s p e c i f y t h e y e a r ( s ) o r q u a r t e r ( s ) d u r i n g t h e c o n s t r u c t i o n p e r i o d

f o r which t h e p r o j e c t i o n ( s ) i s t o be made ( h e r e a f t e r r e f e r r e d t o as p r o j e c t i o n

year and p r o j e c t i o n q u a r t e r ) .

Step 2 - D i v i d e p ro jec ted workforce i n t o 10 c r a f t groups.

Determine t h e average d a i l y employment i n each o f t h e f o l l o w i n g c r a f t

groups du r i ng t h e p r o j e c t i o n qua r te r .

Cons t ruc t ion C r a f t s

o Plumbers and P i p e f i t t e r s ;

0 I ronworkers;

0 Boi lermakers;

Operat ing Engineers;

0 E l e c t r i c i a n s ;

Carpenters ( i n c l u d i n g M i l l w r i g h t s ) ;

Laborers and Teamsters; and

Other c o n s t r u c t i o n c r a f t s .

Nonconstruct i o n Cra f ts

C l e r i c a l workers ( i n c l u d i n g s e c u r i t y and med ica l /nurs ing s t a f f ) ; and

0 Management ( a1 1 o t h e r noncons t ruc t ion workers, i n c l u d i n g managers, engineers, and superv iso rs ) .

C r a f t - s p e c i f i c l abo r requirement p r o j e c t i o n s can be ob ta ined f rom t h e Con-

s t r u c t i o n Labor Demand System (CLDS) data. These da ta a re descr ibed i n

g rea te r d e t a i l under Step 3 below.

Step 3 - Data C o l l e c t i o n .

For t h e purpose o f da ta c o l l e c t i o n d e f i n e two impact areas. De f ine a

r e g i o n a l impact area surrounding t he c o n s t r u c t i o n s i t e t o i n c l u d e a l l coun t i es

o f which h a l f o r more o f t he t o t a l l and area i s w i t h i n a 50-mi le r a d i u s o f t h e

s i t e . Also, d e f i n e a l o c a l impact area t o i n c l u d e t h e coun ty i n which t h e

s i t e i s loca ted , p l u s any o the r coun ty which con ta ins a s i g n i f i c a n t p o r t i o n o f

t h e land area (i.e., 30 percent o r more) w i t h i n 15 highway m i l e s o f t h e s i t e .

Data must be ob ta ined f rom severa l sources. C e r t a i n da ta ( I tems 1-4) must

be ob ta ined f o r each o f t he seven ma jo r c o n s t r u c t i o n c r a f t s as de f i ned i n

Step z . ~ Some da ta ( I tems 5-6) must be c o l l e c t e d f o r a l l coun t i es i n t h e

reg ion- a1 impact area, w h i l e o t h e r da ta ( I t em 7 ) must be c o l l e c t e d o n l y f o r

coun t i es i n t he l o c a l impact area. I n add i t i on , va r i ous s i t e - s p e c i f i c da ta

( I tems 8-10) must be obta ined. The s p e c i f i c da ta t o be c o l l e c t e d and t h e

v a r i a b l e s t o be de f i ned based upon these da ta are descr ibed i n d e t a i l below.

I tem 1 H o u r l y and over t ime wage ra tes . These da ta a re s p e c i f i e d i n

c o l l e c t i v e ba rga in i ng agreements which can be ob ta ined f rom un ion

l o c a l s o r through l a b o r r e l a t i o n s o f f i c e s o f u t i l i t i e s . I n addi-

t i o n , o b t a i n t he Na t i ona l Consumer P r i c e Index f o r 1978 and t h e

c u r r e n t year f rom Bureau o f Labor S t a t i s t i c s p u b l i c a t i o n s .

Compute t h e f o l l o w i n g va r i ab les :

WAGE = t he s t r a i g h t - t i m e h o u r l y wage r a t e ( i n 1978 d o l - l a r s ) f o r a journeyman (i.e., $9.38 i s d e f i n e d as 9.38).

OTIME = t he d a i l y over t ime r a t e expressed as a m u l t i p l e o f t he hourly wage r a t e (i.e., double t ime i s d e f i n e d as 2.0).

3 ~ a t a f o r l a b o r e r s and teamsters should be ob ta ined separa te ly . I n t h e case o f l a b o r requi rement v a r i a b l e s t h e da ta a re added. I n t h e case o f o the r v a r i a b l e s t h e da ta are averaged.

Item 2 Craft-specific labor requirement projections by quarter for the

duration of the project. These data can be obtained from the

utility. However, we found utility projections to be inferior to

projections obtained from the Construction Labor Demand System

(CLDS) data.4 Use of CLDS data is recommended, if available.

For the purpose of prediction labor requirement projections must

be converted to average daily employment for each quarter (use 8

hours per day and 65 working days per quarter for conversion if

not available in these units). For each of the 7 major construc-

tion crafts compute the following variables:

CONT = the number of quarters in which projected average daily employment is greater than or equal to the average daily employment of the previous quarter.

DEMP = the number of quarters in which projected average daily employment is greater than or equal to 25 percent of the highest projected average daily employment for any quarter.

GREMP = the ratio of the average daily employment for the projection year to the average daily employment for the four highest consecutive quarters over the remaining construction period.

Also define the following variables:

SCAR = 1 for pipefitters, ironworkers, and boilermakers 0 for operating engineers, electricians, carpenters, laborers and teamsters

COM = 1 for operating engineers, electricians, and carpenters

0 for pipefitters, ironworkers, boilermakers, laborers and teamsters

0 for GREMP > 1

D2 = 1 for GREMP > 1

0 for GREMP L 1

4 ~ h e Construction Labor Demand System is a Department of Labor program for estimating on-site labor requirements for the construction of current, planned or forecasted energy development projects in the U.S. The CLDS provides estimated manpower requirements by month and year for 29 construction craft groups.

SDEMP = SCAR x DEMP

CDEMP = COM x DEMP

GREMPl = D l x GREMP

GREMP2 = 02 x GREMP

I t em 3 Annual c r a f t - s p e c i f i c l a b o r reauirement ~ r o . i e c t i o n s f o r a l l o t he r

power p l a n t c o n s t r u c t i o n p r o j e c t s w i t h i n 50 m i l e s o f t h e con-

s t r u c t i o n s i t e over t h e p r o j e c t e d c o n s t r u c t i o n pe r i od . Informa-

t i o n on t h e l o c a t i o n o f o t h e r power p l a n t s be ing b u i l t i n t h e

r e g i o n a re a v a i l a b l e i n a p u b l i c a t i o n e n t i t l e d

P l a n t s i n t h e Un i t ed ~ t a t e s . ~ Obta in c r a f t - s p e c i f i c l a b o r

p r o j e c t i o n s f o r a l l o t h e r power p l a n t s ( bo th nuc lear and non-

nuc lea r ) f rom t h e CLDS data. Convert da ta i n t o t o t a l number o f

man-hours p r o j e c t e d (use 8 hours pe r day and 260 work ing days p e r

year i f n o t a v a i l a b l e i n these u n i t s ) . For each o f t h e 7 major

c o n s t r u c t i o n c r a f t s compute t h e f o l l o w i n g v a r i a b l e :

DDR50 = t h e average annual l a b o r requi rements ( i n thousands o f man-hours) a t a1 1 o t h e r power p l a n t c o n s t r u c t i o n p r o j e c t s w i t h i n 50 m i l e s o f t h e s i t e f r om t h e year c o n s t r u c t i o n i s scheduled t o beg in on t h e p r o j e c t through t h e p r o j e c t i o n year.

I t em 4 The l o c a t i o n o f t h e nea res t h i r i n g h a l l o f t h e un ion l o c a l w i t h

j u r i s d i c t i o n over t h e p r o j e c t . T h i s i n fo rma t i on may be con ta ined

i n t h e c o l l e c t i v e ba rga in i ng agreement of t h e un ion l o c a l . If

not , t h e i n fo rma t i on can be obta ined by c o n t a c t i n g t h e un ion h a l l

o r f rom t h e l a b o r r e l a t i o n s o f f i c e o f a u t i l i t y . Using a s t a t e

highway map c a l c u l a t e t h e d i s tance o f t h e h i r i n g h a l l f r om the

c o n s t r u c t i o n s i t e . De f i ne t h e f o l l o w i n g v a r i a b l e :

DLOCAL = t h e d i s tance ( i n m i l e s ) f rom t h e c o n s t r u c t i o n s i t e t o t h e h i r i n g h a l l o f t h e un ion l o c a l w i t h j u r i s d i c t i o n over t h e p r o j e c t .

5 ~ n v e n t o r y o f Power P l a n t s i n t h e Un i t ed States, U.S. Department o f Energy, O f f i c e o f U t i l i t y Operat ions, December, 1977.

Item 5 Population of a1 1 counties in the regional impact area (the cur-

rent population and the population 5 years prior). These data

can be obtained from Census publications.6 Calculate the fol-

lowing variables:

RPOP = the total current population of all counties in the regional impact area.

RPOPGR = population growth in the last five years expressed as a percent of the population 5 years prior (i.e., current population minus population 5 years prior, divided by the population 5 years prior and multiplied by 100) for the regional impact area. (Note: a population decrease will result in a negative val ue. )

Item 6 Civilian labor force and unemployment rate by county for the past

3 years. These data can be obtained from the appropriate employ-

ment agency of the state or states in which the respective coun-

ties are located. Compute the following variable:

RUN = the average unemployment rate for the past 3 years (weighted by civilian labor force) of all counties in the regional impact area. (Note: the unemployment rate variable is expressed as a percent. )

Item 7 Number of vacant units and total number of housing units in the local impact area. If recent information is not available from a

local source, obtain the most recent census data.7 Define the

following variable:

VACRT = total number of vacant units divided by the total number of housing units in the local impact area multiplied by 100.

%ata for Census years are contained in U.S. Bureau of the Census, Census of Population, Characteristics of the Population. Population estimates for non- census years are contained in U.S. Bureau of the Census, Current Population Reoorts. Series P-25 and P-26.

'u.s. Bureau of the Census, Census of Housing, Characteristics for States, Cities, and Counties.

Item 8 Number and populations of communities within 25 miles of the n 0 site. Populations of communities with populations of 2500 or

more are available in census publications. Population estimates

of smaller comnunities are available in the Rand McNally, Commer-

cial Atlas and Marketing Guide. Compute the following variables:

COMlO = the total population of all communities within 10 miles of the construction site divided by the number of comnunities within 10 miles of the site.

COM25 = the total population of all communities within 25 miles of the construction site divided by the number of communities within 25 miles of the site.

Item 9 Number of other nuclear power plants under construction within 50

miles of the construction site. These data can be obtained from

DOE publications.9 Define the following variable:

ONC = the total number of other nuclear power plant units currently under construction within 50 miles of the construction site.

Item 10 Size of the units to be constructed at the site. This informa-

tion can be readily obtained from the utility. Define the fol-

lowing variable:

MWATT = the total number of megawatts in all units to be constructed at the site over the period for which the projection is being made.

Step 4 - Apply the construction worker equation. For each of the 7 major construction crafts, predict X as follows:

X = 39.64

+ 1.58 x Ln WAGE

+ 3.41 x Ln OTIME

8~ornmunities for the purpose of this analysis are those with their own post office (i.e., zip code).

9 ~ o r example see Nuclear Reactors Built, Being Built, or Planned in the United States as of June 30, 1918 (Oak Ridge: Dot Technical Information Center, 1978).

+ 1.19 x Ln CONT

- 3.10 x Ln DEMP

- .31 x Ln SDEMP

+ 1.86 x Ln CDEMP

+ .48 x Ln GREMPl

- .52 x Ln GREMP2

+ .48 x Ln DDR50

+ .21 x Ln DLOCAL

+ 1.71 x Ln RPOP

- 1.11 x RPOPGR

- 3.11 x Ln COM25

+ 1.49 x Ln C O M l O

+ .16 x Ln VACRT

- 6.25xCOM

+ 1.11 x SCAR

+ 1.45 x Ln MWATTS

Step 5 - Ca l cu la te m ig ran t p ropo r t i ons (MPROP) f o r t h e c o n s t r u c t i o n groups.

Ca l cu la te MPROP f o r each o f t h e 7 ma jo r c o n s t r u c t i o n c r a f t s .

MPROP = Y

1 + Y X where: y = e

(Note: MPROP ranges f r om 0 t o 1.)

Step 6 - Apply t h e o t h e r c o n s t r u c t i o n c r a f t s equat ion.

Ca l cu la te t h e m ig ran t p r o p o r t i o n f o r t h e o t h e r c o n s t r u c t i o n c r a f t group as

a f u n c t i o n o f t h e p red i c ted m ig ran t p r o p o r t i o n f o r l abo re rs and teamsters.

MPROP = (2.86 x TEAM) - .07

where: TEAM i s t h e p r e d i c t e d mig ran t p r o p o r t i o n f o r l abo re rs and

teamsters (Note: TEAM i s expressed as a va lue between 0

and 1 . )

Step 7 - Apply noncons t ruc t ion worker equat ion.

For t h e management and c l e r i c a l groups c a l c u l a t e X as f o l l o w s :

X = - 1.70

+ 1.70 x MGCL

- .61 x Ln RUN

- .40 x Ln ONC

- .47 x Ln RPOP

+ 1.05 x Ln MWATTS

Step 8 - Ca l cu la te m i g r a n t p ropo r t i ons (MPROP) f o r t h e nonconst ruct i o n groups.

C a l c u l a t e MPROP f o r t h e management and c l e r i c a l groups.

MPROP = Y

1 + Y X where: y = e

Step 9 - P r e d i c t t o t a l number o f movers.

P r e d i c t t h e number o f movers i n each c r a f t group (NMOVEi) as f o l l o w s :

where: MPROPi = t h e m ig ran t p r o p o r t i o n o f c r a f t group i; and

EMP = t h e average d a i l y employment f o r c r a f t group i

f o r t h e p r o j e c t i o n qua r te r .

The t o t a l number o f movers a t t h e c o n s t r u c t i o n s i t e (NMOVET) can then be

p r e d i c t e d as fo l lows10:

PREDICTING PERSONAL AND HOUSEHOLD CHARACTERISTICS OF MOVERS

I n a d d i t i o n t o m ig ran t p ropor t ions , severa l personal and household charac-

t e r i s t i c s o f movers a re a l so impor tan t i n making socioeconomic impact

l 00ve ra l 1 m ig ran t p ropo r t i ons (MPROPT) can be s imp ly c a l c u l a t e d as f o l lows:

MPROPT = NMOVET/TEMP 1 0

where: TEMP = .; EMPi 1-1

assessments. Not a l l , however, a re e q u a l l y impor tan t i n i n f l u e n c i n g t h e mag-

n i t u d e o f t h e impacts. Compared w i t h m ig ran t p ropo r t i ons and r e s i d e n t i a l

l o c a t i o n pa t te rns , these c h a r a c t e r i s t i c s a re o f secondary importance. We

se lec ted 5 such c h a r a c t e r i s t i c s and used t h e r e s u l t s o f our analyses t o sug-

ges t procedures f o r p r e d i c t i n g these v a r i a b l e s a t f u t u r e nuc lear power p l a n t

c o n s t r u c t i o n s i t e s . These c h a r a c t e r i s t i c s i n c l u d e r e l o c a t i o n o f dependents,

i n t e n t i o n t o remain i n t h e area, t ype o f housing se lected, m a r i t a l s t a t u s and

average f a m i l y s i z e o f workers w i t h f a m i l y present .

Because these v a r i a b l e s a re o f secondary importance i n impact assessment,

t h e approach adopted t o d e r i v e p r e d i c t i n g procedures f o r these v a r i a b l e s was

n o t based on an ex tens ive m u l t i v a r i a t e ana l ys i s . Instead, we used t h e system-

a t i c v a r i a t i o n s which we observed i n these v a r i a b l e s d u r i n g our p r o f i l e anal-

y s i s as t h e bas i s f o r s p e c i f y i n g procedures f o r f o r e c a s t i n g these v a r i a b l e s a t

f u t u r e c o n s t r u c t i o n s i t e s .

I n our p r o f i l e ana l ys i s we observed l a r g e v a r i a t i o n s i n t h e p r o p o r t i o n o f

movers w i t h f a m i l y p resen t f o r va r ious worker groups, w i t h h i ghe r p r o p o r t i o n s

o f movers w i t h f a m i l y p resen t among t h e noncons t ruc t ion group than among t h e

c o n s t r u c t i o n group. S i m i l a r l y , when c o n s t r u c t i o n movers were f u r t h e r d isag-

gregated by r e l a t i v e s c a r c i t y o f labor , we observed somewhat h i ghe r p ropor-

t i o n s w i t h f a m i l y p resen t among t h e common and abundant c r a f t group than among

t h e scarce c r a f t group. I n add i t ion , w i t h respec t t o some f a c t o r s a n o r t h 1

south d i f fe rence was a l so observed. For ins tance, we observed a s i g n i f i c a n t

r eg iona l d i f f e r e n c e i n t h e t ype o f housing se lec ted by movers, w i t h s i n g l e

f a m i l y houses and mob i l e homes more l i k e l y t o be chosen i n t h e South than i n

t h e Nor th . Regional d i f f e r e n c e s were a l so observed w i t h respec t t o t h e r e l o -

c a t i o n o f dependent and m a r i t a l s ta tus .

Accord ing ly , i n s p e c i f y i n g our f o r e c a s t i n g procedures we attempted t o

i nco rpo ra te i n fo rma t i on rega rd ing workforce composi t ion and l o c a t i o n o f t h e

s i t e (which a re a v a i l a b l e p r i o r t o c o n s t r u c t i o n ) t o make more p r e c i s e p r e d i c -

t i o n s o f mover c h a r a c t e r i s t i c s . I n genera l , average values f o r t he var ious

worker groups across a l l s i t e s f o r which da ta were a v a i l a b l e were c a l c u l a t e d

and these averages a re used as a bas i s f o r making p r e d i c t i o n s . I n t h e case of

those va r i ab les f o r which r e g i o n a l d i f f e r e n c e s were found t o e x i s t , separate

averages were computed f o r no r t he rn and southern s i t e s . By adopt ing t h i s

procedure we are ab le t o t ake i n t o account d i f f e r e n c e s i n workforce composi-

t i o n and r e g i o n a l d i f f e r e n c e s i n p r e d i c t i n g these v a r i a b l e s a t f u t u r e con-

s t r u c t i o n s i t e s .

Relocat ion o f Dependents

F i r s t , we est imate the number o f movers who are l i k e l y t o r e l o c a t e t h e i r

f a m i l i e s . Average values f o r t h e 3 groups-- the nonconstruct ion group, scarce

group, and common and abundant group--were ca lcu la ted f o r t h e nor thern and

southern s i t e s and served as the bas i s f o r the development o f f o recas t i ng

procedures. The number o f movers who w i l l r e l oca te f a m i l i e s can be pred ic ted

as fo l l ows :

Step 1 - Obta in pred ic ted numbers o f movers f o r 3 c r a f t groups.

Obtain the pred ic ted number o f movers i n the nonconstruct i o n (NMOVE~~) ,

scarce (NMOVES) and common and abundant (NMOVECA) c r a f t groups based upon

the number o f movers i n t h e 10 c r a f t groups as pred ic ted i n t h e prev ious sec-

t ion. 2

NMOVENC = I NMOVEi i =l

where f o r subsc r ip t i 1 = management, and

2 = c l e r i c a l .

f o r subsc r ip t j 1 = p i p e f i t t e r s ,

2 = i ronworkers, and

3 = boi lermakers.

f o r subsc r ip t k 1 = e l e c t r i c i a n s ,

2 = carpenters,

3 = opera t ing engineers,

4 = laborers and teamsters, and

5 = o the r cons t ruc t i on c r a f t s .

Step 2 - Est imate the number o f movers w i t h f a m i l y present (NFAM).

The number o f movers w i t h f a m i l y present can be obta ined as fo l l ows :

( a ) For nor thern s i t e s ,

NFAM = .66 x NMOVENC

(b ) For southern s i t e s ,

NFAM = -75 x NMOVENC

+ .61 x NMOVES

+ -65 x NMOVECA

I n t e n t i o n t o Remain i n t he Area

I n t h e case o f i n t e n t i o n t o remain i n t h e area we est imate the number o f

movers who are temporary ( i .e., expect t o leave t h e area e i t h e r be fore o r upon

complet ion o f t h e p r o j e c t ) . The number o f movers who expect t o leave the area

upon complet ion o f t he p r o j e c t can be est imated as fo l l ows :

Step 1 - Obtain t he pred ic ted numbers o f movers f o r 2 c r a f t groups.

Obta in t he pred ic ted number o f movers i n t he cons t ruc t i on (NMOVEC) and

nonconstruct ion (NMOVE~~) c r a f t groups as i n Step 1 of Re loca t ion o f Depen-

dents where:

NMOVEC = NMOVEs + NMOVECA

Step 2 - Est imate number o f movers who are temporary (NTEMP).

The number o f a l l movers who are temporary can be obtained as fo l l ows :

NTEMP = -68 x NMOVENC

Type o f Housing

The var iab les o f i n t e r e s t i n es t imat ing type o f housing chosen by movers

are the numbers o f movers l i v i n g i n f o u r d i f f e r e n t housing types. These four

housing types are: houses, mobi le homes, apartments and o the r housing ( i .e.,

ho te ls , motels, boarding and rooming houses). Average values o f movers 1 i v i n g

i n each o f t he f o u r housing types were ca l cu la ted f o r t he cons t ruc t i on and

nonconstruct ion groups f o r t h e nor thern and southern s i t e s . These average

values served as a bas is f o r t he development o f f o recas t i ng procedures. The

number o f a l l movers who are l i k e l y t o l i v e i n each o f t he f o u r housing types

can be est imated as fo l l ows :

Step 1 - Obtain p red i c ted numbers o f movers f o r 2 c r a f t groups.

Obta in t he pred ic ted number o f movers i n t h e cons t ruc t i on (NMOVEC) and

nonconstruct ion ( N M O V E ~ ~ ) groups as descr ibed i n Step 1 o f I n t e n t i o n t o

Remain i n t he Area.

Step 2 - Est imate number o f movers choosing var ious housing types.

The number o f movers l i v i n g i n each o f f o u r housing types can be obta ined

as fo l l ows :

( a ) For nor thern s i t e s ,

HOUSE = 51 x NMOVENC

+ .36 x NMOVEC

MOBILE = a10 x NMOVENC

+ .23 x NMOVEC

APT = -35 x NMOVENC

+ .22 x NMOVEC

OTHER = -04 x NMOVENC

+ .19 x NMOVEC

(b ) For southern s i t e s ,

HOUSE = -59 x NMOVENC

+ .34 x NMOVEC

MOBILE = -18 x NMOVENC

+ -43 x NMOVEC

APT = .20 x NMOVENC

+ .14 x NMOVEC OTHER = .04 x NMOVENC

+ .09 x NMOVEC

M a r i t a l Status

The v a r i a b l e t o be pred ic ted i n t h i s instance i s t he p r o p o r t i o n o f movers

who are marr ied. To ta l number o f marr ied movers can be est imated based upon

t h e numbers o f cons t ruc t i on and nonconstruct ion movers and t h e average propor-

t i o n s o f movers who are mar r ied f o r these two worker groups f o r nor thern and

southern s i t e s . The number o f marr ied movers can be est imated as fo l l ows :

Step 1 - Obtain t he p red i c ted numbers o f movers f o r 2 c r a f t groups.

Obta in t h e pred ic ted number o f movers i n the cons t ruc t i on (NMOVEC) and

nonconstruct ion (NMOVENC) c r a f t groups as descr ibed i n Step 1 o f I n t e n t i o n

t o Remain i n t he Area.

Step 2 - Es t imate number o f movers who are mar r ied (MARRIED).

The number o f movers who a re mar r i ed can be es t imated as f o l l o w s :

( a ) For no r t he rn s i t e s ,

MARRIED = .74 x NMOVENC

( b ) For southern s i t e s ,

MARRIED = -76 x NMOVENC

+ .87 x NMOVEC

Average Fami ly S ize

I n examining average f a m i l y s i z e we focused upon t h e average f a m i l y s i z e

( i n c l u d i n g t h e worker) o f movers who r e l o c a t e t h e i r f a m i l i e s . The average

f a m i l y s i z e d i d n o t , d i f f e r much f o r va r ious worker groups. The average f a m i l y

s i z e f o r t h e c o n s t r u c t i o n group was 3.4 compared w i t h 3.1 f o r t h e nonconstruc-

t i o n group. Thus, once t h e number o f movers w i t h f a m i l y p resen t has been

ca l cu la ted , these average values can be used t o develop mu1 t i p 1 i e r s f o r d e t e r -

min ing t o t a l popu la t i on inc rease assoc ia ted w i t h t h e i n m i g r a t i n g workers and

t h e i r fami 1 ies .

PREDICTING RESIDENTIAL LOCATION PATTERNS

The f o r e c a s t i n g procedures f o r r e s i d e n t i a l l o c a t i o n i n v o l v e e s t i m a t i n g t h e

numbers o f movers which can be expected t o s e t t l e i n i n d i v i d u a l communities

surrounding t h e c o n s t r u c t i o n s i t e . The procedures descr ibed here a re based

upon t h e r e s u l t s o f t h e mod i f i ed g r a v i t y model equat ion which were presented

i n t he p rev ious chapter . Var ious r e g i o n a l and p r o j e c t c h a r a c t e r i s t i c s a re

used t o es t ima te d i s tance and popu la t i on exponents, which a re then i nco rpo r -

ated i n t o a g r a v i t y model and used t o p r e d i c t t h e r e s i d e n t i a l l o c a t i o n p a t t e r n

o f i n m i g r a t i n g workers. The s teps i nvo l ved i n f o r e c a s t i n g r e s i d e n t i a l l oca-

t i o n p a t t e r n s a t f u t u r e c o n s t r u c t i o n s i t e s a re descr ibed i n d e t a i l below.

Step 1 - Determine t o t a l number o f movers and movers f o r 3 c r a f t groups.

Obta in es t imates o f t h e t o t a l number movers as descr ibed i n Step 9 o f

M ig ran t Propor t ions . I n add i t i on , o b t a i n t h e p red i c ted number o f scarce

movers and t h e p r e d i c t e d number o f common and abundant movers as descr ibed i n

Step 1 o f Re loca t ion o f Dependents.

Step 2 - I d e n t i f y communities f o r which f o r e c a s t s w i l l be made.

I d e n t i f y a l l communit ies i n t he area surrounding t h e proposed c o n s t r u c t i o n

s i t e which s a t i s f y t h e f o l l o w i n g s i z e and d i s tance c r i t e r i a : 11

e a l l communit ies w i t h i n 15 m i l e s o f t he s i t e ;

e communit ies w i t h 2500 o r more i n h a b i t a n t s l o c a t e d f rom 15 t o 40 m i l e s f rom the s i t e ;

e communit ies w i t h 10,000 o r more i n h a b i t a n t s l o c a t e d f rom 41 t o 60 m i l e s f rom the s i t e ; and

communit ies w i t h 100,000 o r more i n h a b i t a n t s l o c a t e d f r om 61 t o 80 m i l e s f rom the s i t e .

S t e ~ 3 - Data C o l l e c t i o n

Data must be ob ta ined f r om severa l sources. C e r t a i n da ta ( I tems 1-2) must

be ob ta i ned f o r each community i d e n t i f i e d i n Step 2. Other da ta ( I tems 3- 5)

must be c o l l e c t e d f o r coun t i es i n t h e l o c a l impact area as d e f i n e d under Step

3 o f t h e m ig ran t p ropo r t i ons p r e d i c t i n g procedures. I n a d d i t i o n , va r ious

s i t e - s p e c i f i c da ta ( I tems 6-8) must be obta ined. The s p e c i f i c da ta t o be

c o l l e c t e d and t h e v a r i a b l e s t o be de f i ned based upon these da ta a re descr ibed

i n d e t a i l below.

I t em 1 Popu la t i on of t h e community. Popu la t ion o f communit ies w i t h

popu la t i on o f 2500 o r more are a v a i l a b l e i n census pub l i ca - . .

t ions. l2 Popu la t ion es t imates o f sma l l e r communit ies a re

a v a i l a b l e i n t he Rand McNally, Commerical A t l a s and Marke t ing

Guide. De f i ne t he f o l l o w i n g va r i ab les :

POP = popu la t i on o f t h e community.

POP15 = t h e t o t a l p o p u l a t i o n o f a l l communit ies w i t h i n 15 m i l e s o f t he c o n s t r u c t i o n s i t e .

I t em 2 Dis tance f rom the c o n s t r u c t i o n s i t e . Using a s t a t e highway map,

c a l c u l a t e t he d i s tance ( i n highway m i l e s ) between each community

and t h e c o n s t r u c t i o n s i t e . Def ine t h e f o l l o w i n g v a r i a b l e :

l l ~ o r t he purposes o f t h i s a n a l y s i s communit ies a re de f i ned as those w i t h t h e i r own pos t o f f i c e s ( i .e., z i p codes). For ve ry l a r g e communi- t i e s w i t h more than one z i p code, use o n l y one z i p code as a community i d e n t i f i e r .

12u.s. Bureau o f t h e Census. Census o f P o ~ u l a t i o n . C h a r a c t e r i s t i c s o f t h e Populat ion.

DIST = d is tance ( i n highway m i les ) between the community and the cons t ruc t i on s i t e .

I tem 3 Populat ion o f a l l count ies i n t he l o c a l impact area. These data

are ava i l ab le i n Census pub l ica t ions . l3 Def ine the fo l l ow ing

var iab le :

LPOP = t o t a l popu la t ion o f a l l count ies i n the l o c a l impact area.

I tem 4 Number o f vacant housing un i t s , t o t a l number o f housing u n i t s

and nurr~ber o f mobi le homes i n the l o c a l impact area. I f recent

in fo rmat ion i s no t ava i l ab le f rom a l o c a l source, ob ta in the

most recent Census data.14 Def ine the f o l l o w i n g var iab les :

VACRT = t o t a l number o f vacant u n i t s d i v ided by the t o t a l number o f housing u n i t s i n the l o c a l impact area m u l t i p l i e d by 100.

PCMH = t o t a l number o f mobi le homes i n the l o c a l impact area d i v ided by the t o t a l popu la t ion o f a l l coun- t i e s i n the l o c a l impact area (LPOP as defined above).

I tem 5 To ta l number o f persons employed i n r e t a i l t rade i n the l o c a l

impact area. This in fo rmat ion can be obtained from the County

Business Pat terns publ ished by the U.S. Bureau o f t he Census.

Compute the f o l l o w i n g var iab le :

PCRET = t o t a l number o f persons employed i n r e t a i l t rade i n the count ies o f the l o c a l impact area d i v ided by the populat ion o f t he l o c a l impact area.

RET = PCRET x (POP15/1000). (Note: This va r i ab le i s a proxy measure o f r e t a i l employment w i t h i n 15 m i les o f t he cons t ruc t i on s i t e . )

1 3 ~ a t a f o r Census years are contained i n U.S. Bureau o f t he Census, Census of Populat ion, Charac te r i s t i cs o f t he Populat ion. Populat ion est imates f o r non-census years are contained i n t he U.S. Bureau o f t he Census, Current P o ~ u l a t i o n R e ~ o r t s . Ser ies P-25 and P-26.

1 4 ~ u r e a u o f t he Census, Census o f Housing, Charac te r i s t i cs f o r States, C i t i e s and Counties.

I tem 6 Composition of movers. Using i n fo rma t i on regard ing the number o f

movers a t the cons t ruc t i on s i t e obta ined i n Step 1, c a l c u l a t e t h e

f o l l o w i n g va r i ab les :

NMOVE = t h e t o t a l number o f movers d i v i ded by 100.

PS = t he number o f scarce movers d i v i d e d by the t o t a l number o f movers.

PO = t he number o f common and abundant movers d i v i ded by t h e t o t a l number o f movers.

I t em 7 Locat ion o f t h e nearest SMSA. l5 Using a s t a t e highway map

c a l c u l a t e t he d is tance ( i n highway m i l e s ) f rom the cons t ruc t i on

s i t e t o the c i t y l i m i t s o f t h e c e n t r a l c i t y o f t h e nearest SMSA.

Ca lcu la te t he f o l l o w i n g va r i ab le :

DSMSA = d is tance o f t he cons t ruc t i on s i t e f rom the nearest SMSA d i v ided by 100.

I tem 8 Region. Def ine a reg iona l dummy v a r i a b l e as fo l l ows :

REG = 1, i f t h e s i t e i s loca ted i n t he South (as de f ined by U.S. Census reg ions) .

0, otherwise.

Step 4 - Ca lcu la te t he d is tance exponent.

Ca lcu la te t he d is tance exponent as f o l lows:

EXP = .917

+ .053 x VACRT

+ 6.399 x PCMH

+ .094 x RET

+ .019 x NMOVE

+ .433 x PS

+ .312 x PO

- .083 x DSMSA

- . I33 x REG

1 5 ~ h e Standard Me t ropo l i t an S t a t i s t i c a l Area (SMSA) i s an area speci- f i e d by t h e U.S. Bureau o f t h e Census and i s used t o designate l a r g e met ropo l i t an areas.

I Step 5 - Aggregate all communities within 10 miles of the site. 1 , - For the purpose of applying the gravity model equation, combine all com- I I munities within 10 miles of the site to create one community. Add the popula- 1 # . tion of all communities and assign the community a distance of 5 miles.

I Step 6 - Apply gravity model equation. I

Calculate a proportion (Pi) for each community, treating a1 1 cornrnuni ties I I

within 10 miles as a single community.

Pi = .055 x POP .3 *'

Step 7 - Distribute the estimated proportions to communities within 10 miles. Distribute the proportion computed for all communities within 10 miles of

the site to individual communities within 10 miles of the construction site as follows:

Pj = POP .385 . P

cpop '385

where: P = the proportion for all communities within a 10-mile

radius of the site as calculated in Step 6.

Step 8 - Normalize the estimated proportions. Normalize the proportions calculated for all communities located more than

10 miles from the site (as calculated in Step 6) and the proportions calcu-

lated for all communities within 10 miles of the site (as calculated in Step 7) to sum to one. Compute the proportion of movers in each individual com-

munity as follows:

Step 9 - Calculate number of movers in each community. Multiply PROPi as calculated in Step 8 and total number of movers at the

site to obtain the number of movers who can be expected to locate in each

commun i ty .

VALIDITY OF THE FORECASTING PROCEDURES 1

Several steps were taken t o e s t a b l i s h the v a l i d i t y o f the fo recas t i ng * I

I

procedures described i n t h i s chapter. A more d e t a i l e d d iscussion o f t he I

v a l i d i t y o f the fo recas t i ng procedures i s presented i n Appendix E. I n t h i s I

sec t ion we present a b r i e f summary o f t he evidence which suggests t h a t one can I

I

expect t he proposed procedures t o perform w e l l a t f u t u r e cons t ruc t i on s i t e s . I

M igrant Propor t ions

The v a l i d i t y o f t he proposed migrant p ropor t ion fo recas t i ng procedures i s

supported by the f o l l o w i n g f o u r fea tures o f the est imated equations:

F i r s t , a l a rge p ropo r t i on o f t he observed v a r i a t i o n i n c r a f t - s p e c i f i c

migrant p ropor t ions i s expla ined by the est imated equations under-

l y i n g the fo recas t i ng procedures (71 percent i n the case o f t he con-

s t r u c t i o n worker equat ion and 85 percent i n the case o f t he noncon-

s t r u c t i o n worker equat ion). This imp l ies a c o r r e l a t i o n between pre-

d i c t e d and actual migrant p ropor t ions o f .85 and .92 f o r cons t ruc t i on

and nonconstruct ion c r a f t groups, respec t i ve l y . Moreover, s ince we

are i n t e r e s t e d i n p r e d i c t i n g o v e r a l l migrant p ropor t ions and n o t

migrant p ropor t ions among workers i n each c r a f t group, one can expect

t he o v e r a l l migrant p ropo r t i on pred ic ted values t o be even more h igh-

l y co r re la ted than i nd i ca ted by the est imated equations. e Second, the magnitude, s ign and s i g n i f i c a n c e o f t he c o e f f i c i e n t e s t i -

mates were found t o be s tab le w i t h respect t o ( 1 ) i n c l u s i o n and

exc lus ion o f c o n t r o l var iab les i n the equations, and (2 ) es t ima t ing

t h e equations us ing subsets o f t he data, i.e., es t ima t ing the equa-

t i o n s excluding a l l observat ion from a s i n g l e s i t e . The remarkable

consistency i n parameter est imates which we observed i n the var ious

est imated equations c l e a r l y demonstrates the robustness o f t h e e s t i -

mated model and thus prov ides f u r t h e r evidence o f t h e va l i d i t y o f t h e

fo recas t i ng procedures.

e Third, a narrow range o f mean square values o f t he expla ined va r ia-

t i o n (4.28 t o 5.29 f o r cons t ruc t i on and 6.36 t o 6.99 f o r nonconstruc-

t i o n ) and res idua ls (.274 t o .347 f o r cons t ruc t i on and . I26 t o . I73

f o r nonconstruct ion) i s observed when equations est imated w i t h a l l

s i t e s inc luded and equations est imated excluding a l l observat ions

f rom a s i n g l e s i t e are compared. This i nd i ca tes t h a t t he re i s sys-

temat ic v a r i a t i o n i n migrant p ropor t ions o f c r a f t s bo th w i t h i n and

across s i t e s , and t h a t t h e proposed s p e c i f i c a t i o n o f t h e model does a

very good j o b o f c o n s i s t e n t l y c a p t u r i n g about t h e same amount o f t h e

v a r i a t i o n across t h e var ious subsets o f data.

F i n a l l y , t h e d i f f e r e n c e between ac tua l and p r e d i c t e d o v e r a l l m ig ran t

p ropo r t i ons was found t o be r e l a t i v e l y smal l . The mean abso lu te

d e v i a t i o n and t h e root-mean-square d e v i a t i o n across t h e 21 surveys

inc luded i n our ana l ys i s were 2.9 and 3.7 percentage po in t s , respec-

t i v e l y . Th i s suggests t h a t a r e l a t i v e l y h i gh degree o f p r e d i c t i o n

accuracy i s assoc ia ted w i t h t h e proposed f o r e c a s t i n g methodology.

Personal and Household C h a r a c t e r i s t i c s o f Movers

The proposed procedures f o r p r e d i c t i n g personal and household charac te r-

i s t i c s o f movers were n o t based upon est imated equat ions. As a r e s u l t , t h e

o n l y evidence o f t h e v a l i d i t y o f t h e proposed f o r e c a s t i n g procedures l i e s i n a

comparison of p red i c ted and ac tua l values among t h e s i t e s inc luded i n our

ana lys is . The mean abso lu te d e v i a t i o n between ac tua l and p r e d i c t e d values and

t h e assoc ia ted root-mean-square d e v i a t i o n f o r t h e var ious v a r i a b l e s o f i n t e r -

e s t a re as f o l l o w s : 16

Mean absol u t e d e v i a t i o n

Root-mean-square d e v i a t i o n

Re loca t i on o f Dependents 5.4

Type o f Housing - House - Mob i le home - Apartment - Other

M a r i t a l S ta tus 3.4

Given t h a t these v a r i a b l e s are o f secondary importance i n socioeconomic impact

assessments, these expected p r e d i c t i o n e r r o r s a re n o t l i k e l y t o be o f major

importance.

16~ecause our examinat ion o f i n t e n t i o n t o remain i n t he area was based upon o n l y 4 surveys, l i t t l e can be concluded rega rd ing t h e v a l i d i t y o f t h e f o r e - c a s t i n g procedures.

Res iden t i a l Loca t i on

The v a l i d i t y of t h e proposed r e s i d e n t i a l l o c a t i o n f o r e c a s t i n g procedures

i s supported by t h e f o l l o w i n g f ea tu res o f t h e es t imated equat ions:

F i r s t , approximatelyc60 percen t o f t h e observed v a r i a t i o n i n r e s i -

d e n t i a l l o c a t i o n p a t t e r n s across t h e t e n s i t e s i nc l uded i n our ana l-

y s i s i s exp la ined by t he est imated equat ion u n d e r l y i n g t h e f o recas t -

i n g procedures. I n a d d i t i o n , t h e s ign, s i g n i f i c a n c e and magnitude o f

t h e c o e f f i c i e n t est imates were found t o be s t a b l e w i t h respec t t o t h e

i n c l u s i o n and exc lus ion o f va r ious c o n t r o l v a r i a b l e s and a l so when

a l l communit ies assoc ia ted w i t h s i n g l e s i t e s were excluded f rom t h e

regress ion .

Second, t h e range o f t h e mean square o f t h e exp la ined v a r i a t i o n

(which ranged f rom 102.29 t o 109.95) and t h e mean square o f t h e r e -

s i d u a l (which ranged f rom .860 t o .880) o f t h e va r i ous equat ions- - the

equat ion es t imated w i t h a l l s i t e s inc luded and t h e equat ions e s t i -

mated i n which a l l observa t ions f rom s i n g l e s i t e s were excluded--was

sma l l . The cons is tency, s t a b i l i t y and robustness o f t h e es t imated

equat ion a l l serve t o inc rease our conf idence i n t he v a l i d i t y o f

these f o r e c a s t i n g procedures.

0 F i n a l l y , t h e d i f f e r e n c e between t h e ac tua l and p r e d i c t e d p r o p o r t i o n s

o f movers l i v i n g w i t h i n f i v e - m i l e i n t e r v a l s o f t h e s i t e was r e l a -

t i v e l y smal l f o r most d i s t ance bands. The g e n e r a l i z a b i l i t y of t h e

est imated. equat ion would, no doubt, have been improved w i t h t h e

i n c l u s i o n o f a g rea te r number o f s i t e s i n t he ana l ys i s . However, t he

proposed f o r e c a s t i n g procedures represen t a g r e a t improvement over

procedures which t o da te have been a v a i l a b l e f o r f o r e c a s t i n g res iden-

t i a l l o c a t i o n p a t t e r n s o f i n m i g r a t i n g workers a t nuc lea r power p l a n t

c o n s t r u c t i o n s i t e s .

REFERENCES

Chalmers, J. A. "The Role o f Spa t i a l Re la t ionsh ips i n Assessing t h e Socia l and Economic Impacts o f Large-Scale Construct ion Pro jec ts . " Natura l Resources Journal, 17 : 2 (Ap r i 1, 1977), pp. 209-222.

Inventory of Power P lan ts i n the Uni ted States. U. S. Department o f Energy, O f f i c e o f U t i 1 i t y P r o j e c t Operations, December, 1977.

Mountain West Research, Inc . Construct ion Worker P r o f i l e , F i n a l Report. Prepared f o r the Old West Regional Commission, 1975.

Murdock, S.,H.; Wieland, J. S:; and L e i s t r i t z , F. L. "An Assessment o f the Grav i t y Model f o r P r e d i c t i n g Community Sett lement Pat terns i n Rural Energy-Impacted Areas i n the West." Land Economics, 54:4 (9178), pp. 461-471.

Nuclear Reactors B u i l t . Beina B u i l t . o r Planned i n the Uni ted States as o une 30, 0 Center, 1978.

Rand McNal ly, Commercial A t l a s and Market ing Guide, 1979.

Stenehjem, E. J. Summary Descr ip t ion o f SEAM: The Socia l and Economic Assessment Model. Argonne Nat ional Laboratory, Energy and Environmental Systems D iv i s ion , A p r i l , 1978.

U.S. Bureau o f t he Census. Census o f Housing: 1970, Volume I , Housing Charac te r i s t i cs f o r States, C i t i e s and Counties.

U.S. Bureau o f the Census. Census o f Populat ion: 1970, Volume I, Charac te r i s t i cs o f the Populat ion.

U.S. Bureau o f t he Census. County Business Pat terns.

U.S. Bureau o f t he Census. - Current Populat ion Reports. Series P-25 and P-26.

APPENDIX A

THE DATA COLLECTION EFFORT

APPENDIX A

THE DATA COLLECTION EFFORT

Th is study examines labor f o r c e m ig ra t i on and r e s i d e n t i a l choice o f

workers a t nuclear power p l a n t cons t ruc t i on s i t e s . A very important p a r t

of t h i s study was the c o l l e c t i o n of considerable data f o r a l a rge number

of cons t ruc t i on s i t e s . Several types o f data were obtained. F i r s t , i t

was necessary t o ob ta in in fo rmat ion regarding the numbers o f workers who

moved t o the area t o work a t p a r t i c u l a r cons t ruc t i on s i t es , t h e i r i n ten-

t i o n t o remain i n the area beyond completion o f t he p ro jec t , l o c a t i o n o f

work week residence, type o f housing selected and personal and household

c h a r a c t e r i s t i c s o f movers.

The survey data which formed the bas is o f t h i s study inc luded 28

worker surveys which were conducted a t 13 d i f f e r e n t nuclear power p l a n t

cons t ruc t i on s i t e s . Surveys were conducted a t f o u r nuclear power p l a n t

cons t ruc t i on s i t e s s p e c i f i c a l l y f o r t h i s study. We were, however, able

t o increase the number o f s i t e s i n our ana lys is by i nc lud ing data from

s i m i l a r surveys which were conducted by u t i l i t i e s a t n ine add i t i ona l

s i t e s .

I n add i t i on t o these survey data, considerable secondary data were

a lso co l lec ted . Numerous data sources were examined i n an e f fo r t t o

ob ta in var iab les which captured d i f f e rences i n the many f a c t o r s which

could i n f l uence workers' r e l o c a t i o n decis ions. The secondary data which

were c o l l e c t e d included pro jec ted c r a f t - s p e c i f i c labor requirement pro-

f i l e s , as we l l as numerous reg iona l and p r o j e c t c h a r a c t e r i s t i c s , f o r each

o f the s i t e s i n the study. These data were obtained from a number o f

sources, i nc lud ing c o l l e c t i v e barga in ing agreements, s t a t e agencies and

various publ ished sources.

This appendix presents a de ta i l ed d iscussion o f the data c o l l e c t i o n

e f f o r t . The d iscussion i s d i v ided i n t o 2 sect ions. The f i r s t sec t i on

describes the survey data and the second p a r t describes the secondary

data.

SURVEY DATA

The survey data used i n t h i s study inc lude the responses o f over

49,000 workers from 28 surveys conducted a t 13 d i f f e r e n t nuc lear power

p l a n t cons t ruc t i on s i t e s . The procedures which were used t o conduct

these surveys and the type o f in fo rmat ion c o l l e c t e d var ied somewhat

depending upon who conducted the survey.' The nature of these d i f f e r -

ences was minor, however, and i t was poss ib le t o generate data which were

consi s ten t across a1 1 surveys.

I n t h i s sec t i on we present a d e t a i l e d d iscussion o f t he survey data

co l l ec ted . The f o l l o w i n g t o p i c s are discussed: survey admin is t ra t ion ,

na ture o f t h e da ta co l lec ted , ex ten t o f v a r i a t i o n i n reg iona l and p r o j e c t

c h a r a c t e r i s t i c s , and prepara t ion o f the survey data f i l e s .

Survey Admin is t ra t ion

Conducting worker surveys a t l a r g e cons t ruc t i on p r o j e c t s i s n o t an

easy task. Several r a t h e r unique survey problems encountered a t l a r g e

cons t ruc t i on p r o j e c t s l i m i t the number o f v i ab le opt ions f o r survey

admin is t ra t ion . The cons t ruc t i on workforce i s genera l l y t rans ien t ; work

i s o f t e n temporary and the re may be a h igh turnover from one week t o the

next. As a r e s u l t , t he number o f workers i s no t constant, b u t r a t h e r

var ies from day t o day. I n add i t ion , the workforce i s q u i t e l a r g e and workers are dispersed over a very l a r g e cons t ruc t i on s i t e . F i n a l l y ,

names, addresses and occupations o f workers t y p i c a l l y are n o t a v a i l a b l e

t o i d e n t i f y t he popu la t ion i n quest ion.

Because o f the c r a f t - s p e c i f i c nature o f the analys is , ob ta in ing sur-

vey da ta from adequate numbers o f workers i n var ious c r a f t groups a t each

s i t e was very important t o t h i s study. We exercised extreme cau t i on i n

s e l e c t i n g the surveys t o be inc luded i n our data set . I n a d d i t i o n t o

conta in ing in fo rmat ion usefu l i n our analysis, a l l surveys were regarded

as acceptable i n several o ther respects. F i r s t , a census survey was

conducted a t each s i t e . Second, t h e survey procedures adopted allowed

l ~ o u r surveys were conducted by us. Three u t i l i t i e s were invo lved i n conduct ing the o ther surveys.

sufficient control over survey administration. Third, adequate response

rates were achieved. 1. Sampling Versus Census Surveys

The number of workers at a nuclear power plant construction site may

vary from 500 to 4,000 workers depending upon factors such as the number

of units being built and the stage of project completion. One might, therefore, conclude that surveying only a sample of workers on site would

be appropriate for most analyses. However, the transient nature of the

construction workforce and the limited information available prior to a

survey make the successful implementation of a sample survey extremely

difficult.

Even a simple random sample of workers is made difficult by the fact that it is generally not possible to identify the population from which

one might sample. Often there is a quite high turnover among workers

from one week to the next. In addition, the situation is further compli-

cated by the nature of the employment hierarchy at a construction site--

with many of the workers on site being hired by subcontractors.

Furthermore, because differences across crafts are important to the

analysis to be performed, it is important to survey adequate numbers of

workers from all major crafts represented at a site. Depending upon the

stage of project completion, some craft groups may be represented in rather small numbers at the time of the survey and it is important to

include adequate numbers of workers from these crafts in the sample.

This suggests that a stratified random sample would be appropriate.

This, however, would be difficult given the prior information necessary to draw a stratified sample. In most cases it is possible to obtain only

a crude estimate of the total number of workers expected to be on site at - a particular time. An accurate estimate of the number of workers by

craft is virtually impossible to obtain.

The difficulties in implementing a simple random sample--not to men-

tion the additional problems associated with a stratified sample--make a

census survey the only reasonable alternative. Indeed, given the viable

options for administering construction worker surveys which would insure

an adequate response rate, a census survey is both easier and less costly

to perform.

2. Survey Procedures -- Used Many of the standard survey administration procedures ( i .e., mai 1

surveys, telephone surveys, personal interviews) are not viable options

at large construction sites. The primary reason is that names,

addresses, and telephone numbers can not be easily obtained for workers

at most construction sites. In many cases, it is possible that no single

source of this information is maintained. Furthermore, even if such

information were available, the utility, prime contractors, or subcon-

tractors may not be willing to release the information because they con-

sider it to be too personal.

This difficulty in identifying individual workers considerably limits

the procedures which can be used in administering a worker survey at

large construction projects. Some form of group administration is the

most viable for successful implementation. Enclosing questionnaires with

paychecks, or distributing questionnaires at entries or exits might seem

to be acceptable options. However, such procedures do not provide ade-

quate control over survey administration and, as a result, would most

likely yield unacceptably low response rates.

The key to achieving a high response rate is to identify a procedure by which every worker at a site can be contacted either individually or

in a group. Two such procedures were used in administering the 28 surveys included in this study. The first procedure, which involved admin-

istering the surveys during regular safety meetings, was adopted at three

sites. The remaining surveys were administered by supervisors and fore-

men to their crews. The specific details of each of these methods are

provided below.

Safety meeting method. This method takes advantage of the safety

meetings which are required to be held at regular intervals at nuclear

power plant construction sites. At some sites safety meetings are held

weekly, with meetings scheduled for all crafts at the same time (occa-

sionally these meetings are held at a central location). At other sites

safety meetings are scheduled to be held at different times, on different

days, for different groups of workers. During these meeting workers meet

in small groups to discuss matters of safety under the supervision of a

foreman or safety supervisor. With the cooperation of the uti 1 ity and/or

prime contractor, these meetings provide an ideal situation in which to

conduct the survey.

In adopting this method, safety meetings were extended by 10 or 15 minutes and the survey questionnaires were distributed, completed and

collected at that time. Because the survey activity was so closely

monitored, and because the meetings involved all construction workers at

the site, this method generally produced very high response rates.

Office workers, however, typically do not participate in safety meet-

ings. As a result, when this method was used, alternate arrangements

were necessary to survey nonconstruction workers.

Supervisor method. This method takes advantage of the employment

hierarchy at a construction site. Workers are generally divided into

small crews of from 8 to 15 workers under a supervisor or foreman. This

supervisor method involves distributing questionnaires to subcontractors

and supervisors, who in turn distribute them to their foreman. Foremen

are then asked to administer the surveys to their crews at some conven-

ient time during the day--for example, during lunch or some other normal

break in work.

Adopting this method a1 lowed surveys to be administered to work crews scattered over a large construction site with little or no disruption of

work. However, successful implementation of this technique did require the cooperation and assistance of a large number of supervisors and fore-

men.

3. Response Rates Achieved

Many of the past attempts at conducting surveys of construction

workers have had only limited success. Old Mountain West, for example,

reported response rates ranging from a low of 14 percent to a high of 78 percent in their surveys of workers at 14 energy development project. 2

The average response rate among the 14 surveys was 50 percent. Simi-

larly, in surveys of 12 Bureau of Reclamation water development projects,

'~ountain West Research, Inc., Construction Worker Profile, Final Report, prepared for the Old West Regional Commission, 1915, p. 12.

response ra tes ranged from 21 t o 85 percent, w i t h an average response

r a t e of o n l y 52 percent. 3

The response ra tes achieved i n the 28 surveys inc luded i n t h i s study

were cons iderab ly h igher than response ra tes which have been achieved i n

cons t ruc t i on worker surveys i n pas t s tudies. The response ra tes ranged

from a low o f 60.2 percent t o a h igh o f 94.9 percent, w i t h an average

response r a t e o f approximately 81.5 percent. The response ra tes achieved

i n each o f t he 28 surveys inc luded i n t h i s study are presented i n Table

A- 3 .

Nature o f t he Data Co l lec ted

Since 28 surveys were conducted by several research groups us ing

d i f f e r e n t survey instruments, t he data c o l l e c t e d were n o t i d e n t i c a l f o r

a l l s i t e s . The survey instruments used i n the var ious surveys are i n -

cluded a t t he end o f t h i s appendix. However, desp i te the d i f f e r e n c e ~ i n

survey instruments, there was s u f f i c i e n t s i m i l a r i t y i n the in fo rmat ion

gathered i n these surveys t o address many issues important i n socio-

economic impact assessment.

The in fo rmat ion contained i n a l l 28 surveys was s u f f i c i e n t t o a l l ow

us t o address quest ions regarding:

a t he p ropo r t i on o f workers a t a s i t e who moved t o the area t o work a t the s i t e ;

a t he type o f housing i n which the movers l i v e ;

t he r e s i d e n t i a l l o c a t i o n pa t te rns o f both movers and nonmovers; and

a t he household composit ion (i.e., average f a m i l y s i z e and number o f school-age c h i l d r e n ) o f inmigra t i n g workers.

Considerably more in fo rmat ion was a v a i l a b l e f o r some s i t e s , which a1 lowed

us t o address a number o f o the r issues. These issues inc lude:

a t he i n t e n t i o n o f workers t o remain i n t he area;

a whether o r n o t workers main ta in a permanent residence elsewhere;

3 ~ . A. Chalmers, Bureau o f Reclamation Construct ion Worker Survey, Bureau o f Reclamation, Engineering and Research Center, October, 1977, p. 8.

m relocation of dependents; and

a demographic characteristics of nonmovers as well as movers.

The availability and nature of the data for the 28 surveys is summarized

in Table A-1. It might be noted that the 28 surveys contained in this data set do

not constitute a representative sample of all nuclear power plants under

construction in the United States. Indeed, even the choice of the four

sites surveyed by us was determined more by the willingness of utilities

to cooperate than by considerations of representative sampling. It

should, however, be recognized that representative sampling, while not

possible, was also not critical for the purposes of our study.

The ultimate goal of this study was to develop a forecasting method-

ology that could be applied to the future construction of nuclear power

plant projects. Since there is no basis to view the distribution of

existing generating plants as the best predictor of the location for

future power plants, it was far more important to include sites which

will be representative of plants that are likely to be constructed in the

future. Therefore, much more important to our study than obtaining a

representative sample of existing power plants, was capturing as much variation as possible along a number of different dimensions.

Extent of Variation in Regional and Project Characteristics

An attempt was made to improve the generalizability of our results by

including a sufficient number of surveys in our sample so as to incorpor-

ate as many relevant regional and project characteristics as possible in

our analysis. Seven key dimensions were identified as important to the study. While resource limitations did not permit us to observe every

possible variation in each dimension, the 28 surveys in our sample do

exhibit a wide range of variation in the various dimensions. The vari-

ations observed in our sample sites for each of these seven dimensions

are briefly described below and are summarized in Tables A-2 and A-3.

1. Regional Distribution

Preferably, a sample of nuclear power plant construction sites should

include sites from five different regions of the country: the Northeast,

'I-

7

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a

s 0 r=

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* -- a C,

E g 0 L

'I- 0

Crc

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5 +'

H

-7

V)

C,

c

W

-0

st

aJ

s 0

-r

ln

3

n

ln

U

-r

C,

V)

SF

L

aJ C,

U

L

0

S

rc

v,

ro

Lo

rL

o

+-

r+

Jm

>t

a>

E

LE

~~

E0

0a

JL

00

I

3

ma

u

+'

ln L

SC

,O

OQ

)

0

nL

ao

w

Er

n-

S

zE

-e

=

rc

st-

~J

RS

EU

-I

-E

EW

O

C,

a

U

0

.J

aJ

-U

~

~l

n>

rn

IJ

Fl

n>

E+

~W

I ln

aJ

aJ z

n

a

L a

=

0

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ln

L

0,

I

TZ

WE

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C,

a

C,

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=>

TABLE A-2

Regional and Power P l a n t P r o j e c t Charac te r i s t i cs

KEY :

BW = b o i l i n g water P r = p r i v a t e

PW = pressur ized water Pb = p u b l i c

PC = prime con t rac to r Un = union

U = u t i l i t y h i r e s workers Non = nonunion

I

US = u t i l i t y h i r e s subcontractor

UvlF = u t i l i t y workforce

S i t e

1

2

N = Nor th

t44 = Midwest

SE = Southeast

S = South

a Region was def ined as the area w i t h i n a 50 m i l e rad ius from the s i t e .

The d is tance t o the cen t ra l c i t y o f the nearest SMSA.

I

-0 L 0) 0 E U W EUC' m m . r

- w c a==)

Already Com-

p l e ted

1

E 0 .r

r \

6 s .r

Un

Un

P r o j e c t Charac te r i s t i cs

Under Con-

s ~ ~ ~ ~ -

1

2

2

2

2

3

2

1

2

3

2

3

2

5

-

-

3 1 - Un

Un

Non

Non

t4on

VI +I- .-E S- ' W 0- - ~ v , - r s cno

1080

1120

1 w

EW

SE

SE

SE

S

S

S

S

12

13 I

2

L Z m 0 E

L U W O OI u u * c m - m sssa

4

5

6

7

8

9

10

11

Regional

z .r u u -1 - .- K m

2

N

WtI

----- 2

2

Already Com-

p l e t e d

1

2

1120 1 Pw

-

1

u : D-

w CI

I-h

BW

PW

P r

Pr

Pr

P r

P r

P r

20

84

20

58

2 3

70

50

30

20

S ~ ~ ~ ~ -

1

3

1078

1180

1280

1153

829

1177

1233

US

US

WF

WF

WF

S

S

2 * .u-

"7

= 2 8E 5' "7

44

62

BGJ

PW

PW

PW

P W

1213

1067

1184

Pb

Pb

3 .,- 7

.#-

CI z u- 0

n 0

ch

P r

P r

1

1

3

1

2

0

2

1

2

PW

BW

PW

PLI

BU

w U L 0 'C

Y L

s C 0

VI s C,

m C, V)

PC

US

----- 5 3

55

Charac te r i s t i cs

VI 0 1 '4 -

a s - w m o a,.?'rC 7 -s'uzs 26 u .r .r U 3 N -

5.000 t o

10,000

0

4

3

3

3

3

1

0

0

1

PC I Un

Pb

P b

1

0

1

0

2

1

2

1

0

1

U

U

3

V) 'C .r .r 0 .r

Un

Un

U

U

O V 1 3 L Q

10,000 t o

25,000

2

0

1

2

-

25.000+

0

2

0

0

Un

Un 1

2

TABLE A-3

Survey Response Rates and the Stage of P r o j e c t Completion a t t he Time o f t h e Survey

a I n case o f m u l t i p l e surveys a t a s i t e , the surveys a re i d e n t i f i e d by numbers a f t e r a decimal p o i n t i n o rde r o f the dates on which the surveys were implemented.

Prec ise number o f workers cou ld n o t be determined.


Number a

1.0

2.0

3.0

4.0

5.1

5.2

6.0

7.0

8.0

9.1

9.2

9.3

9.4

10.1

10.2

10.3

11.1

11.2

11.3

11.4

12.1

12.2

12.3

12.4

13.1

13.2

13.3

13.4

Worker

Number On S i t e

1572

1641

1333

2364

1680

21 22

406

1993

2448

900

2200

3500

3834

2500

3200

21 00

11 00

2200

1600

2800

475

1700

2800

3439 b

b

3450

441 3

Response

Response Rate

88.4%

84.3%

85.2%

94.9%

91.3%

83.6%

83.3%

72.7%

90.5%

72.8%

61 .l%

60.2%

87.915

68.2%

80.0%

84.7%

76.6%

66.4%

68.1%

68.0%

84.6%

87.7%

88.8%

91 .O%

93.7%

86.4%

Stage of

Quarters Elapsed

12

11

9

16

18

25

4

10

30

3

7

12

15

13

19

28

6

13

21

3 1

1

7

14

20

1

3

5

7

Completion

Stage

Prepea k

Peak

Peak

Peak

Prepeak

Peak

Prepeak

Prepeak

Pos tpeak

Prepeak

Prepeak

Prepeak

Peak

Prepeak

Peak

Postpeak

Prepeak

Prepeak

Prepeak

Prepeak

Prepeak

Prepeak

Prepeak

Peak

Prepeak

Prepeak

Prepeak

Prepeak

the Midwest, the Southeast, the South, and the our sample of 13

sites included at least one site in each of these regions, with the

exception of the West. The seriousness of this omission will, of course, depend upon the extent to which the characteristics of western power

plant construction are not captured by the variation in the character-

istics of the plants in other regions. 5

2. Local Community Characteristics

Some power plants are built in relatively rural surroundings, while

others are located quite close to large population centers. In our 13 sites we were able to observe considerable variation in the number and

sizes of communities surrounding the site. For example, within a 25-mile

radius of the construction site, one site in our sample had three commun-

ities of 5,000 to 10,000 inhabitants, three communities of 10,000 to

25,000 inhabitants, and two communities of more than 25,000 inhabitants.

Another site in our sample had only one large community within 25 miles--

a community with a population of more than 25,000. Yet another site had

only two communities of 5,000 to 10,000 people. Alternatively one could consider the distance of the site from a major metropolitan area as the

dimension of relevance. The 13 sites in our sample showed considerable

variation in this respect. The distance of the site from the central

city of the nearest SMSA varies from 20 to 84 miles. 6

3. Stage of Project Completion

Our sample of 28 surveys included surveys conducted at different

stages of project completion. The surveys were conducted from 1 to 31

4~hese regions were defined somewhat arbitrari ly after considering the existing location of facilities, population distribution, regional growth and avai 1 ab i 1 i ty of a1 ternati ve sources of power.

5~hile it would have been preferable to include a site from the West, having been unable to do so should not limit the application of our findings to nuclear power plant construction in the West.

6 ~ h e Bureau of the Census uses the Standard Metropol itan Statistical Area (SMSA) to define metropolitan areas. Among the criteria used to define an SMSA is that the area must include at least one central city (or two contiguous cities) with 50,000 or more inhabitants.

quarters after construction began. However, number of quarters since

construction began may not be the best reflection of stage of project

completion. The primary problem with using this measure is that it is

not adjusted for factors such as seasonality or construction delays.

Once can instead define an alternative measure of stage of project com-

pletion using the profile of actual labor requirements and the most

recent projections of labor requirements for the remainder of the construction period. Based upon whether labor requirements were rising,

constant, or falling at the time of the survey, surveys can be classified

as either prepeak, peak or postpeak. Among the 28 surveys included in

our study 19 surveys were classified as prepeak, 7 as peak and only 2 as

postpeak. Moreover, in the case of 6 of the 13 sites, we were able to

obtain survey data at several points in time during plant construction.

4. Plant Characteristics

Both boiling water and pressurized water reactors were included in

our sample. The capacity of the individual units under construction did

not exhibit much variation, ranging from a low of 829 megawatts to a high

of 1280 megawatts. However, the number of units being built at the site

varied from a single unit to a maximum of three units.

5. Previous Power Plant Construction in the Area

A factor which could influence the migration of workers to a particular site is the number of other nuclear power plants which have already

been completed in the area prior to the construction of the project. Similarly, one might consider the effect of another power plant being

simultaneously constructed within 50 miles of the project. Among the 13

sample sites there are cases in which the power plant was the first one

to be constructed in the area and cases in which as many as five other

units had already been constructed in the area. Likewise, it is possible

to observe instances in which other nuclear plants were being built in

the same general area, as well as instances in which no other projects

were currently being built.

6. Utilities and Construction Contractors

Both public and private utilities were included in our sample. In

addition, the sample captured variation in construction contract arrange-

ments. The sample included sites in which the utility hired a prime

contractor. Also included were sites in which the utility was the prime

contractor, including cases in which the uti 1 ity hired subcontractors, as well as cases in which the utility hired construction workers directly. Another situation which was represented in our sample is the case in

which the utility retained its own construction workforce.

7. Extent of Unionization

Variation in the extent of construction worker unionization is likely

to affect the variables of interest in our study. Through sample sites

in the Northeast and the Midwest we included areas with the strongest

construction unions, and through sites in the South we included areas in

which union activity is relatively weak. The sample also contained non-

union sites, thereby capturing the full range of variation that one might

expect to observe along this important dimension.

Preparation of the Survey Data Files

Worker surveys were coded and keypunched.7 Computer files for each

data set were created and edited. Since seven different survey instru-

ments were used to collect the data, the cleaning and editing procedures

were specific to each survey instrument. The editing process included

the following general procedures:

(1 ) checking for inconsistencies and missing values; (2) el iminating inconsistent responses;

(3) inferring responses for missing values from available information;

( 4 ) checking for out-of-range values; and

( 5 ) supplying proper missing value codes.

The extent to which such cleaning and editing was necessary (or possible)

depended upon the length and complexity of the questionnaire.

7 ~ n the case of surveys conducted by others, procedures varied. In some instances the data were already coded and keypunched and we received the data on either computer cards or magnetic tape. In other cases questionnaires had not been coded and we received copies of the survey questionnaires. One utility had already coded surveys for movers but had not coded nonmover surveys.

Since the in fo rmat ion which was obtained from the d i f f e r e n t surveys

was no t i d e n t i c a l f o r a l l s i t e s , i t was necessary t o achieve compar-

a b i l i t y - - t o the ex ten t possible--across surveys i n our sample. This

inc luded the f o l l o w i n g tasks:

I n t he case o f t h ree surveys, conver t ing alpha p lace codes t o numeric p lace codes. This invo lved recoding the cur ren t , previous, and permanent r e s i d e n t i a l l oca t i ons f o r t he th ree d i f f e r e n t s i t e s .

e Recoding l o c a t i o n a l codes used by others were recoded t o make them comparable t o codes used by us.

e Other response categor ies were recoded t o make them comparable across a l l surveys ( i .e., c r a f t codes, housing types, number o f c h i l d r e n ) .

e The d is tance from the community o f residence t o the s i t e was ca l cu la ted f o r a l l surveys which d i d n o t request t h a t inforrna- t i o n . Since t h i s in fo rmat ion was considered t o be important t o our ana lys is o f r e s i d e n t i a l loca t ion , distances were a lso ca l cu la ted f o r a1 1 o ther s i t e s i n our sample.

SECONDARY DATA

I n add i t i on t o the survey data, considerable secondary da ta were a lso

obtained f o r t h i s study. These data were c o l l e c t e d from a number o f

d i f f e r e n t sources, i n c l u d i n g u t i l i t i e s and contractors, c o l l e c t i v e bar-

ga in ing agreements, s t a t e agencies and var ious publ ished sources. The secondary data which were c o l l e c t e d inc lude var iab les which r e f l e c t :

e income p o t e n t i a l associated w i t h employment a t the s i t e ;

c r a f t - s p e c i f i c labor f o r c e requirements;

a v a i l a b i l i t y o f labor i n t h e region;

competing demand f o r labor i n t he region;

popu la t ion and housing a v a i l a b i l i t y i n t he region; and

e var ious reg iona l and comnunity c h a r a c t e r i s t i c s .

A summary o f the p r o j e c t c h a r a c t e r i s t i c s and reg iona l and community char-

a c t e r i s t i c va r i ab les which were c o l l e c t e d f o r the study i s presented i n

Tables A-4 and A-5.

I n t h i s sec t ion we present a d e t a i l e d d iscussion o f t he secondary

data co l l ec ted . Th is inc ludes a d iscussion o f the problems encountered

in secondary da ta c o l l e c t i o n , as we l l as a desc r ip t i on of major da ta

sources and a summary o f var iab les c o l l e c t e d from the var ious sources.

TABLE A-4

A Sumnary o f Secondary Data Col lected

Pro jec t Character is t ics

Variable

1. Co l lec t i ve bargaining agreement provisions, by c r a f t

a. Hourly wage r a t e b. Overtime r a t e c. Fr inge benef i ts d. A v a i l a b i l i t y o f t r a v e l

a1 lowance

2 . Location o f h i r i n g h a l l o f the union loca l w i t h j u r i s d i c t i o n over the pro ject , by c r a f t

3. Q u a r t e r l y pre-construct ion labor requirement pro ject ions, by c r a f t

4. Q u a r t e r l y actual l abor u t i l i z a - t ion , by c r a f t

5. Q u a r t e r l y overtime hours, by c r a f t

6. Q u a r t e r l y mid-construct ion labor requirement pro ject ions, by c r a f t

7. Q u a r t e r l y 1 abor requirement p r o f i l e s , by c r a f t

8. Power p l a n t charac te r i s t i cs

a. Type o f p l a n t b. Size o f p l a n t (megawatts)

9. Other nuclear power p l a n t const ruct ion a c t i v i t y i n the reg ion

a. A1 ready completed b. Current ly under construc-

t i o n

10. Labor requirements a t o ther power p l a n t const ruct ion p ro jec ts

a. Wi th in 50-miles o f the s i t e

b. Wi th in 120-miles o f the s i t e

Period

1978

1978

Construct ion period

Startup t o survey date

Star tup t o survey date

Survey date t o p r o j e c t completion

Construct ion per iod

----

----

Construct ion per iod

Area

S i t e

S i t e

S i t e

S i t e

S i t e

S i t e

S i t e

S i t e

S i t e

S i t e

Source

Union c o l l e c t i v e bargaining agreements (union l o c a l s and u t i l i t i e s )

Union loca ls

U t i l i t i es /con t rac to rs

U t i l i t i e s / c o n t r a c t o r s



CLDS

Nuclear Reactors B u i l t , Being B u i l t o r Planned i n the United States as o f June 30, 1978 - Nuclear Reactors B u i l t , Being B u i l t o r Planned i n the United States as o f June 30, 1978

CLDS

TABLE A-5

A Sumnary of Secondary Data Collected

Regional and Community Character i s t i c s

Variables

1. Land a rea

2. Population c h a r a c t e r i s t i c s

a. Population

b. Percent urban

c. Population change

d. Net migrat ion

3. Total employment

4. C i v i l i a n l abor fo rce

5. Unempl oyment r a t e

Area

County

County Community

County

County

County

County

County

County

County

County

County

County

Peri od

1975

1970

1972, 1975

1971, 1973 1974, 1976

1977

1970

1970-1 975

1970-1 975

1970

1970

1971-1978

1970

1971 -1 978

1 Source

County and Ci ty Data Book, 1977

1970 Census of Populat ion, Rand- McNal l y , Commer- c i a l At las and Marketing Guide


Current Popul a- t i o n Reports, S e r i e s P-25 and P-26.

1970 Census of Populat ion

County and City Data Book, 1977




S t a t e employment agenciesa


S t a t e employment agenciesa

9 7

TABLE A-5 (cont. )

a ~ a t a not ava i l ab le from a l l s t a t e s f o r a l l years.

Variables

6. Employment a. Total b. Construction c. Retail t r ade d. Service

7. Per c ap i t a income

8. Contract construction payroll

9. Housing a v a i l a b i l i t y b

a. Total number of housing units

b. Total year-round housing units

c. Year-round housing un i t s i n one-unit s t r uc tu r e s

d. Owner-occupied un i t s e. Renter-occupied units f . Number of mobile homes and

t r a i 1 e r s g. Number of vacant units

10. Housing change

11. Number of one-person house- holds

12. Percent owner-occupied housing

13. Housing cos t b

a. Median value of owner- occupied housing

b. Median r en t

14. Distance t o s i t e

I

b ~ o u s i n g information was ava i l ab le only f o r communities w i t h 1000 o r more inhabi tants .

Period

1970-1 976 1 970-1 976 1 969-1 976 1969-1 976

1969-1 970

1969-1976

1970

1 960-1 970

1970

1970

1970

---- i

Area

County

County

County

County Community

County

County

County

County Community

Communi t y

Source

County Business Pat terns

Local Area Personal Income

County Business Pat terns

1970 Census of Housing,


1970 Census of Housing


County and City Data Book, 1977; 1970 Census of Housing

S t a t e highway maps

Problems Encountered in Secondary Data Collection

As in any major data collection effort, numerous problems were

encountered in the identification of possible data sources and in the

specification of variables to be collected. Perhaps the overriding prob-

lem in the collection of these secondary data was the need to obtain

comparable data for all sites included in the study. Considerable effort

was devoted to determining the availability of secondary data from vari-

ous local data sources. Visits were made to a number of state, regional,

county, and city offices in an attempt to obtain information about popu-

lation, employment, housing, and public services in the region surround-

ing each construction site. A number of publications were identified as

sources of some of the necessary information. Publications which we

obtained include population data books, unemployment figures, planning

reports, and Chamber of Commerce pub1 ications. However, the amount of

information available from local sources varied considerably from site to

site. In general, those sites which were located near large metropolitan

areas had much more data available than those sites located in more rural

areas.

In addition to the wide variation in the availability of data across

sites, these local data sources often differed with respect to the defin-

itions of variables reported. Often variables reported were similar, but not identical, for different sites. Or, different variables were

reported in different years for the same site. For example, housing availability in one year was reported as "total housing units available"

and in another year was reported as "vacancy rate."

Problems regarding the consistency of variable definitions also

extended to the labor requirement data which were obtained from utilities

and contractors. Some utilities reported employment as average number of

men per quarter, whereas in the case of other utilities employment was

reported in terms of total number of man-hours. Some utilities provided

quarterly data, while others provided monthly data. In order to use

these data it was first necessary for us to convert the variables to the

same units to achieve comparability across sites. In some instances

sufficient information was available for us to do this. In other cases

these data could not be made comparable. Thus, the problem of compar-

ability of data across sites made local data sources of limited value for

the purpose of this study. The construction of a nuclear power plant does not occur at a single

point in time, but rather extends over a period of several years. As a result, another problem which we encountered in secondary data collection

was the identification of the appropriate year or years for which the data were to be obtained. However, examination of potential data sources

revealed that in this respect one is again limited by the availability of data. Considerable data are available in census publications. Thus,

much more information was available for 1970 than for other years. In

some cases, such as with respect to housing data, recent information was

rather difficult to obtain. In other cases data were not readily available prior to 1970. Since project construction extends over a rather

long period of time; the choice of appropriate years for data collection

was not straightforward. In most cases we made an attempt to obtain data

for each year from 1970 through 1978. With the exception of only one or

two projects, this included the entire construction period (i .e., from

the year construction began through the year of the latest survey).

An additional factor which created problems in data collection was

that often data were not available at the desired level of disaggrega- tion. Much of the secondary data required for this study were desired at

the craft level. In certain cases, such as variables reflecting income

potential, labor requirements, and competing demand for labor, data were

available for various construction crafts. However, in other cases, such

as the availability of labor in the region, craft-specific variables were

more difficult to obtain.

Finally, in secondary data collection we were restricted with respect

to the regions for which data are reported. Data for small areas sur-

rounding the construction site were difficult, if not impossible, to

obtain. Data are more commonly reported at the county level. For the

purpose of secondary data collection, two different areas--termed the

local area and the region--were defined. We defined the local area to

include the county in which the site was located plus any other county

which contained a significant portion of the land area within 15 highway

miles of the project (i .e., 30 percent or more). In all cases the local area included only one or two counties. A larger region was also identified for each site. We defined the region to include all counties of

which half or more of the total land area was within a 50-mile radius of

the site. Data were collected at the county level, since most data are

reported at this level of aggregation, and variables were computed for

the local area and region of each site based on these county data. 8

Major Data Sources

Numerous sources were examined in an effort to obtain the necessary

data. Since the 13 construction sites included in our study are located

in six different states, the need to obtain consistent data for all sites

often restricted the data collection effort. As mentioned earlier, local

data sources were of limited value for the purpose of this study. Thus,

whenever possible we obtained data from federal agencies and publications

to allow for more inter-regional comparisons. The major sources of these

secondary data include utilities and contractors, the Construction Labor

Demand System, collective bargaining agreements, state employment agen-

cies, and other published sources. A brief description of each of these data sources and the types of data obtained from them is presented below.

1. Utilities and Contractors The utility, or the prime contractor in the case of some sites, was

identified as a likely source o f information regarding the labor requirements associated with power plant construction. Various data were

requested from each utility or prime contractor, including (1) quarterly

labor requirement projections by craft which were made prior to project

construction; (2) quarterly actual labor requirements by craft which had

been expended to date; and (3) quarterly labor requirement projections by

craft for the remainder of the construction period. We made an attempt

8~ata were collected for a total of 138 counties which includes 18 counties in the local impact area of the sites in our sample. Because of the close proximity of some of the sites in our sample, some counties are located in the region of more than one site.

to obtain these data from the utility or prime contractor at each of the 13 sites included in the study.

Unfortunately, there was some difficulty in obtaining these data from

all sites, making these data of limited value for the purpose of this

study. The problem was most serious in the case of pre-construction

projections. In several cases, these projections were made more than ten

years prior to the request, and consequently, these data were not readily

available for all sites. In other cases, pre-construction projections

were not disaggregated by craft or were available only on an annual

basis. Moreover, as a result of delays in the construction schedule,

those projections which were available were very poor indications of the

actual utilization of labor.

We did obtain actual craft-specific manpower requirements which had

been expended to date from utilities or contractors at all sites. Also,

with the exception of only two sites, recent labor requirement projec-

tions for the remainder of the construction period were obtained for each

site. However, differences in the way in which utilities provided these

manpower requirement data required that the figures be made comparable

for all sites. Monthly data, if provided, were aggregated to quarterly data. In most cases data were provided as average number of men per quarter. In other cases, however, total numbers of man-hours per quarter were obtained. In these instances, the average number of men was com-

puted by dividing the total number of man-hours by the constant 520 (8

hours per day x 65 working days per quarter). A comparison of the actual labor requirement profile and recent pro-

jections of employment for the remaining construction period provided an

indication of overall stage of project completion at the time of the

survey (i.e., surveys were classified as prepeak, peak or postpeak based

on increasing, constant or decreasing labor requirements). However, failure to obtain accurate and comparable labor requirement data from all

sites led us to the search for alternative sources of labor requirement

variables.

2. Construction Labor Demand System

The Construction Labor Demand System was identified as an alternate

source of labor requirement data for all 13 sites included in this

study. The Construction Labor Demand System (CLDS) is a Department of Labor program for estimating on-site labor requirements for the construc-

tion of current, planned, or forecasted energy development projects in the United States. The CLDS data provide estimated manpower requirements associated with any construction project by month and year for 29 construction craft groups. These estimated manpower requirements are based upon typical manpower utilization for the size and type of project, and are updated on a regular basis using information regarding the actual utilization of labor as provided by utilities.

We obtained monthly craft-specific labor requirements from the CLDS for all 13 nuclear power plant construction projects included in the study. Based upon these data, quarterly labor requirement profiles were constructed for seven major construction crfts at each construction site. We then used these craft-specific labor requirement profiles to derive several labor requirement variables in an attempt to capture differences in the nature of the demand for labor for various craft groups ( i .e., total number of man-hours projected, peak employment, duration of peak employment). Additional 1 abor requirement variables were defined in an effort to capture differences in the relative attractiveness associated with employment at the construction site (i.e., the expected con- tinui ty of employment, the expected duration of employment, the expected growth of employment opportunities at the time of the survey).

In addition, we obtained monthly craft-specific labor requirements for all other power plant construction projects (nuclear as well as non- nuclear) simultaneously under construction within a 120-mile radius of each site. These data were obtained in an attempt to capture the competing demand for labor in the area surrounding the construction site. Annual labor requirements for each craft group at all other competing construction projects were computed based upon the CLDS data. We then used these data to define variables reflecting the concurrent demand for

labor within a 50-mile and a 120-mile radius of the site, as well as

variables reflecting the change in the concurrent demand for labor over the period of construction.

3. Collective Bargaining Agreements Collective bargaining agreements were obtained for all major con-

struction crafts for the union locals with jurisdiction over each proj-

ect. There is considerable variation in the types of provisions con-

tained in collective bargaining agreements; however, agreements typically

include provisions specifying craft and territorial jurisdictions, rate

of compensation, union referral and hiring practices, normal work hours,

holidays, and various working conditions. Many provisions, such as union

referral and hiring practices, are difficult to quantify and therefore

could not be included in the analysis. The collective bargaining agree-

ments were useful in providing several variables which reflect the income

potential associated with employment at a particular site for each craft

group. The income potential variables which we extracted from the col-

lective bargaining agreements include: (a) hourly wage rate; (b) over-

time wage rate; (c) value of fringe benefits paid per hour worked; and

(d) inclusion of a transportation a1 lowance. In addition, we computed

the distance from the construction site to the hiring hall of the union

local with jurisdiction over the project for each craft at each site.

4. State Employment Agencies

Considerable effort was devoted to obtaining data regarding the

availability of labor within commuting distance of the construction

site. Union locals are, of course, the most logical source of such

data. Unfortunately, unions are often rather reluctant to provide infor-

mation regarding union membership and, as a result, it was necessary to pursue alternate sources of these data. While population could be used

as a proxy for the availability of labor, information regarding the size

of the civilian labor force and the unemployment rate were viewed as

preferable variables. Indeed, perhaps even more desirable for this par-

ticular study are data reflecting the size of the construction labor

force and the construction unemployment rate.

Unemployment rates were not available at the county level from fed-

eral sources for the years required. Therefore, we contacted various

state agencies ( i .e., Department of Labor, Employment Service, Department

of Employment Security) in an attempt to obtain data regarding the size

of the civilian labor force and unemployment rates for counties surround-

ing the construction site over the period of construction. Information

for 1970 was obtained from census data. With very few exceptions, state

employment agencies were able to provide this information for the period

1971 through 1978. Unemployment rates by industry, however, were not

available at the county level. Therefore, we estimated the construction

unemployment rate from the overall unemployment rate based upon a rela-

tionship derived from data at the state level.' Overall and construc-

tion unemployment rates for the local area and the region were calculated

for each year as a weighted average of the respective counties.

5. Other Published Sources

The regional characteristic variables were obtained from a variety of pub1 ished sources. Population data ( i .e., 1970 population, population

estimates for the years 1971 through 1978, population change between 1970

and 1975) and housing data (i.e., total number of housing units, number

of mobile homes, number of vacant units, percent owner-occupied units)

were obtained from various census publications. lo In addition, we

obtained the 1970 population of communities surrounding each site and

computed the distance of each community to the construction site. 11

Total employment, retail and service employment, construction employment,

and first quarter contract construction payroll were obtained from the

County Business patterns. l2 Per capita income was obtained from the

Local Area Personal ~ncome. l3 Data were collected at the county level

9 ~ e used ordinary least squares regression to estimate the re1 ationship between the construction unemployment rate and the overall unemployment rate using data at the state level (excluding Alaska) for the years from 1971 through 1976. We then used this estimated equation to predict construction unemployment rates for the local area and region for each site as a function of the overall unemployment rates for the respective areas.

1°u.s. Bureau of the Census, Census of Population: 1970, Vol . I, Characteristics of the Popu1ation;sus of Housing: 1970, Vol. I, Housing Characteristics for States, Cities, and Counties: U.S. Bureau ot the Census. Current Po~ulation Reports. Series P-25 and'p-26; U.S. Bureau of the census, countr and City bata ~ook, 1977.

llu.s. Bureau of the Census, Census of Population, - cit.; Rand- McNally, Commercial Atlas and Marketing Guide, 1979.

12u.s. Bureau of the Census, County Business Patterns. ldlIepartment of Commerce, Bureau of Economic Analysis, Local Area Personal Income.

and aggregated for the local area and region. Housing variables, however, were computed only for the local area.

Other data sources which were used in this study include Nuclear * - Reactors Built, Being Built, or Planned in the United States as of June

30, 1978 and the Inventory of Power Plants in the United states. l4 These documents were used to obtain information regarding the type and size of the units under construction and the existence of other power plan construction projects already built, or under construction, in the region.

14nuclear Reactors Built, Being Built, or Planned in the United States as of June 30, 1918 (Oak Ridge: DOE Technical Information Cent-8); Inventory of Power Plants in the United States, U.S. Department of Energy, Office o f Utility Project Operations, December, 1977.

REFERENCES

Chalmers, J. A. Bureau o f Reclamation Construct ion Worker Survey. Bureau o f Reclamation, Engineering and Research Center, October, 1977. . ,

Department o f Commerce, Bureau o f Economic Analysis, Local Area Personal Income .

Inventory o f Power P lan ts i n the Uni ted States. U. S. Department o f tnergy, O f f i c e o f U t i l i t y P r o j e c t Operations, December, 1977.

Mountain West Research, Inc. Construct ion Worker P r o f i l e , F i n a l Report. Prepared f o r the Old West Regional Commission, 1975.

Nuclear Reactors B u i l t , Being B u i l t , o r Planned i n the Uni ted States as o f June 978. Oak Ridge, Tennessee: DOE Technical In fo rmat ion Center , %8:

Rand McNally, Commercial A t l as and Market ing Guide, 1979.

U.S. Bureau o f t he Census. Census o f Housing: 1970, Volume I, Housing Charac te r i s t i cs f o r States, C i t i e s and Counties.

U.S. Bureau o f t he Census. Census o f Populat ion: 1970, Volume I, Charac te r i s t i cs o f t he Populat ion.

U.S. Bureau o f t he Census. County and City Data Book, 1977. Washington, D.C.: U.S. Government P r i n t i n g Of f i ce , 1918.

U.S. Bureau o f t he Census. County Business Patterns.

U.S. Bureau o f t he Census. Current Populat ion Reports. Ser ies P-25 and P-26.

Survey Instrument f o r Surveys 1 .0 , 2.0, 8.0 and 9.4

1. WHAT IS YOUR OCCUPATION? 01 q Boilermaker 02 0 Bricklayer 03 0 Carpenter 04 0 Cement Mason 05 0 Electrician 06 0 Insulator/Asbestos Worker 07 0 Ironworker

(Please check the one box which best describes your job) 08 q Laborer 15 Clerical 09 0Millwright 16 IJ Engineer/Technician 10 Doperating Engineer 17 Inspector 11 OPainter 18 Management 12 OPipeISteamfiner 18 OSecurity 13 Sheetmetal Worker 20 0 Other (describe: 14 OTeamster 1

2. WHERE DO YOU LlVE DURING THE WORK WEEK? (city or town) (state) (zip)

3. WHERE IS THIS RESIDENCE LOCATED? 1 Inside City or Town Limits 2 q Outside City or Town Limits

4. WHICH ONE OF THE FOLLOWING BEST DESCRIBES THE RESIDENCE WHERE YOU LlVE WRING THE WORK WEEK? 1 Rented Single Family House 4 Clowned Single Family House 7 0 HotellMotel 2 0 Rented Apartment or Duplex 5 OOwned Apartment or Duplex 8 0 Rooming House 3 0 Rented Mobile ~ o r " e 6 Downed Mobile Home 8 0 Other (describe:

5. HOW MUCH DO YOU PAY EACH MONTH FOR THlS RESIDENCE IN RENTOR MORTGAGE? (Including lot rental for mobile home)

1 O N o Cash Payment 3 0$100 to $149 5 $200 to $249 2 O $ l to $99 4 O$150to$199 6 0 $250 to $299

7 0 $300 or more

6. HOW MANY BEDROOMS DOES THlS RESIDENCE HAVE?

7. WHICH OF THE FOLLOWING FACTORS WERE THE MOST IMPORTANT IN CHOOSING THlS RESIDENCE? (Check all that apply)

Close to Work Osh~ppingfSe~ices Available Nearby Low Taxes Recreational Opportunities

0 Cost of Housing Overall Community Attractiveness Housing Availability Other (describe:

0 Quality or Location of Schools )

8. HOW FAR IS THIS RESIDENCE FROM THE JOB-SITE? In Miles In Minutes

9. HOW DO YOU USUALLY GET TO WORK? 1 Drive Alone 2 0 Drive in Personally Arranged Carpool

3 0 Drive in Union or Project Arranged Carpool 4 0 Other (describe: 1

10. DID YOU MOVE TO THIS RESIDENCE TO WORK ON YOUR JOB AT THIS SITE? 1 Yes 2 0 No

E S , (A) WHERE DID YOU LlVE BEFORE THlS JOB? (city or town) (state) (zip)

(0) DID YOU OWN YOUR FORMER RESIDENCE? 1 Yes 2 No (C) DO YOU STILL OWN THAT RESIDENCE? 1 q Yes 2 q No

11. HOW MANY TIMES IN THE PAST FIVE YEARS HAVE YOU MOVED TO A NEW TOWN TO TAKE A NEW JOB?

12. DO YOU PLAN TO REMAIN IN THlS TOWN OR IMMEDIATE AREA AT LEAST AS LONG AS ACCEPTABLE EMPLOYMENT IS AVAILABLE AT THIS JOB SITE? 1 0 Yes 2 q NO

13. DO YOU PLAN TO REMAIN IN THIS TOWN OR IMMEDIATE AREA BEYOND COMPLETION OF -rHIs PROJECT IF ACCEPT- ABLE EMPLOYMENT IS AVAILABLE IN THE AREA? 1 0 Yes 2 0 No

14. DO YOU MAINTAIN A PERMANENT RESIDENCE IN ADDITION TO THE RESIDENCE IN WHICH YOU LlVE DURING THE WORK WEEK? 1 0 Yes 2 0 No

IF YES. (A) WHERE IS THlS RESIDENCE LOCATED? - (city or town) (state) (zip)

(B) HOW MANY TIMES A MONTH (on warage) DO YOU TRAVEL TO THlS RESIDENCE?

15. WHAT IS YOUR MARITAL STATUS? 1 O Married 2 Single, Separated. Divorced, Widowed

IF MARRIED, (A) IS YOUR SPOUSE CURRENTLY EMPLOYED? 1 Yes 2 q No (B) IF YOUR SPOUSE IS UNEMPLOYED, IS

SHE /HE LOOKING FOR WORK7 l O Y e s 2 0 N o

16. HOW MANY CHILDREN DO YOU HAVE IN THE FOLLOWING AGE GROUPS? (Write in "0" if None) (a) 0-4 Years (preschool) (c) 13-18 Years (Grades 7-12) (b) 5-12 Years [Grades K-6) (dl Over 18 Years of age

17. WlTH WHOM DO YOU LlVE DURING THE WORK WEEK? 1 q Live Alone 3 0 Roommate [s) - How many? 2 Spouse andlor Dependents 4 Other IF NOT LIVING WlTH YOUR SPOUSE AND DEPENDENTS, DO YOU INTEND TO LOCATE THEM HERE?

1 0 Yes 2 No 3 Have No Family

18. SEX: 1 O Male 2 q Female

19. AGE:

20. YEARS OF SCHOOL COMPLETED:

21. WHAT IS YOUR TOTAL ANNUAL FAMILY INCOME FROM ALL SOURCES (before taxes)? (Check the box beside the category which best describes your income)

1 Less than $15,000 3 $20.000 - $24.999 5 q $30,000 or more 2 0 $1 5,OW - $19.999 4 D $25,000 - $29,999

22. ARE YOU A MEMBER OF A UNION? 1 q Yes 2 0 No

-S. (A) HOW LONG (in months and yean) HAVE YOU BEEN A MEMBER OF THE UNION LOCAL WlTH JURIS- DICTION OVER THlS PROJECT: (Place a "0" in the blank if you have not transferred your membership to this local.) /

(Years) (Months)

(B) DO YOU BELONG TO THE PREFERRED UNION HIRING HALL GROUP FOR JOB REFERRAL? 1 Yes 2 No

(C) WERE YOU INFORMED OF EMPLOYMENT ON THlS PROJECT BY THE BUSINESS REPRESENTATIVE OF EITHER THlS LOCAL OR YOUR PREVIOUS UNION LOCAL? 1 0 Yes 2 O N o

T L L y o u fo, yo,, rdopcdion!

Survey Instrument for Surveys 3.0, 4.0, and 12.4

1. Your Employer 's Name

2. Your age

3. Are you (p lease check) - s i n g l e - m a r r i e d - separated o r d i v o r c e d

4. I f mar r ied , number i n your f a m i l y ( i n c l u d i n g s e l f ) -

5. Number o f f a m i l y members l i v i n g w i t h you ( i n c l u d i n g s e l f ) -

6. Ages o f a l l your c h i l d r e n -, , , , , , , ,

7. Your Occupation (check one) :

O1 - Boilermaker O6 - B r i c k l a y e r 11 -- C l e r i c a l l5 - Carpenter 02 - Cement Mason 07 - E l e c t r i c i a n 12 - I n s u l a t o r l6 - I r o n Workei 03 - Laborer O8 - M i l l w r i g h t 13- Oper. Engr. l7 - P a i n t e r o4 - P i p e f i t t e r o9 - Plumber 14 - S e c u r i t y I 8 - Superv iso r 05 - Teamster 10 - Other

8. How l o n g have you worked a t t h i s j o b s i t e ? - y e a r s - months

9. How l o n g do you expect t o be a t t h i s j o b ( f r o m today)? - years - months

10. Where do you l i v e d u r i n g t h e work week? c i t y o r town s t a t e

11. D is tance f rom t h e j o b s i t e - ( m i l e s )

12. Average one-way d r i v i n g t ime - (minutes )

I s t h i s res idence - i n s i d e c i t y l i m i t s - o u t s i d e c i t y l i m i t s do n o t know?

How l o n g have you l i v e d a t t h i s res idence? - y e a r s - months

D i d you move t o t h i s res idence because o f your j o b a t t h i s s i t e ? - Yes - No

I f yes, f rom where d i d you move? c i t y o r town s t a t e

What t y p e o f res idence i s t h i s ? s i n g l e family-owned s i n g l e f a m i l y - r e n t e d r e n t a l apartment - h o t m o t e l - m o b i l e homep- rooming house

Do you share t h i s res idence w i t h anyone who i s NOT a member o f y o u r f a m i l y ? Yes - No

Are any o f those you share a res idence w i t h employed a t t h i s j o b s i t e ? - Yes - No

I f yes, how many?

How do you most o f t e n g e t t o work? - d r i v e a lone d r i v e i n carpool - o t h e r nurr~ber i n pool

Do you m a i n t a i n a p r i m a r y res idence besides t h e one l i s t e d above? - Yes - No

I F YES, ANSWER REMAINING QUESTIONS--IF NO, STOP HERE

I f Yes, where i s i t l o c a t e d ? c i t y o r town s t a t e

Approximate d i s t a n c e f rom t h e j o b s i t e ? m i l e s

25. Number o f f a m i l y members l i v i n g a t t h i s res idence?

26. What t ype o f res idence i s t h i s ? s i n g l e family-owned - s i n g l e f a m i l y - r e n t e d r e n t a l apar tment - mobi lehome - o t h e r

27. How o f t e n do you t r a v e l t o and f rom t h i s res idence? - on weekends - more o f t e n every o t h e r weekend - o'ther

28. How long have you ma in ta ined t h i s res idence? - y e a r s - months

29. W i l l you move back t o t h i s res idence when y o u r j o b here i s completed? Yes - N o

THANKS FOR YOUR COOPERATION

Survey Instrument for Survey 5.1

Personal Charac te r i s t i cs

2. M a r i t a l Status ( c f r c l e one): Stngle Marr ied Divorced/Separated Widow(er)

3. Age: - 4. Current Address:

C i t y State County

Township

5. I c u r r e n t l y l i v e : - inside c i t y o r town l i m i t s - i n a developed area outs ide c i t y l i m i t s - i n a r u r a l area

6. What was your l a s t employment before working a t ****** Nuclear S ta t ion?

Have

Other Duke employment - Construct ion (other than Duke employment) - Manufacturing Other employment (self-employed, trade, sales, etc. ) Unemployed more than three months Other (school, m i l i t a r y service, unable t o work, e tc . School M i l i t a r y serv ice

you moved since you were employed f o r ****** Nuclear

Construct ion o r Manufacturing Another nuclear s t a t i o n

* 1

S ta t ion operat ion?

- Yes - No - Yes, Moved Across Country

I f NO, please go t o Question # lo.

I f YES, please answer Questions A through D below also.

8.1 What was your address before you moved:

C i t y State County

Towns h i p

9.1 How many people c u r r e n t l y l i v e w i t h you a t your new loca t ion? - 9.2 How many c h i l d r e n l i v i n g w i t h you a t your new loca t ion are:

- Not o l d enough t o go t o school - Going t o elementary, j u n i o r high, o r h igh school

L i v i n g a t home and going t o co l lege o r technica l school - L i v i n g a t home and working

9.3 Why d i d you choose your new locat ion:

Close t o work - Q u a l i t y and loca t ion o f schools

Low taxes - Good recreat ion ava i l able

- Cost o f housing - Good shopping f a c i l i t i e s

- A v a i l a b i l i t y o f housing - Other (please l i s t )

More des i rab le area o r housing

9.4 W i l l you move when you f i n i s h working on t h i s p ro jec t? - Yes - No

10. How do you normally get t o work?

Your own car

Carpool

- Other (please l i s t )

- Motorcycle

11. How many mi les would you have t o d r i v e t o get t o work from your residence?

12. Current place o f residence:

A house

- An apartment o r duplex

- Mobile home o r t r a i l e r

- Other (please 1 i s t )

13. Which o f the below appl ies t o you?

I RENT MY HOME AND I PAY: - I OWN MY OWN HOME. I F I SOLD IT, I WOULD PROBABLY GET

- Less than $50.00 per month - Less than $15,000

- $50.00 t o $75.00 per month $15,000 t o $20,000

- $75.01 t o $125.00 per month - $20,000 t o $30,000

- $125.01 t o $175.00 per month - f 30,000 t o $40,000

- $175.01 t o $200.00 per month - More than $40,000

- $200.01 t o $250.00 per month

- More than $250.00 per month

14. P lant Code

Survey Instrument f o r Surveys 5 .2 , 6.0 and 7.0

SURVEY OF THE CONSTRUCTION FORCE AT ****** NUCLEAR STATION

(Please do NOT s i g n you r name.)

1. What i s you r age? - 2. What i s y o u r c u r r e n t address, where you no rma l l y s t a y d u r i n g t h e week?

C i t y S t a t e County

3. What was you r l a s t employment be fo re coming t o ******?

Other Duke employment - Const ruc t i on (not. w i t h Duke) - Manufactur ing - Unemployed - Other

4. Have you moved s ince be ing employed t o work a t ******? - Yes - No ( I f No, go t o ques t i on 9. I f Yes, go t o ques t i on 5 . )

5. What was you r address be fo re you moved?

C i t y S t a t e County

6. How many people c u r r e n t l y l i v e w i t h you a t you r new l o c a t i o n ? -

7. How many c h i l d r e n c u r r e n t l y l i v i n g w i t h you are:

Not o l d enough t o go t o school? - Going t o elementary, j u n i o r high, o r h i g h schoo l? -

8. Why d i d you choose you r new locati.on? L i s t i n o rde r (1, 2, 3, e t c . ) t h e reasons t h a t app l y t o you.

Close t o work. - Low taxes. - Cost o f housing.

A v a i l a b i 1 i t y o f housing Schools. - Recreat ion .

- Other (p lease 1 i s t ) .

9. How many m i l e s do you d r i v e one way each day t o work? -

10. What t y p e o f res idence do you no rma l l y s t a y i n d u r i n g t h e week?

House. Apartment. Mobi le home. Other.

17. I s your l o c a l res idence a f u l l - t i m e res idence ( 7 days a week)? - Yes - No

12. Are you i n a c a r poo l? - Yes No

Thank you f o r comple t ing t h i s ques t i onna i re . The survey w i l l a i d i n l i c e n s i n g f u t u r e p r o j e c t s .

Survey Ins t rument f o r Surveys 9.1, 9.2, 9.3, 10.3, 11.3, 11.4, 12.1, 12.2, 12.3, 13.1, 13.2, 13.3 and 13.4

SURVEY OF CONSTRUCTION PROJECT IMPACT

Large c o n s t r u c t i o n p r o j e c t s c r e a t e a need f o r more housing and schools near t h e c o n s t r u c t i o n s i t e . You a re requested t o p rov ide i n f o r m a t i o n f o r a TVA survey t o f i n d o u t more about these needs. Your coopera t ion i n f i l l i n g ou t t h e app rop r i a te p a r t s o f t h i s form w i l l be app rec ia ted and t h e i n f o r m a t i o n g i ven w i l l be kept comple te ly c o n f i d e n t i a l . Please r e t u r n t h e fo rm t o t h e person who handed i t t o you.

1. Name Age -

Job T i t l e Man No.

Annual Trades and Labor

2. Where d i d you l i v e be fo re beg inn ing work on t h i s p r o j e c t ?

C i t y S t a t e

3 . Where a r e you l i v i n g now?

C i t y S t a t e

CONTINUE WITH THE QUESTIONNAIRE ONLY I F YOU ANSWERED 2 AND 3 WITH DIFFERENT ANSWERS

Please check t h e i t e m which a p p l i e s t o you r case.

4. 1 am l i v i n g i n ( a ) a boardfng room , ( b ) an apartment , ( c ) a t r a i l e r -, ( d ) a house -.

5. I ( a ) o w n , ( b ) r e n t -. 6. I am l i v i n g i n t h e p r o j e c t area (a ) by myse l f , ( b ) w i t h roommates -,

( c ) w i t h my f a m i l y -. ANSWER THE NEXT QUESTION ONLY I F YOU ARE LIVING IN THE PROJECT AREA WITH YOUR FAMILY

7. I have c h i l d r e n l i v i n g w i t h me. Of these, t h e r e a re ( a ) - i n grade school ,m - i n h igh school , ( c ) - i n co l lege.

Survey Instrument for Surveys 10.1, 10.2, 11.1 and 11.2

SURVEY OF CONSTRUCTION PROJECT IMPACT

Large construct ion p ro jec ts create a need f o r more housing and schools near the construc- t i o n s i t e . You are requested t o provide in format ion f o r a TVA survey t o f i n d ou t more about these needs. Your cooperation i n f i l l i n g ou t the appropriate par ts o f t h i s form w i l l be appreciated and the in format ion given w i l l be kept completely c o n f i d e n t i a l . Please r e t u r n the form t o the person who handed i t t o you.

1 . Nanie Age

Job T i t l e Man No.

Annual Trades and Labor

2. Where d i d you l i v e before beginning work on t h i s p ro jec t? C i t y State

3. Where are you l i v i n g now? C i t y State

CONTINUE WITH THE QUESTIONNAIRE ONLY I F YOU ANSWERED 2 AND 3 WITH DIFFERENT ANSWERS

Please check the i tem which appl ies t o your case.

4. Are you l i v i n g i n (a) boarding room , ( b ) apartntent , ( c ) t r a i l e r -, (d) house ?

5. Do you (a) r e n t - o r (b) own ?

6. Are you l i v i n g i n the p r o j e c t area (a) by yourse l f , (b) w i t h roommates -, o r ( c ) w i t h your fami l y ?

ANSWER THE NEXT QUESTION ONLY I F YOU ARE LIVING IN THE PROJECT AREA WITH YOUR FAMILY

7. How many ch i ld ren are l i v i n g w i t h you ? O f these, how many are i n (a) grade school , (b) h igh school -, ( c ) co l lege -?

8. Would you p r e f e r t o l i v e i n another type o f housing i n t h i s p r o j e c t area? Yes - No

I f yes, what type o f housing would you p re fe r?

9. House (a) t o r e n t - o r (b) buy - 10. Apartment 11. T r a i l e r (a) r e n t - o r (b) buy - 12. Boarding room -

13. What prevents you from l i v i n g i n the type o f housing you p r e f e r i n the,area?

(a) Not ava i lab le - ( c ) Avai lab le but too f a r from work - (b) Avai lab le bu t costs too much - (d) Other reason -

APPENDIX B

CONSTRUCTION WORKER SURVEYS: A MEANS FOR SUCCESSFUL IMPLEMENTATION

APPENDIX B

CONSTRUCTION WORKER SURVEYS: A MEANS

FOR SUCCESSFUL IMPLEMENTATION

The eve r- i nc reas ing demand f o r energy has c rea ted a need t o c o n s t r u c t

l a r g e power p l an t s , i n c l u d i n g nuc lear power s t a t i o n s . These l a r g e p r o j -

e c t s r e q u i r e a r e l a t i v e l y l ong c o n s t r u c t i o n phase--approximately f i v e t o

t e n yea rs- - tha t p rov ides employment f o r 2,000 t o 4,000 workers du r i ng i t s

peak. T y p i c a l l y , these l a r g e power p r o j e c t s have been l oca ted i n r u r a l

surroundings, a t some d i s tance f rom areas w i t h l a r g e l abo r pools . The

employment o p p o r t u n i t i e s c rea ted by these c o n s t r u c t i o n p r o j e c t s o f t e n

b r i n g a sudden i n f l u x o f workers and t h e i r f a m i l i e s t o t he smal l communi-

t i e s near t h e c o n s t r u c t i o n s i t e .

The problem o f e s t i m a t i n g t he socioeconomic impacts o f i n m i g r a t i n g

workers on t h e l o c a l communit ies surrounding a c o n s t r u c t i o n s i t e i s be ing

addressed w i t h i nc reas ing frequency. Prev ious f o r e c a s t s o f popu la t i on

growth and r e s i d e n t i a l l o c a t i o n r e l a t e d t o nuc lea r power p l a n t cons t ruc-

t i o n have r a r e l y been accurate.' They have s u f f e r e d f rom a l ack o f

i n f o r m a t i o n rega rd ing t h e i n m i g r a t i n g workers and t h e i r cho ices o f r e s i -

d e n t i a l l o c a t i o n . The need f o r more accurate i n f o r m a t i o n t o serve as a

b a s i s f o r making f u t u r e p r e d i c t i o n s and f o r mon i t o r i ng socioeconomic

assessments i s q u i t e c l e a r . Th i s need has been recognized; r e c e n t l y ,

severa l a t tempts have been made t o conduct c o n s t r u c t i o n worker surveys a t

a number o f nuc lear power p l a n t c o n s t r u c t i o n s i t e s throughout the Un i ted

States.

l ~ h e Nat iona l Environmental Pol i c y Ac t r e q u i r e s t h a t a socioeconomic impact statement be prepared as p a r t o f t h e l i c e n s i n g process and t h a t these impacts be moni tored d u r i n g t h e p e r i o d o f cons t ruc t i on . Moreover, t h e impact assessments a re used as a bas i s f o r compensating communities f o r adverse impacts due t o t h e c o n s t r u c t i o n o f a power p l a n t .

or an e v a l u a t i o n o f socioeconomic impact s tud ies , see Socioeconomic Impacts: Nuclear Power S t a t i o n S i t i n g , Pol i c y Research Associates,tate Col lege, PA, 1977.

Many of t he past attempts a t conduct ing surveys o f cons t ruc t i on work-

e rs have had o n l y l i m i t e d success. This can, i n pa r t , be expla ined by

t h e unique nature of the survey problems encountered a t a l a rge construc-

t i o n s i t e . F i r s t , t he cons t ruc t i on workforce i s genera l l y t rans ien t ;

work i s of ten temporary and there may be a h igh turnover f rom one week t o

t h e next. Thus, t he number o f workers i s no t constant, b u t r a t h e r va r i es

from day t o day. Second, the workforce i s q u i t e l a r g e and workers are

dispersed over a very l a rge cons t ruc t i on s i t e . F i n a l l y , t h e names and

addresses o f the workers are no t u s u a l l y ava i l ab le t o de f i ne the popula-

t i o n i n quest ion. Consequently, t o i d e n t i f y a " representa t ive sample" o f

cons t ruc t i on workers a t a s i t e i s v i r t u a l l y impossible.

To e f f e c t i v e l y implement a cons t ruc t i on worker survey- - in order t o

ga in the cooperat ion o f t he i n d i v i d u a l cons t ruc t i on w o r k e r s - - f i r s t i t i s

necessary t o gain the cooperat ion o f a number o f i n d i v i d u a l s and groups

a t a cons t ruc t i on s i t e . These may inc lude the u t i l i t y , prime cont rac tor ,

p r o j e c t manager, subcontractors, foremen, and unions. An understanding

o f the employment r e l a t i o n s h i p s and union arrangements a t cons t ruc t i on

s i t e s i s essen t i a l t o t he success o f conduct ing a survey o f c o n s t r u c t i o n

workers.

We success fu l l y conducted worker surveys a t f o u r d i f f e r e n t nuclear

power p l a n t cons t ruc t i on s i t e s . The task, however, requ i red an ex tens ive use o f t ime and resources. Our e f f o r t would have been s u b s t a n t i a l l y l ess

i f the problems associated w i t h such surveys and the experiences of pre-

v ious researchers i n implementing these surveys had been documented and

a v a i l a b l e t o us. Recogni t ion o f t h i s need has l e d us t o w r i t e t h i s paper.

We w i l l s ys temat i ca l l y present the problems associated w i t h conduct-

i n g cons t ruc t i on worker surveys and suggest poss ib le methods t o so lve

these problems. The d iscussion i s d iv ided i n t o s i x sect ions: (1 ) Pre-

survey Groundwork; ( 2 ) Sampling Issues; ( 3 ) V iable Methods o f Survey

Admin is t ra t ion ; ( 4 ) Response Rate and Follow-up; ( 5 ) Development o f the

Survey Instrument; and ( 6 ) Other Issues. We discuss each of these i n

t u r n below.

PRE-SURVEY GROUNDWORK

It i s u s u a l l y no t poss ib le t o i d e n t i f y the cons t ruc t i on workers by

name o r address. This f a c t immediately l i m i t s t he op t ions a v a i l a b l e t o

I t he researcher f o r conduct ing the survey. S p e c i f i c a l l y , t he survey has I ..

t o be conducted a t t he work s i t e . The cooperat ion and involvement o f a I

number o f key i n d i v i d u a l s a t a s i t e i s necessary, therefore, t o systemat- I -

i c a l l y e s t a b l i s h contac t w i t h the workers. Achieving t h i s cooperation, I I

however, i s no t simple. Employment arrangements a t l a rge power p l a n t

I c ons t ruc t i on p r o j e c t s are governed by a h ie rarchy o f employment and union

I r e l a t i onsh ips . Although these employment arrangements might vary f rom

I s i t e t o s i t e , i n general, the h ie rarchy i s o f the form i l l u s t r a t e d i n

I Table 0-1.

The Employment Hierarchy

Typ ica l l y , t h e u t i l i t y has a prime cons t ruc t i on con t rac to r on a p r o j -

e c t who has the o v e r a l l cons t ruc t i on r e s p o n s i b i l i t y on the s i t e . Several

s p e c i f i c cons t ruc t i on a c t i v i t i e s on the s i t e are contracted out. Other

jobs are undertaken by the prime con t rac to r w i thout in termediary subcon-

t r a c t o r s . I n t h i s l a t t e r case, t he superv isors and workers are h i r e d

d i r e c t l y by the prime cont rac tor . I n the former, t he subcontractors are

the immediate employers o f cons t ruc t i on workers a t a s i t e . The workers

u s u a l l y work i n small groups, t y p i c a l l y c o n s i s t i n g o f f i v e t o twenty

persons; each group i s supervised by a foreman o r supervisor.

There are, o f course, except ions t o the h ie rarchy described here. I n

some cases, the u t i l i t y ac ts as i t s own prime con t rac to r and has several

subcontractors on the p r o j e c t . A l t e r n a t i v e l y , subcontractors are con-

f ined o n l y t o very spec ia l i zed jobs and the u t i l i t y h i r e s the workers

d i r e c t l y t o perform the var ious cons t ruc t i on jobs on the p r o j e c t . Some

u t i l i t i e s and prime con t rac to rs have cons t ruc t ion workers on t h e i r regu-

l a r s t a f f and they do n o t h i r e workers on an "as requ i red" bas i s from

l o c a l pools o f union o r nonunion workers.

On cons t ruc t i on s i t e s t h a t are covered by c o l l e c t i v e barga in ing

agreements, t he unions a lso p l a y a s i g n i f i c a n t ro le . The prime contrac-

t o r and subcontractors get t h e i r workers through t h e union h i r i n g h a l l s

o f t he various l oca l s . C o l l e c t i v e bargain ing agreements sometimes s t i p u-

l a t e t h a t foremen f o r var ious jobs must a l so be h i r e d through the union

h a l l s . Moreover, each union l o c a l has a union j o b steward a t the s i t e t o

assure t h a t the p rov i s ions o f the c o l l e c t i v e barga in ing agreements are

implemented. These provisions often give the unions an important say in

terms of what is requested of workers on the job.

. . Obtaining the Necessary Cooperation

The multiplicity of contractors, subcontractors, and construction

trades each with its own local union makes gaining cooperation from each

of them a difficult task. But such cooperation is essential to the suc-

cess of the survey. Further, the cooperation of these groups could be

instrumental in obtaining the eventual cooperation of the workers them-

selves. There are several concerns that discourage all these groups from cooperating. These concerns include:

a the usefulness of the study;

a the possible use of staff and worker time to implement the survey;

a a common distrust of research findings and the potential for such findings to affect adversely the interest of the groups at the construction site; and

a in the case of workers, an attitude of indifference towards any form of research.

Foremost to gaining the cooperation of these groups is an ability to

demonstrate the usefulness of the findings of the study to everyone asso-

ciated with nuclear power plant construction. This we found was best

achieved through personal contact; written communication set the stage but rarely brought about outright willingness to cooperate. It will be

obvious from the following discussion of methods for implementing the

surveys, that the survey not only imposes a burden on the workers but

also requires the use of their work time on the project. Not surpris-

ingly, a utility and contractors will cooperate only if they see some potential benefit accruing to them from the proposed study. We found

that the offer to compensate for use of worker time to complete the ques-

tionnaire, though rarely accepted by a utility, also helped to elicit

their cooperation. 3

30nly one of our four uti 1 ities requested reimbursement for conducting a survey at their site. For about 1,500 workers filling out a 15-minute questionnaire on the site, we were charged approximately $8,000.

An e f fec t i ve approach t o seeking and ob ta in ing the cooperat ion o f the

key i n d i v i d u a l s i s t o s t a r t a t the t o p and work down the h i e r a r c h i a l

s t r u c t u r e shown i n Table B-1. The process requ i res i d e n t i f y i n g the key

i n d i v i d u a l a t t he u t i l i t y l e v e l and seeking both h i s e x p l i c i t support f o r

t he p r o j e c t as w e l l as h i s ass is tance i n i d e n t i f y i n g and seeking the

support o f key i n d i v i d u a l s f u r t h e r down the employment h ie rarchy .

The U t i l i t y . The support o f the u t i l i t y and the prime con t rac to r i s

l i k e l y t o i n f l uence the decis ions of t he groups who work f o r them. I n

fac t , i t i s unreasonable t o expect cooperat ion f rom anyone e l s e w i thou t

t h e i r e x p l i c i t support and involvement. If the u t i l i t y rep resen ta t i ve i s

convinced t h a t the study i s l i k e l y t o be usefu l t o t he u t i l i t y and i s

w i l l i n g t o say so, then ob ta in ing the support a t o the r l e v e l s i s made 4 cons iderab ly easier . I n many cases, i t might be poss ib le t o use the

agency sponsoring t h e research t o make the i n i t i a l contac t w i t h t h e u t i l -

i t y personnel. 5

The P r o j e c t Manager. The p r o j e c t manager, o r a member o f h i s s t a f f ,

then becomes a key contac t f o r meeting and seeking the cooperat ion o f t h e

subcontractors, supervisors, and union representa t ives a t the s i t e . He

i s a lso ins t rumenta l i n developing an acceptable survey s t r a t e g y and

making the necessary arrangements t o conduct the surveys. Because a l l

t he f e a s i b l e methods o f implementation r e q u i r e the superv isors t o a c t as a l i n k between the researcher and the worker, subcontractors and super-

v i s o r s need t o be invo lved i n t he development o f t he implementing proce-

dures.

Other P r o j e c t S t a f f . The procedures f o r con tac t i ng o the r members of

t h e p r o j e c t s t a f f w i l l vary g r e a t l y depending upon the p r o j e c t manager.

A p r o j e c t manager may wish t o appoint an ass i s tan t t o make f u r t h e r

4 ~ t each o f t he f o u r s i t e s i n our study, our contact person a t the u t i l i t y understood t h e s e n s i t i v i t i e s o f t h e cons t ruc t i on p r o j e c t s t a f f and was essen t i a l i n i n t roduc ing the research team t o the p r o j e c t manager f o r t h e u t i l i t y and/or t he prime con t rac to r .

=bIe were able t o use t h e NRC t o make the i n i t i a l contact w i t h t h e u t i l - i t i e s ; desp i te t h i s , i t was necessary t o contac t s i x u t i l i t i e s i n o rder t o get f o u r p a r t i c i p a n t s .

arrangements. Some p r o j e c t managers w i l l choose t o invo lve a l a r g e num-

ber o f people a t t h i s stage; o thers may i nvo l ve o n l y a few. The ex ten t

t o which superv isors and foremen are invo lved va r ies depending upon the

survey s t ra tegy selected as w e l l as by t h e decis ions o f t he p r o j e c t man-

ager.

Unions. Get t ing unions t o encourage t h e i r members t o p a r t i c i p a t e i n

t he survey i s perhaps t h e most d i f f i c u l t task. Unions are very indepen-

dent, have a d i r e c t access t o workers, and can i n f l uence worker response.

If they are n o t consulted, o r are skep t i ca l about the research t o be

performed, the chances o f implementing t h e survey are remote. Fur ther-

more, t he u t i l i t y and t h e prime con t rac to r are eager t o main ta in good

labor and management r e l a t i o n s and are n o t l i k e l y t o accept anyth ing t h a t

might p o t e n t i a l l y jeopardize t h a t re la t i onsh ip .6 Union j ob stewards a t

t he cons t ruc t i on s i t e s have d i r e c t access t o and in f luence on the work-

ers. Workers are no t l i k e l y t o respond t o the survey i f the union stew-

ards a t t he s i t e do n o t encourage them t o do so. Likewise, union stew-

ards are no t l i k e l y t o cooperate w i thout t he approval o f the business

agents o f t h e i r union l oca l s .

The B u i l d i n g Trades Council. The task o f g e t t i n g the cooperat ion o f

t he var ious c r a f t s and separate union l o c a l s i s impossible w i thou t t he

he lp o f t he p r o j e c t s t a f f . An e f f e c t i v e way i s t o use the labor manage-

ment r e l a t i o n s o f f i c e r from the u t i l i t y o r the prime con t rac to r t o seek

the assistance o f t he l o c a l B u i l d i n g Trades Counci l i n g e t t i n g i n d i v i d u a l

business agents t o cooperate. The l o c a l B u i l d i n g Trades Counci l i s an

assoc ia t ion o f cons t ruc t i on t rade unions which o f f e r s a p lat form t o v a r i -

ous union l o c a l s t o coordinate t h e i r a c t i v i t i e s and t o discuss the con-

s t r u c t i o n employment requirements w i t h the major cons t ruc t i on cont rac tors

i n t he area. The B u i l d i n g Trades Counci l can prov ide the oppor tun i t y t o

exp la in the p r o j e c t d i r e c t l y t o a l l t he union representa t ives a t the same

t ime and thereby save tremendous amounts o f e f f o r t requ i red t o contac t

6 ~ h e i n f l uence o f unions var ies f rom s i t e t o s i t e . It was our exper i- ence t h a t unions commanded greater i n f l uence a t s i t e s i n t he Northeast compared t o the South. Accordingly, i t was eas ie r t o arrange surveys a t t he southern s i t e s .

the unions i n d i v i d u a l l y . The ex ten t t o which union cooperat ion has t o be

sought should be determined i n consu l ta t i on w i t h the p r o j e c t s t a f f and

can be expected t o vary from s i t e t o s i t e .

Th is pre-survey groundwork can be t ime consuming and may extend over

a prolonged per iod. I t i s , however, ext remely important and should be

inc luded i n the survey planning. I n our experience, c a r e f u l p lann ing o f

these d e t a i l s was perhaps the most inst rumenta l f a c t o r i n the success o f

our surveys.

SAMPLING ISSUES

The number o f workers a t a nuc lear power p l a n t cons t ruc t i on s i t e may

vary from 500 t o 4,000, depending upon t h e stage o f p r o j e c t completion.

Thus, one might conclude t h a t surveying o n l y a sample o f these workers

would be s u f f i c i e n t t o t e s t hypotheses and draw conclusions about the

e n t i r e populat ion. This i s n o t necessa r i l y t rue , however, i n t he case o f

cons t ruc t i on worker surveys because o f t he t r a n s i e n t na ture o f the work-

f o r c e and because o f the importance o f subgroups o f t he workforce a t a

given s i t e .

I n t he f i r s t place, i t i s n o t poss ib le t o i d e n t i f y e a s i l y the popula-

t i o n o f cons t ruc t i on workers a t a s i t e . The cons t ruc t i on workforce, as

we have noted, i s t rans ien t ; o f t e n the re i s a h igh tu rnover from one week t o the next. Also, workers move f rom one j ob t o another and f rom one

subcontractor t o another on the s i t e . It i s t he re fo re n o t poss ib le t o

i d e n t i f y t he popu la t ion from which one might sample.

Furthermore, i f the data w i l l be w ide ly used, t he re i s a need t o

survey workers from a l l c r a f t s represented a t t he s i t e . This i s t r u e f o r

two reasons. F i r s t , because d i f f e rences across c r a f t s a re u s u a l l y impor-

t a n t t o t he ana lys is t o be performed, and second, because a researcher i s

i n v a r i a b l y seeking t o genera l i ze f rom the data a t one p o i n t dur ing t h e

cons t ruc t i on phase t o o the r p o i n t s du r ing the cons t ruc t i on phase. A t any

one p a r t i c u l a r t ime, depending upon t h e stage o f p r o j e c t completion, some

c r a f t s w i l l be represented on the s i t e i n r a t h e r small numbers. The f a c t

t h a t these c r a f t s c o n s t i t u t e a smal l p ropo r t i on o f the t o t a l workforce a t

t he t ime o f t he survey does n o t r e f l e c t t he r e l a t i v e importance o f t h e

c r a f t du r ing the e n t i r e phase o f cons t ruc t ion . I f the purpose o f t h e

survey i s t o c o l l e c t in fo rmat ion t h a t can be app l ied t o var ious stages o f

project completion, it is important to include adequate numbers of these

smaller crafts in the sample.

These factors suggest that stratified random sampling ought to be

adopted. This, however, is rather difficult because of the level of

prior information required to draw a stratified sample. Typically, even

the number of workers expected to be on the site at a particular time can

only be estimated rather crudely; it is virtually impossible to obtain

accurate estimates of the number of workers by craft. 7

Since stratified or simple random sampling is usually not possible, a

reasonable alternative is to conduct a census survey at the site. This

situation is not as unfortunate as it might seem. On the contrary, it

has the advantage of reducing the problem of bias and enabling the

researcher to examine small but key groups of workers at the site. It

was our experience that, in view of the special implementing arrangements

for conducting the survey at a construction site, a census survey is

easier and also less costly than surveying a sample of workers. This is

because the viable survey administration methods that can be adopted are

such that conducting a sample survey would make the procedures much more

complicated. The next section on the viable methods of survey adminis-

tration will clarify this point.

VIABLE METHODS OF SURVEY ADMINISTRATION

Many of the standard procedures for administering surveys, such as

mai 1 surveys, telephone surveys, and personal interviews, are not viable

for conducting a survey at a large construction site. The reason for this is that names, addresses, and telephone numbers generally are not

available for the population of workers at the site. This is not to say

that a record of names and addresses is not maintained. There are, how-

ever, two problems to obtaining them. First, there is usually no single

source where an up-to-date, complete listing of names and addresses of

workers at a site is maintained. Second, utilities and contractors are

h his information is difficult to obtain because workers from a particular craft typically work for several subcontractors. Even specialty craft subcontractors have a few workers from other crafts working for them.

not likely to release this information, even if it were available,

because they deem it personal. This reluctance to release names and

addresses stems from a consideration of the implications that this action

might have on employer-employee relationships.

The unions could possibly be another source of this information.

However, the unions are usually the most skeptical of research projects

and are the least likely to cooperate. Also, using union membership

lists to identify workers would exclude nonunion workers on the site from

the survey.

This inability to identify the worker population considerably limits

the methods that a researcher can adopt to implement the survey. Accord-

ingly, some form of group administration is the only option to implement

a survey of workers at a construction site. Options such as distributing

questionnaires with paychecks, or handing out questionnaires at entry and

exit points of the site seem potentially plausible but are not, in fact,

workable. Such procedures, without pre-identification of individual

workers, do not allow any control over completing and returning of the

survey forms, and would probably yield an unacceptably low response rate.

The only procedures that are likely to work under the circumstances

are those in which the questionnaires are distributed and collected in a

controlled manner. These require a system by which every worker at the site can be contacted individually or in a group and the surveys adminis-

tered at that time. The precise method for implementing a survey will

depend upon the specific administrative practices of the construction

site in question.

After numerous discussions with utility and project staff at the

various sites and after evaluating the procedures used by various other

groups to administer similar surveys, as well as the response rates

achieved in these survey efforts, we identified three viable options for

conducting the surveys. These options include 1) the safety meeting

option, 2) the supervisor option, and 3) the paycheck distribution

option. Each of these three options is described in detail below.

The Safety Meeting Option

The first option takes advantage of the safety meetings that are

required to be held at regular intervals at nuclear power plant construc-

tion sites.8 At these meetings, workers meet in small groups to discuss questions of safety at the site under the supervision of a foreman or a supervisor. These meetings are therefore a convenient place to conduct the survey.

The survey forms can be distributed, completed and collected at the meeting itself. This option requires that the regular safety meeting be extended by 10 or 15 minutes. Meeting locations and number of workers at each meeting can be predetermined. Arrangements can be made to deliver

the required number of questionnaires and to collect them at each location. At the conclusion of the safety meeting business a supervisor or the person administering the survey can briefly describe the nature of the study, be available to answer any questions, and encourage the cooperation of the workers in filling out the survey. An important feature of this procedure is that it is likely to result in a high response rate,

requires no follow-up, can be closely monitored, and covers all workers present on the site. 9

There are, however, certain conditions that are important to the feasibility of this option: foremost is the willingness of the utility personnel and/or prime contractor to extend the safety meeting for administering the questionnaire. In addition, it is important to confirm that safety meetings do indeed cover all workers and are held on regular basis. If not, bias due to omission of certain groups of workers from

the survey could be inadvertently introduced.

The Supervi sor Option The second option takes advantage of the way in which work is organ-

ized at a construction site. Workers at a site are divided into small groups under a foreman and/or supervisor. In this option each supervisor

8 ~ t some sites safety meetings are scheduled weekly, with meetings for all crafts being held at the same time at a central location. At other sites safety meetings may be held at different times, on different days, for different groups of workers.

'~t should be noted that safety meetings will not include office workers. Therefore, if this option is selected, it will be necessary to make special arrangements to survey office workers.

adminis ters the survey t o h i s workers, e i t h e r i n d i v i d u a l l y o r as a group,

a t some convenient t ime dur ing the day. Supervisors and the number o f

workers i n each crew can be i d e n t i f i e d i n advance. Supervisors can be

given t h e requ i red number o f quest ionnaires a t t h e beginning o f the day

and the completed quest ionnaires can be c o l l e c t e d from them a t t he end o f

t he day. I f a superv isor i s unable t o get a l l h i s workers t o f i l l ou t

t he quest ionna i re t h a t day, he can be asked t o have them f i l l e d ou t t h e

next day.

Th is permi ts t he survey t o be conducted w i t h l i t t l e o r no d i s r u p t i o n

o f work. For example, superv isors can use the normal breaks between work

t o have workers complete the quest ionnaire. Although t h i s procedure does

have t h e advantage o f n o t d i s r u p t i n g work, i t does r e q u i r e the coopera-

t i o n and assis tance o f a l a rge number o f supervisors. Supervisors must

understand the purpose o f t he survey and f o l l o w p rec i se admin is te r ing

i n s t r u c t i o n s t o assure the o b j e c t i v i t y o f t he survey.

Th i s p repara t ion can be done bes t i f the researchers can meet w i t h

t h e superv isors i n d i v i d u a l l y o r i n a group.10 Despi te t h e f a c t t h a t

work crews are sca t te red over a l a r g e area a t the cons t ruc t i on s i t e ,

foremen/supervisors do meet r e g u l a r l y w i t h the p r o j e c t s t a f f and subcon-

t r a c t o r s . These meetings could prov ide access t o the group o f super-

v i s o r s who w i l l be used t o adminis ter t he survey t o workers. Such a

meeting, however, may n o t always be poss ib le a t a l l s i t e s .

The Paycheck D i s t r i b u t i o n Option

The t h i r d op t i on i s based on the use o f c e n t r a l paycheck d i s t r i b u t i o n

l oca t i ons a t a s i t e . A t some s i t e s , paychecks are d i s t r i b u t e d a t a few

c e n t r a l l oca t i ons , w i t h e x i t s t h a t can be e a s i l y manned. Th is a l lows f o r

the contac t necessary t o conduct t he survey e f f e c t i v e l y . Th is procedure

invo lves stopping work 10 o r 15 minutes e a r l y and d i s t r i b u t i n g t h e ques-

t i o n n a i r e s w i t h workers' paychecks. Workers are asked t o complete the

quest ionna i re immediately and t o r e t u r n the completed quest ionna i re as

they leave the pay area.

group meeting i s necessary because of t h e number of foremen o r superv isors a t a s i t e might be as many as 200. I n d i v i d u a l contac t i s f e a s i b l e o n l y f o r those who are unable t o at tend the group meeting.

The v i a b i l i t y o f t h i s op t i on depends upon t h e w i l l i ngness of t he

u t i l i t y t o a l l ow workers t o q u i t work 10 o r 15 minutes e a r l y on payday,

t he number o f payment p o i n t s on the s i t e , and t h e ease w i t h which t h e

e x i t s from the payment po in t s can be monitored. For t h i s procedure t o be

successful , i t i s important t o in fo rm workers about t he survey and t o

seek t h e i r cooperat ion be fore the ac tua l survey date.

These th ree opt ions are t h e o n l y ones which we considered t o be

v i a b l e methods f o r e f f e c t i v e l y implementing a cons t ruc t i on worker sur-

vey. It may be poss ib le t o i d e n t i f y o the r v i a b l e opt ions, g iven the

circumstances a t a p a r t i c u l a r s i t e , b u t we were unable t o i d e n t i f y

acceptable a l t e r n a t i v e s i n our experience a t t he f o u r s i t e s t h a t we sur-

veyed.

The .ef fect iveness o f these opt ions w i l l va ry from s i t e t o s i t e and

depend upon t h e arrangements t h a t u t i l i t i e s and prime cont rac tors are

w i l l i n g t o make a t 8 s i t e f o r purposes o f t he survey.'' For instance,

s a f e t y meetings may no t be scheduled r e g u l a r l y f o r a l l c r a f t s and there-

f o r e may n o t be a f e a s i b l e op t i on a t a g iven s i t e . The superv isor op t i on

may be d i f f i c u l t because i t requ i res the cooperat ion o f a l a r g e number o f

i n d i v i d u a l s a t a s i t e ; however, i t may be regarded as the l e a s t d isrup-

t i v e t o the work on the p r o j e c t . The paycheck d i s t r i b u t i o n i s perhaps

the l e a s t a t t r a c t i v e o f t he opt ions we have i d e n t i f i e d , b u t might be

considered the most convenient by the u t i l i t y o r the prime con t rac to r .

A very important t h i n g t o remember i s t h a t the f i n a l choice o f t he

method t o be adopted i s n o t completely i n t he hands o f t he researcher.

The researcher must be f l e x i b l e and adapt t he survey s t ra tegy t o the

cond i t ions and circumstances a t a g iven cons t ruc t i on s i t e . It i s , how-

ever, use fu l t o i d e n t i f y several a l t e r n a t i v e s f o r admin is t ra t ion o f t he

surveys, so t h a t var ious op t ions can be discussed w i t h the represen-

t a t i v e s o f t h e u t i l i t y and/or prime con t rac to r and an opt ion acceptable

t o the researcher and t o the p r o j e c t s t a f f can be i d e n t i f i e d . I n

general, t he p r o j e c t s t a f f w i l l want t o choose the op t ion t h a t i s l e a s t

d i s r u p t i v e t o the work on the p ro jec t . U t i l i t y personnel may a lso

l ~ h e superv isor op t i on was adopted on th ree of the f o u r s i t e s t h a t we surveyed. The s a f e t y meeting op t i on was se lec ted a t the f o u r t h s i t e .

express concern about the cost of the workers' time taken to complete the questionnaire. In some cases, reimbursement might be necessary to gain the cooperatin of the utility. 12

Once an option for survey administration has been adopted, it is important to meet with everyone who will be involved in the survey activity. (The particular individuals will depend upon the option selected. ) It is crucial that these individuals recognize the importance of the project, and that they understand their specific responsibilities.

RESPONSE RATE AND FOLLOW -UP

The success of the survey effort is very dependent upon a high response rate from the workers. Careful preparation is necessary because, except perhaps for the supervisor option, there is little opportunity for follow-up.

As was mentioned in an earlier section, getting the cooperation of the workers is extremely important to achieving a high response rate. Unless the importance of the study can be conveyed, workers may be rather reluctant to complete the questionnaire. It is helpful to get the project management, unions, supervisors, and union job stewards to support the survey and encourage the workers to complete the survey instrument.

Calculating an actual response rate may also present some problems. The information necessary to calculate a response rate is merely the

number of completed questionnaires and the total number of workers on the site on the day of the survey. If response rates by craft are desired, then total workers by craft on the day of the survey are also required.

This information, however, may not always be readily available. For example, it is possible that attendance is reported only on a weekly basis (as the average number of workers on site during that week) or that information by craft is not available. Arrangements should be made with the project staff to obtain the necessary information. This should be done prior to the survey date to allow sufficient time to develop an

121eimbursement was an issue at only one of the four sites that we surveyed.

acceptable procedure to estimate total worker counts at the site on the day of the survey, if an exact count is not available.

DEVELOPMENT OF THE SURVEY INSTRUMENT

The development of the survey instrument is certainly of major importance in any research project. As is the case in most surveys, in devel-

oping a survey of construction workers, a trade-off must be made in terms of the amount of information that can be obtained and the length of the questionnaire. Utility personnel often expressed the opinion that the questionnaire should be limited to one page and should not take more than 10 minutes to complete.

In addition to concerns about the length of the questionnaire, objections may also be encountered regarding particul ar questions. For exam-

ple, in our experience, the project and union representatives felt that questions regarding income and rent were too personal .13 Also, union representatives at one site objected to including a question about union status.

Serious objections may require deleting a question from the questionnaire. In other cases, questions may be rephrased or otherwise modified to minimize the objections. For instance, a worker may be asked to indicate rent or income within certain ranges, rather than to provide the exact amount. In addition, questions requesting information of a personal nature can be placed at the end of the questionnaire. 14

An additional problem that may be encountered in surveying a worker

population of this type is illiteracy. Especially among less-skilled workers such as laborers, functional illiteracy may not be uncommon. For this reason, the questionnaire should be kept as simple as possible.

131ndeed, analysis of our completed questionnaires did indicate that rent and income were the two questions that were most often left un- answered.

14~1so, we included a sentence in the introduction to the questionnaire stating that the worker did not have to answer any question that he considered to be too personal.

We raise the issue of questionnaire development because the details

of the survey instrument usually receive attention only after most of the

groundwork has already been completed. It can be very disappointing to

the researcher to have to exclude what he feels is information essential

to his research.

OTHER ISSUES

Several other factors are important in assuring success of the survey

effort. These factors also arise from the special nature and circum-

stances of the construction activities at a site.

The time that the survey is conducted could be an important factor.

Construction work is often seasonal. Especially at northern sites, con-

struction may slow down or completely stop during the winter months. Day of the week can also be important. (If the surveys are administered

during the safety meeting or on payday, there is little choice in this

matter.) Mondays and Fridays are generally considered to have the high-

est rates of absenteeism, and for this reason may not be the best days to

conduct a survey. Further, Mondays and Fridays are not ideal for a num-

ber of other reasons. Mondays may not allow enough time for distributing

the questionnaires to supervisors and for other survey preparations. Similarly, surveys conducted on Fridays allow no time for any follow-up

activities on the next day. If possible, i t may also be desirable to avoid scheduling a survey on

the day before or after a major holiday. Attendance on those days may be

somewhat lower than usual. Even the weather can be a factor in the suc-

cess of the survey; rain on the day of the survey can affect attendance.

There is, however, no convenient solution to this problem.

We found it very helpful to prepare a brief description of the proj-

ect for distribution at the many meetings that were scheduled. This

description should include the purpose of the study, the nature of ques-

tions asked, and emphasize the importance of the study to everyone asso-

ciated with nuclear power plant construction. Not only the key indi-

viduals of the project staff, but the workers themselves, should be

informed of the survey in advance. If a regular safety meeting is held,

an announcement can be made during the meeting preceding the survey.

Alternatively, a brief notice describing the survey can be included with

paychecks before the survey date. Also, announcements can be printed and

posted at several places around the site where workers are likely to

gather. We used several of these methods successfully in the surveys we

conducted.

SUMMARY In conducting a construction worker survey, it is important to gain

the cooperation of a number of individuals at the construction site. A

rather complex hierarchy of employment and union relationships exists at

a construction site and a researcher is confronted with the problems, not

only of the workers' attitude to the survey, but also the attitudes of

several other individuals. The secret to ensuring the success of the

survey effort lies in obtaining the cooperation of all the key indi-

viduals at the site before the survey. Although these individuals should

be closely involved in decisions regarding the procedures developed to

conduct the survey, any burdens imposed upon the utility and project

staff should be minimized. Costs and labor relations are paramount con-

cerns to utility personnel and the researcher should be sensitive to

their concerns.

Assuring a high response rate is, of course, the most important con-

sideration. A survey strategy should be selected that will maximize the likelihood that a worker will return a completed questionnaire. This

requires a situation in which the survey administration can be moni-

tored. Distributing questionnaires during group meetings or distributing

them to workers through their supervisors has proved to be very successful in this regard.

This paper has been a very general discussion of the problems con-

fronted in conducting a construction worker survey. In fact, circum-

stances will vary considerably from site to site. Decisions should be made based upon the particular circumstances at each site. However, it

is hoped that the above discussion will provide some suggestions which

may be useful in approaching the problem in future research projects.

REFERENCES

Socioeconomic Impacts: Nuclear Power S t a t i o n S i t i n g , P o l i c y Research Associates, S ta te College, PA, 1977.

APPENDIX C

MIGRANT PROPORTION MULTIVARIATE ANALYSIS

APPENDIX C

MIGRANT PROPORTION MULTIVARIATE ANALYSIS

Th is appendix presents a more d e t a i l e d d iscussion of t h e migrant

p ropo r t i on analys is which was conducted i n t he m u l t i v a r i a t e analys is

p o r t i o n o f t h i s study. The purpose of t he ana lys is was t o exp la in the

observed v a r i a t i o n i n c r a f t - s p e c i f i c migrant p ropor t ions across the s i t e s

inc luded i n t h i s study. The r e s u l t s o f t h i s ana lys is served as a basis

f o r spec i f y i ng procedures f o r f o recas t i ng migrant p ropor t ions a t f u tu re

nuclear power p l a n t cons t ruc t ion s i t e s . The d iscussion i s d iv ided i n t o

th ree sect ions. The f i r s t sec t i on describes the determinants o f migrant

p ropor t ions a t nuclear power p l a n t cons t ruc t i on s i t es . The second sec-

t i o n describes the emp i r i ca l s p e c i f i c a t i o n and the f i n a l sec t i on des-

c r i b e s the ana lys is r e s u l t s .

DETERMINANTS OF MIGRANT PROPORTIONS

The problem which i s addressed i n t h i s study i s a spec ia l case o f

migra t ion . While most m ig ra t i on s tud ies examine the gradual movement o f

people from one area t o another, t h i s study examines the r a t h e r sudden

movement o f workers i n response t o a p a r t i c u l a r employment opportunity- - a s i t u a t i o n i n which employment demand f a r exceeds the l o c a l labor supply.

Thus, t h i s study does not examine m ig ra t i on i n the general populat ion,

b u t r a t h e r focuses upon m ig ra t i on w i t h i n t h e cons t ruc t i on indus t ry . This

i s an important cons idera t ion because the f a c t o r s which i n f l uence the

m ig ra t i on o f workers t o l a rge cons t ruc t i on p r o j e c t s d i f f e r i n many

respects from the f a c t o r s t y p i c a l l y considered i n t r a d i t i o n a l m ig ra t i on

studies.

Most m ig ra t i on models view m ig ra t i on as a permanent move. However,

employment f o r cons t ruc t i on workers i s seldom permanent. Espec ia l l y

among more spec ia l i zed c r a f t s , workers are h i r e d f o r s p e c i f i c jobs o f a

r a t h e r l i m i t e d durat ion. As a r e s u l t cons t ruc t i on workers o f t e n must

move from s i t e t o s i t e o r comute r a t h e r long distances each day t o main-

t a i n steady employment.

As i s t r u e o f workers i n o ther i ndus t r i es , t h e a t t rac t i veness o f an

employment oppor tun i t y t o a cons t ruc t i on worker l i e s i n the expected

income t o be der ived from a given move. I n t r a d i t i o n a l m i g r a t i o n s tud ies

wage r a t e s are commonly used as measures o f t he r e l a t i v e a t t rac t i veness

of employment o p p o r t u n i t i e s t o movers. However, because employment

oppor tun i t i es i n cons t ruc t i on are u s u a l l y o f a r e l a t i v e l y s h o r t durat ion,

o ther f ac to rs r e l a t i n g t o the a v a i l a b i l i t y o f employment a re very impor-

t a n t considerat ions. The p o t e n t i a l o f an employment oppor tun i t y f o r a

cons t ruc t i on worker i s , t o a l a r g e extent , determined by t h e r e g u l a r i t y

w i t h which a worker can ob ta in work and the length o f t ime over which

such regu la r employment i s ava i lab le . Also important i s t he oppor tun i t y

fo r overt ime work. Even though the wage r a t e i s t he same f o r two d i f f e r -

en t jobs, t h e income associated w i t h them cou ld vary considerably depend-

i n g upon the c o n t i n u i t y and du ra t i on o f employment and the a v a i l a b i l i t y

of overt ime work. Thus, i t i s t he annual income, r a t h e r than t h e h o u r l y

wage r a t e , which i s t he important considerat ion. A cons idera t ion o f t he

c r a f t - s p e c i f i c d i f f e rences i n the a t t rac t i veness o f employment opportuni-

t i e s has n o t been inc luded i n past s tudies. This s tudy w i l l at tempt t o

determine t h e importance o f va r i ab les which r e f l e c t d i f f e rences i n t he

wage rates, as w e l l as v a r i b l e s which r e f l e c t d i f f e rences i n t he na ture

o f labor requirements ( i .e., expected du ra t i on and c o n t i n u i t y o f employ-

ment) i n e x p l a i n i n g t h e v a r i a t i o n i n migrant p ropor t ions across s i t e s and

across var ious c r a f t groups. Worker i nm ig ra t i on i s a l so l i k e l y t o vary from s i t e t o s i t e depend-

i n g upon the c h a r a c t e r i s t i c s o f t he area. If cons t ruc t i on occurs i n a

r e l a t i v e l y populated area, one might observe 1 i t t l e m ig ra t i on associated

w i t h cons t ruc t i on because the l o c a l labor supply may be able t o meet the

increased demand f o r workers. I n a very r u r a l area, on t h e o the r hand,

one might observe considerable inmigra t ion . A cons idera t ion o f t h e l o c a l

a v a i l a b i l i t y o f labor i s p a r t i c u l a r l y important because i n the construc-

t i o n i n d u s t r y access t o p a r t i c u l a r jobs i s c o n t r o l l e d by the union

through the union h i r i n g h a l l o r work r e f e r r a l system. Through t h i s

system, preference i s g iven t o members o f the union l o c a l w i t h j u r i s d i c -

t i o n over t he p r o j e c t . The h i r i n g h a l l system i s a l so used t o g i ve p re f-

erence t o workers based on length o f s e n i o r i t y i n the union l o c a l . Thus,

very important t o a s tudy o f t he na ture are considerat ions o f t he s i z e of

t he cons t ruc t i on l abo r f o r c e w i t h i n commuting d is tance o f t he s i t e and

the competing demand f o r workers f rom o ther cons t ruc t i on p r o j e c t s i n t he

area. However, a l so important are the f a c t o r s which r e f l e c t t he a t t r a c-

t iveness o f the area t o i nm ig ra t i ng workers. These f a c t o r s might inc lude

f u t u r e employment oppor tun i t i es i n t he area and the a v a i l a b i l i t y of hous-

i n g i n nearby communities. I n t h i s s tudy we examine the importance o f

f a c t o r s such as the l o c a l a v a i l a b i l i t y o f labor, competing demand f o r

labor i n t he region, and var ious o the r reg iona l c h a r a c t e r i s t i c s i n

e x p l a i n i n g the v a r i a t i o n i n c r a f t - s p e c i f i c migrant p ropor t ions across

s i t e s .

EMPIRICAL SPECIFICATION

Migrant p ropo r t i on was def ined t o be the r a t i o o f t h e number o f

movers t o the t o t a l number o f workers a t t he s i t e . Workers were c l a s s i -

f i e d as movers i f they had changed t h e i r work week residence t o work a t

the cons t ruc t i on s i t e . The u n i t o f ana lys is f o r purposes of es t ima t ing

these equations was workers grouped by c r a f t . Because o f major d i f f e r -

ences between cons t ruc t i on and nonconstruct ion workers, as w e l l as the

f a c t o r s t h a t are l i k e l y t o i n f l uence t h e i r migrant p ropo r t i on a t a s i t e ,

two separate equat ions were s p e c i f i e d and estimated. The cons t ruc t i on

worker equat ion inc luded the f o l l o w i n g seven c r a f t groups: 1

a plumbers and p i p e f i t t e r s ;

a i ronworkers

a bo i 1 ermaker s ;

a opera t ing engineers;

a e l e c t r i c i a n s ;

a carpenters; and

e l aborers and teamsters.

The nonconstruct ion worker equat ion inc luded two groups:

e c l e r i c a l workers ( i n c l u d i n g s e c u r i t y and medica l /nurs ing s t a f f ) ; and

a management (a1 1 o ther nonconstruct ion workers, i n c l u d i n g managers, engineers, and superv isors) .

l ~ e excluded workers f rom o ther c r a f t s such as b r i ck laye rs , cement masons, sheetmetal workers, pa in ters , and asbestos workers. This heterogeneous group o f workers, however, t y p i c a l l y c o n s t i t u t e s less than e i g h t percent o f a l l workers a t a nuclear power p l a n t cons t ruc t i on s i t e .

Based upon theory and t h e r e s u l t s of our p r o f i l e ana lys i s we speci-

f i e d migrant p ropor t ions as a f u n c t i o n o f several f ac to rs . These f a c t o r s

can be expressed as a f u n c t i o n a l r e l a t i o n s h i p o f t h e f o l l o w i n g form:

(1) MPROP = f(INCPOT, LABRQ, COMPDMD, LBAVAIL, RGCHAR,

CO NTVAR )

where:

MPROP = Migrant p ropo r t i on o f a p a r t i c u l a r c r a f t a t a s i t e ;

INCPOT = A vec tor o f va r i ab les r e f l e c t i n g the income p o t e n t i a l associated w i t h employment a t t he s i t e ;

LABRQ = A vec tor o f va r i ab les r e f l e c t i n g labor requirements a t t he s i t e ;

COMPDMD = A vector o f va r i ab les r e f l e c t i n g competing demand f o r 1 abor i n region;

LBAVAIL = A vec tor o f va r i ab les r e f l e c t i n g l o c a l a v a i l a b i l i t y o f 1 abor i n region;

RGCHAR = A vec tor o f reg iona l c h a r a c t e r i s t i c var iab les ; and

CONTVAR = A vec tor o f c o n t r o l var iab les .

However, f o r t he purpose o f exp la in ing t h e v a r i a t i o n i n migrant pro-

por t i ons across surveys f o r var ious c r a f t groups, we used o rd ina ry l e a s t

squares regression t o est imate an equat ion o f t h e f o l l o w i n g form:

('1 Ln MPROP = a1 + a2 Ln INCPOT + a3 Ln LABRQ

1-MPROP

+ 04 Ln COMPDMD + a5 Ln LBAVAIL

+ a6 Ln RGCHAR + a, Ln CONTVAR + c

where the terms are the same as i n equat ion ( I ) , except:

as = c o e f f i c i e n t s o f va r i ab les inc luded i n the equation;

E = the e r r o r term; and

Ln = t h e na tu ra l l oga r i t hm ic t ransformat ion.

Two spec ia l fea tures o f the l i n e a r r e l a t i o n s h i p shown i n equat ion ( 2 )

should be noted. F i r s t , a l o g i t t rans format ion was used because t h e

values o f the dependent va r i b les , being propor t ions, are cons t ra ined

between 0 and 1. This t rans format ion has the e f f e c t o f ensur ing t h a t the

pred ic ted migrant p ropo r t i on values w i l l n o t f a l l ou ts ide t h e range o f

zero t o one. Second, a l oga r i t hm ic t rans format ion o f t he explanatory

va r iab les was used t o capture the non- l inear r e l a t i o n s h i p between t h e

va r iab les and migrant p ropor t ions .

Data from 21 cons t ruc t i on worker surveys f rom 9 nuclear power p l a n t

s i t e s were inc luded i n the analysis. C r a f t s w i t h l ess than 30 workers a t

a s i t e were excluded from the ana lys is because o f t he p o t e n t i a l f o r l a rge

e r r o r s i n es t imat ing migrant p ropor t ions based on small numbers.2 This

y i e l d e d a t o t a l o f 134 observat ions f o r the cons t ruc t ion worker equat ion

and 42 observat ions f o r t he nonconstruct ion worker equation.

D e f i n i t i o n o f Var iables

Several va r i ab les were def ined t o capture t h e i n f l uence o f t he

explanatory f a c t o r s shown i n equat ion (2 ) . I n many instances, t he speci-

f i c va r i ab les inc luded i n the nonconstruct ion worker equat ion d i f f e r e d

from those included i n the cons t ruc t i on worker equation. Th is was d ic-

t a t e d by the d i f f e rences i n t he na ture o f cons t ruc t i on and nonconstruc-

t i o n employment, labor requirements a t t he s i t e and the a v a i l a b i l i t y o f

da ta on nonconstruct ion workers. A b r i e f d iscussion of each o f t he

explanatory fac to rs , as w e l l as the s p e c i f i c va r i ab les which were con-

sidered, i s presented below. The p rec i se v a r i a b l e d e f i n i t i o n s are

inc luded a t the end o f t h i s appendix.

1. Income P o t e n t i a l

Among cons t ruc t i on workers, m ig ra t i on i s l i k e l y t o be in f luenced by

the income p o t e n t i a l associated w i t h employment a t a p a r t i c u l a r s i t e . We

i d e n t i f i e d f o u r va r i ab les which r e f l e c t d i f f e rences i n the r a t e o f com-

pensat ion and, therefore, income p o t e n t i a l , f o r cons t ruc t i on workers.

The f o l l o w i n g va r iab les were considered:

wage r a t e (WAGE);

overt ime r a t e (OTIME);

f r i n g e b e n e f i t r a t e (FRINGE); and

avai 1 a b i 1 i t y o f t r a v e l a1 lowances (TALLOW).

2 ~ n addi t ion, 3 surveys f rom one s i t e were inc luded from the ana lys is because data f o r some o f the explanatory va r iab les were n o t a v a i l a b l e fo r t h a t s i t e .

Due to the nature of construction employment (i .e., irregularity of

employment) a number of other factors can also influence income potential

for construction workers. These include factors such as continuity and

duration of employment. Those variables, however, reflect differences in

1 abor requirements associated with project construct ion and are included

as part of our discussion of labor requirement variables.

Among nonconstruction workers, on the other hand, migrant proportions

observed at a site are less likey to be associated with income potential

and much more likely to be influenced by the personnel policies of utili-

ties and engineering firms. Especially among the management group, a

large number of workers are likely to be brought in by the utility or

prime contractor to work on the project with only a small number being

hired locally. Moreover, the nonconstruction group is a very hetero-

geneous group and, as a result, no typical income values could be

obtained for the clerical and management groups. Thus, reflecting both

the lack of adequate data and the importance of personnel policies in

influencing mi grant proportions, no income potential variables were

included in estimating the nonconstruction equation.

2. Labor Requirements

We developed several variables in an effort to capture differences in labor requirement profiles among the different crafts at a site as well

as across sites. Some variables were developed to capture the expected

availability of employment at the site over the entire construction phase

of the project. These variables, which include continuity and duration

of employment are important because they influence the expected income of

construction workers. Other variables were defined to reflect differ-

ences in overall and peak workforce requirements. Also, because of the

cross-sectional nature of our data, we developed other variables to cap-

ture differences in labor requirements at the time of the survey. Speci-

fically, the following variables were considered:

expected continuity of employment at the site (CONT) ;

expected growth of employment opportunities at the time of the survey (GREMP) ;

total projected employment (TEMP) ;

number of workers at a site at the time of the survey (NCRAFT);

overall stage of project completion (PEAK);

a expected peak employment (NPEAK); and

a expected du ra t i on o f peak employment (DPEAK).

Unfor tunate ly , d e t a i l e d l abo r requirement data were no t a v a i l a b l e f o r

t he nonconstruct ion workforce. Indeed, t he o n l y v a r i a b l e which was

a v a i l a b l e f o r t he nonconstruct ion group was t h e number o f workers on s i t e

a t the t ime o f the survey (NCRAFT). Th i s v a r i a b l e was inc luded i n e s t i -

mating t h e nonconstruct ion equation.

3. Competing Demand f o r Labor

An attempt was made t o determine the competing demand f o r workers a t

o the r cons t ruc t i on p r o j e c t s i n the area. The va r iab les which we def ined

t o capture the concurrent demand f o r cons t ruc t i on workers i n the reg ion

were based upon c r a f t - s p e c i f i c l abo r requirements o f o the r power p l a n t

cons t ruc t i on p r o j e c t s i n t he area.3 Distances o f 50 and 120 m i les

around the s i t e were used t o de f i ne two independent demand var iab les . I n

add i t ion , two va r iab les were def ined t o r e f l e c t t h e change i n the

reg iona l demand f o r l abo r between the year cons t ruc t i on began on the

p r o j e c t and t h e year i n which t h e survey was conducted.

These f o u r va r i ab les were as fo l l ows :

a concurrent labor demand w i t h i n a 50 -m i le rad ius o f t h e s i t e (DDR50) ;

a concurrent labor demand w i t h i n a 120-mi le rad ius o f t h e s i t e (DDR120) ;

a change i n concurrent labor demand w i t h i n a 50-mi le rad ius o f t h e s i t e (CHDDR50) ; and

a change i n concurrent labor demand w i t h i n a 120-mi le rad ius o f the s i t e (CHDDR120).

These data on concurrent labor demand were n o t a v a i l a b l e f o r the

nonconstruct ion workforce. As a r e s u l t , two a l t e r n a t i v e va r iab les were

developed and used i n es t ima t ing t h e nonconstruct ion equation. These

va r iab les inc lude:

a t he number o f o ther nuclear power p l a n t s a l ready b u i l t i n t he reg ion (ONB); and

e the number o f o ther nuclear power p l a n t s c u r r e n t l y under cons t ruc t i on i n t he reg ion (ONC).

3 ~ e were r e s t r i c t e d t o o n l y us ing data on power p l a n t cons t ruc t i on because data on o the r cons t ruc t i on a c t i v i t i e s i n the area were n o t ava i l- able.

4. Local Avai 1 a b i l i ty o f Labor

The lack o f data regard ing t h e s i z e of t h e a v a i l a b l e labor supply and

unemployment r a t e s o f cons t ruc t i on workers i n the regions i n quest ion l e d

us t o de f i ne several proxy va r iab les t o capture the v a r i a t i o n i n t he

l o c a l a v a i l a b i l i t y o f labor . The c r a f t s p e c i f i c supply o f l abo r was

p a r t i c u l a r l y d i f f i c u l t t o measure. However, du r ing t h e p r o f i l e analys is ,

we observed a r e l a t i o n s h i p between c r a f t - s p e c i f i c migrant p ropor t ions a t

a s i t e and the d is tance between the s i t e and the nearest h i r i n g h a l l o f

the union l o c a l w i t h j u r i s d i c t i o n over the p ro jec t . Because workers must

r e p o r t t o union h i r i n g h a l l s f o r j ob r e f e r r a l , i t can be argued t h a t

union h i r i n g h a l l s are l i k e l y t o be loca ted near cons t ruc t i on employment

oppor tun i t i es and a l so t h a t workers are more l i k e l y t o l i v e near t h e i r

h i r i n g h a l l s . Accordingly, t he supply o f labor i s l i k e l y t o dec l i ne w i t h

increas ing d is tance from the h i r i n g h a l l s . Based on t h i s not ion, we

developed a proxy v a r i a b l e f o r t he supply of labor . S p e c i f i c a l l y , t h e

v a r i a b l e was def ined as fo l l ows :

0 d is tance from the s i t e t o t h e h i r i n g h a l l o f t h e union l o c a l w i t h j u r i s d i c t i o n over t he p r o j e c t (DLOCAL).

P o t e n t i a l l y , reg iona l popu la t ion s i z e could a l so be used as a proxy

f o r t he supply o f cons t ruc t i on workers a t a s i t e . However, i n our model

popu la t ion could a l so r e f l e c t reg iona l a t t rac t i veness because popu la t ion i s genera l l y associated w i t h the type and amounts o f serv ices a v a i l a b l e

i n an area. I n add i t ion , popu la t ion might r e f l e c t p o t e n t i a l employment

oppor tun i t i es o ther than the nuclear power p l a n t p ro jec t . Thus, al though

the popu la t ion var iab les may r e f l e c t both labor a v a i l a b i l i t y and the

a t t rac t i veness o f the region, the popu la t ion va r iab les are presented here

as p a r t o f t he reg iona l c h a r a c t e r i s t i c s o f an area.

Las t ly , l o c a l unemployment r a t e s prov ide an i n d i c a t i o n o f l abo r

a v a i l a b i l i t y . I n a study o f t h i s nature, one would i d e a l l y l i k e t o

ob ta in c r a f t - s p e c i f i c l o c a l unemployment ra tes . However, l o c a l unemploy-

ment r a t e s ( i .e, unemployment r a t e s a t t h e county l e v e l ) were a v a i l a b l e

on ly f o r the e n t i r e workforce. Nevertheless, we were able t o p r e d i c t

county- level cons t ruc t i on unemployment r a t e s us ing p r e d i c t i n g equat ions

based on s t a t e data. Accordingly, f o u r unemployment va r i ab les were

developed and considered i n t h i s ana lys is :

0 reg iona l o v e r a l l unemployment r a t e (RUN) ;

l o c a l o v e r a l l unemployment r a t e (LUN);

e reg iona l cons t ruc t i on unemployment r a t e (RCUN); and

l o c a l cons t ruc t i on employment r a t e (LCUN).

Again, n o t a l l o f t he above va r iab les were inc luded i n es t imat ing the

nonconstruct ion equation. Distance from the union h i r i n g h a l l and con-

s t r u c t i o n unemployment ra tes , f o r example, were n o t considered t o be

appropr ia te f o r t he nonconstruct ion subgroup. Therefore, on ly the

reg iona l o v e r a l l unemployment r a t e (RUN) and the l o c a l o v e r a l l unemploy-

ment (LUN) r a t e were used as measures o f l o c a l labor a v a i l a b i l i t y i n

es t ima t ing the nonconstruct ion equation.

5. Regional Charac te r i s t i cs

Several va r i ab les were def ined t o capture t h e c h a r a c t e r i s t i c s o f t h e

reg ion surrounding the s i t e . These var iab les were def ined i n an e f f o r t

t o determine the r e l a t i v e a t t rac t i veness o f t h e area t o i nm ig ra t i ng

workers. Populat ion, average community s i z e and housing a v a i l a b i l i t y

va r i ab les were inc luded among these reg iona l c h a r a c t e r i s t i c var iab les .

The prec ise measures used, however, were o f t e n d i c t a t e d by the a v a i l -

a b i l i t y o f data, which a t t he county and community l e v e l was severely

l i m i t e d i n years o the r than census years. The f o l l o w i n g reg iona l charac-

t e r i s t i c var iab les were considered i n es t imat ing both the cons t ruc t ion

and nonconstruct ion equations:

e Regional popu la t ion (RPOP);

Growth i n reg iona l popu la t ion (RPOPGR);

e Average s i z e o f comnunities w i t h i n 10 m i les of t h e s i t e ( COMSZ 10) ;

e Average s i z e o f comnunities w i t h i n 25 mi les of t h e s i t e ( COMSZ25) ;

e Housing vacancy r a t e (VACRT);

Percent owner-occupied housing ( PCTOWN) ;

e Number o f housing u n i t s per c a p i t a (PCHSG) ;

Number o f mobi 1 e homes ( PCMH) ; and

e Regional per c a p i t a income (RPCI).

6. Contro l Var iables

I n add i t i on t o t h e above var iables, we i d e n t i f i e d a number of o the r

va r i ab les which could a l so serve t o exp la in t h e v a r i a t i o n i n migrant

p ropor t ions across s i t es , and among var ious worker groups. These

included:

8 A d u m y v a r i a b l e t o i d e n t i f y workers f rom scarce c r a f t s (SCAR);

8 A dumy v a r i a b l e t o i d e n t i f y workers from common c r a f t s (COM) ;

e A dummy v a r i a b l e t o i d e n t i f y t he type o f r e a c t o r (TYPE) ; and

8 The s i z e o f u n i t s ( i n megawatts) under cons t ruc t i on a t the s i t e (MWATT) .

A s i m i l a r se t o f c o n t r o l va r i ab les was used i n es t ima t ing t h e noncon-

s t r u c t i o n equation. However, ins tead o f us ing the SCAR and COM dummy

var iab les , a management-clerical dumy v a r i a b l e was used. The v a r i a b l e

was def ined as fo l l ows :

8 A dummy v a r i a b l e t o i d e n t i f y management workers (MGCL).

F i n a l S p e c i f i c a t i o n

The s e l e c t i o n of t h e f i n a l s p e c i f i c a t i o n was made based on empi r ica l

examination of the est imated equat ions under a l t e r n a t i v e s p e c i f i c a t i o n s ,

i.e., i n c l u s i o n and exc lus ion o f d i f f e r e n t sets o f var iab les . The

decis ions regard ing i n c l u s i o n and exc lus ion o f var iab les , as w e l l as the

r e t e n t i o n o f va r i ab les i n t he equation, was based upon several consider-

at ions .

A l l va r i ab les which were de f ined t o r e f l e c t t h e same exp lanatory

f a c t o r were examined f o r c o l i n e a r i t y . Var iables which had simple corre-

l a t i o n c o e f f i c i e n t s o f .7 or more o r which were a l t e r n a t i v e measures o f t he same c h a r a c t e r i s t i c , were n o t inc luded i n the equat ion s imul ta-

neously. I n such cases, s e l e c t i o n o f t h e v a r i a b l e f o r i n c l u s i o n i n t he

f i n a l s p e c i f i c a t i o n was made based upon a comparison o f the performance

o f t h e va r iab les i n var ious regress ion equations ( i .e., t h e v a r i a b l e 2 which improved the R t h e most o r had the most s i g n i f i c a n t c o e f f i c i e n t

was se lec ted) .

Var iables which were def ined t o r e f l e c t d i f f e r e n t explanatory f a c t o r s

were a lso tes ted f o r c o l i n e a r i t y . Between co l inear va r i ab les ( v a r i a b l e s

w i t h simple c o r r e l a t i o n c o e f f i c i e n t s o f .7 o r more) t h e v a r i a b l e which we

selected f o r i n c l u s i o n i n the f i n a l s p e c i f i c a t i o n was the v a r i a b l e which,

i n our judgment, had a st ronger t h e o r e t i c a l bas is f o r i n c l u s i o n i n t he

equation. I n cases i n which we had no a p r i o r i t h e o r e t i c a l bas is f o r

making t h i s determinat ion, we se lec ted t h e v a r i a b l e which had h igher 2 explanatory power (i.e., y i e l d e d a h igher increase i n R ) .

F i n a l l y , h i g h l y i n s i g n i f i c a n t va r i ab les were examined t o determine

whether o r no t they were i r r e l e v a n t t o our spec i f i ca t i on . A v a r i a b l e was

considered t o be i r r e l e v a n t i f ( a ) i t s ' t i va lue was l e s s than 1, ( b ) t h e

magnitude o f i t s s tandard ized b e t a c o e f f i c i e n t was r e l a t i v e l y smal l , and

( c ) i n c l u s i o n o r exc lus ion o f t h e v a r i a b l e s f r om t h e est imated equat ion

d i d n o t s i g n i f i c a n t l y a l t e r t h e magnitude o r s i g n i f i c a n c e o f o t h e r coe f-

f i c i e n t est imates. A l l such v a r i a b l e s were excluded f rom t h e f i n a l

s p e c i f i c a t i o n . The o n l y excep t ions t o t h i s occur red i n the case o f

i n t e r a c t i o n terms. I n general , i n t e r a c t i o n terms were avoided. They

were i nc l uded o n l y i f very s t r ong p r i o r b e l i e f o r t h e o r e t i c a l j u s t i f i c a -

t i o n e x i s t e d f o r cons ide r i ng i n t e r a c t i o n s . I n such cases, i n t e r a c t i o n

terms were r e t a i n e d i n t h e f i n a l equa t ion i r r e s p e c t i v e o f t h e i r s i g n i f i -

cance o r c o n t r i b u t i o n t o t h e equat ion.

RESULTS

The r e s u l t s o f t he f i n a l s p e c i f i c a t i o n o f t h e c o n s t r u c t i o n and non-

c o n s t r u c t i o n worker equat ions a re presented i n Tables C-1 and C-2. Both

equat ions performed remarkably we l l , e x p l a i n i n g 71 and 87 percent o f t h e

v a r i a t i o n i n m ig ran t p r o p o r t i o n s among t h e c o n s t r u c t i o n and nonconstruc-

t i o n groups. Va r i ab le c o e f f i c i e n t es t imates were g e n e r a l l y found t o be

s t a t i s t i c a l l y s i g n i f i c a n t and were o f t h e expected s ign. The es t imated

c o e f f i c i e n t s were a l s o found t o be robus t . The s i gn and s i g n i f i c a n c e of

key v a r i a b l e s were n o t s e n s i t i v e t o t he i n c l u s i o n and exc lus ion o f o t h e r

v a r i a b l e s i n t h e equat ion. The r e s u l t s o f t h e c o n s t r u c t i o n and noncon-

s t r u c t i o n worker equat ions a re d iscussed i n g rea te r d e t a i l below.

Cons t ruc t ion Worker Equat ion

As can be seen i n Table C-1, a t o t a l o f 18 v a r i a b l e s were i nc l uded i n

t h e f i n a l s p e c i f i c a t i o n o f t h e c o n s t r u c t i o n worker equat ion. O f these 18

va r i ab les , 16 were s t a t i s t i c a l l y s i g n i f i c a n t a t o r above t h e 90 percent

conf idence l e v e l , and t oge the r t he 18 v a r i a b l e s exp la ined about 71 per-

cen t o f t he v a r i a t i o n i n m ig ran t p ropo r t i ons . Var iab les rep resen t i ng

each o f t h e exp lana to ry f a c t o r s were inc luded i n t he f i n a l s p e c i f i c a -

t i o n . Those v a r i a b l e s which were de f i ned t o cap tu re r e g i o n a l charac te r-

i s t i c s and l a b o r requirements were found t o be t he most impor tan t i n

e x p l a i n i n g the d i f f e r e n c e s i n c r a f t - s p e c i f i c m ig ran t p ropo r t ions across

surveys. With t he excep t ion o f t h e d u r a t i o n o f employment va r i ab les , a l l

v a r i a b l e s were o f t he expected s ign. The r e s u l t s o f t h e reg ress ion w i t h

TABLE C-1

Migrant Propor t ion Regression Results Construct ion

Dependent va r iab le MPROP Ln m P

Mean -1.43

Variable Coe f f i c ien t t

Income Poten t ia l

Ln WAGE 1.58 1.83*

Ln OTlME 3.41 3.92***

Labor Requirements

Ln CONT

Ln DEMP

Ln (DEMP * SCAR)

Ln (DEMP * COM)

Ln (GREMP * D l ) a

Ln (GREMP * ~ 2 ) ~


Ln DDR50

Local A v a i l a b i l i t y o f Labor

Ln DLOCAL .21

Regional Character is t ics

Ln RPOP

RPOPGR

Ln COHSZ25

Ln COMSZlO

Ln VACRT

Control Variables

COM

SCAR

Ln MWATTS

Constant 39.66 6.20***

a where: GREMP ( 1, D l = 1 otherwise, D l = 0

bwhere: GREMP > 1, 02 = 1 otherwise, 02 = 0

TABLE C-2

Migrant Proport ion Regression Results Nonconstruction

Dependent va r iab le Ln MPROP 1 -MPROP

Mean - -26

Variable Coe f f i c ien t t


Ln ONC

Local Avai 1 abi 1 i ty o f Labor

Ln RUN


Ln RPOP

Control Variables

MGCL

Ln MWATT

Constant

respect t o each o f t h e explanatory f a c t o r s i d e n t i f i e d i n equat ion (2 ) a re

b r i e f l y discussed below.

1. Income P o t e n t i a l

For cons t ruc t i on workers, t h e income p o t e n t i a l associated w i t h

employment a t the cons t ruc t i on s i t e i s determined n o t o n l y by t h e i r wage

ra te , b u t a l so by f a c t o r s such as overt ime ra te , f r i n g e b e n e f i t s

received, and the avai 1 a b i l i t y o f t r a v e l a1 lowances. I n addi ton, because

the na ture o f cons t ruc t i on employment ( i .e., t h e i r r e g u l a r i t y o f employ-

ment), a number o f o ther f a c t o r s can a lso i n f l uence income p o t e n t i a l f o r

cons t ruc t i on workers. These inc lude f a c t o r s such as t h e expected cont in-

u i t y and du ra t i on o f employment. These var iab les , however, r e f l e c t d i f -

ferences i n labor requirements associated w i t h p r o j e c t cons t ruc t i on and

are inc luded as p a r t o f our d iscussion o f l abo r requirement var iab les .

Among t h e f o u r va r i ab les de f ined t o capture the v a r i a t i o n i n income

p o t e n t i a l across s i t e s and survey, wage r a t e (WAGE) and over t ime r a t e

(OTIME) were found t o be important i n exp la in ing migrant p ropor t ions .

Both had the expected p o s i t i v e s ign and were s i g n i f i c a n t w i t h the over-

t ime r a t e v a r i a b l e showing a h igher explanatory power than t h e wage r a t e

var iab le . This supports t he b e l i e f t h a t overt ime i s a key component o f

h igh income among cons t ruc t i on workers, and as a r e s u l t serves as an important f ac to r i n a t t r a c t i n g labor from o ther a c t i v i t i e s and areas.

Travel allowances and f r i n g e b e n e f i t s were no t found t o i n f l uence migrant

p ropor t ions i n any s i g n i f i c a n t way.


With respect t o labor requirements, t h ree f a c t o r s were i d e n t i f i e d as

important i n es t ima t ing migrant p ropo r t i on d i f f e r e n t i a l s across c r a f t s

and s i t e s . These th ree f a c t o r s inc lude the expected growth o f employment

o p p o r t u n i t i e s a t the t ime o f t he survey (GREMP), the expected c o n t i n u i t y

o f employment (CONT), and t h e expected du ra t i on o f employment a t t he s i t e

(DEMP).

With respect t o t he expected growth o f employment oppor tun i t i es a t

the t ime o f t he survey, two va r iab les were def ined t o capture whether

employment oppor tun i t i es a t t he cons t ruc t i on s i t e f o r a p a r t i c u l a r c r a f t

I group were a t a prepeak stage (demand f o r labor was expected t o increase) 1 . o r a t a postpeak stage (demand f o r l abo r was expected t o decrease). The

1 expected growth o f employment oppor tun i t i es a t t he t ime o f t h e survey I ' (GREMP) was def ined as the r a t i o of the number o f workers i n a p a r t i c u l a r I c r a f t a t t he t ime o f t h e survey t o t h e h ighes t employment expected du r ing I

t h e remaining cons t ruc t i on period. The value o f t h i s v a r i a b l e r i s e s from l

a small f r a c t i o n t o 1 dur ing t h e pe r iod i n which employment i s growing, I l

and becomes greater than 1 dur ing the subsequent per iods when the employ-

I ment a t a s i t e i s decl i n ing . Since one would expect migrant p ropor t ions

I t o r i s e dur ing the pe r iod o f inc reas ing employment and dec l ine dur ing the

I pe r i od o f decreasing employment, we d i d n o t en te r t he GREMP va r iab le

I d i r e c t l y . Instead, two va r iab les based on GREMP were def ined. F i r s t , we

1 de f ined GREMP*Dl (where D l = 1 i f GREMP - < otherwise D l = 0) t o capture

I t h e i n f l uence o f inc reas ing u t i l i z a t i o n o f l abo r on migrant p ropor t ion .

I S i m i l a r l y , we def ined GREMP*D2 (where D2 = 1 i f GREMP > 1, otherwise D2 =

I 0) t o capture the i n f l uence o f decreasing u t i l i z a t i o n o f labor on migrant

1 p ropor t ions . The c o e f f i c i e n t est imates o f both va r iab les were s i g n i f i -

I cant and had the expected sign. These r e s u l t s i n d i c a t e t h a t the greater

t h e expected increase i n u t i l i z a t i o n o f labor f o r a p a r t i c u l a r c r a f t , t h e

h igher the migrant p ropo r t i on and, s i m i l a r l y , the greater the expected

decrease i n u t i l i z a t i o n o f labor f o r a p a r t i c u l a r c r a f t , t h e lower the migrant porpor t ion . This n o t i o n was conf irmed by the h i g h l y s i g n i f i c a n t

and p o s i t i v e s ign o f t h e c o e f f i c i e n t est imate o f t h e c o n t i n u i t y v a r i -

able. I n o ther words, c r a f t s w i t h greater c o n t i n u i t y o f employment were

associated w i t h h igher migrant p ropor t ions . However, a s i m i l a r associa-

t i o n between pro jec ted du ra t i on o f employment (du ra t i on o f employment

a l so serv ing t o increase p o t e n t i a l income associated w i t h the move) and

migrant p ropor t ions was no t found t o e x i s t .

I n fact, t h e du ra t i on v a r i a b l e (DEMP) c o e f f i c i e n t est imate n o t o n l y

was of opposi te sign, b u t was a lso s i g n i f i c a n t . Th is would suggest t h a t

t he re are factors, o ther than income p o t e n t i a l , which are r e l a t e d t o t h e

du ra t i on v a r i a b l e and are n o t separa te ly considered i n the est imated

equat ion. These f a c t o r s i n f l uence migrant p ropor t ions i n t he opposi te

d i r e c t i o n . And, the i n f l uence o f these f a c t o r s i s l a r g e r than the

expected ef fect of t h e income p o t e n t i a l associated w i t h the du ra t i on

va r iab le .

One such f a c t o r might be t h e r e l a t i o n s h i p between du ra t i on o f employ-

ment f o r p a r t i c u l a r c r a f t s and the r e l a t i v e a v a i l a b i l i t y o f these workers

i n the area i n which t h e s i t e i s located. Indeed, those c r a f t s w i t h the

shor tes t expected du ra t i on are l e a s t l i k e l y t o have adequate numbers o f

workers a v a i l a b l e i n t he reg ion surrounding t h e s i t e . Jobs o f a l i m i t e d

durat ion, i n general, tend t o r e q u i r e more spec ia l i zed s k i l l s and there-

fore workers from these c r a f t s are scarce i n r e l a t i v e l y r u r a l areas--the

t y p i c a l l o c a t i o n of most nuclear power p lan ts . The c r a f t s which have the

longest du ra t i on a t nuclear power p l a n t s i t e s , on the o ther hand, are the

u n s k i l l e d c r a f t s such as laborers. Typ i ca l l y , these have t h e lowest

migrant p ropor t ions s ince they are more r e a d i l y a v a i l a b l e l o c a l l y .

Thus, we attempted t o est imate the e f f e c t o f the du ra t i on v a r i a b l e on

migrant p ropo r t i ons separa te ly f o r t he scarce, comnon, and abundant c r a f t

groups. This was done by i n t e r a c t i n g dummy va r iab les f o r t he scarce and

comnon c r a f t groups w i t h DEMP. (DEMP*SCAR) and (DEMP*COM) were i n t r o -

duced i n t o the equat ion i n a d d i t i o n t o DEMP t o capture t h e r e l a t i o n s h i p

between migrant p ropor t ions and DEMP separa te ly f o r workers grouped i n t o 4

t h ree s c a r c i t y groups . I n s p i t e of t h i s , we were unable t o ob ta in t h e

expected assoc ia t ion f o r any o f the c r a f t groups. Since the c o e f f i c i e n t

est imate o f DEMP*SCAR was small and extremely i n s i g n i f i c a n t , i t imp l i ed

t h a t t he re was no s i g n i f i c a n t d i f f e r e n c e i n the assoc ia t ion between DEMP

and migrant p ropor t ions f o r workers f rom the scarce and abundant

( l abo re rs and teamsters) c r a f t groups. However, the c o e f f i c i e n t est imate

o f DEMP*COM was s i g n i f i c a n t . This imp l ied t h a t t h e assoc ia t i on i n ques-

t i o n was d i f f e r e n t f o r workers from common c r a f t groups. One should no te

t h a t al though t h e c o e f f i c i e n t est imate o f DEMP*COM was p o s i t i v e , i t was

smal ler than the c o e f f i c i e n t est imate o f DEMP. Since the e f f e c t of

inc reas ing DEMP on the migrant p ropor t ions f o r workers f rom comnon c r a f t s

i s obta ined by summing the two c o e f f i c i e n t s , the e f f e c t was shown t o be

negat ive.

4 ~ h e COM and SCAR va r iab les are durrmy va r iab les def ined t o assume a value of 1 f o r common c r a f t s and scarce c r a f t s , respec t i ve l y ; and zero otherwise.

3. Competing Demand fo r Labor The competing demand for workers from various c r a f t s a t other power

plant construction projects i n the region (DDRG50) was found t o be re la ted t o migrant proportions. The competing demand estimate was found t o be highly s ign i f ican t and posit ive. The competing demand variable which was based upon a 50-mile radius surrounding the construction entered the equation; however, the similar variable based upon 120lnile

radius did not prove t o be useful in explaining the differences in mi grant proportions across c r a f t s . This evidence suggests tha t power plant construction projects within comnuti ng distance of the nuclear power plant draw workers from the same labor pool. However, i n the case of more d i s tan t power plant construction projects, the impact of t h i s fac to r on migrant proportion i s ins ignif icant . Change in competing demand for labor between the year construction began on the project and the year in which the survey was conducted did not enter the f i na l equa- t ion .

4. Local Avai 1 abi 1 i t y of Labor The lack of data regarding t he s i z e of the available labor supply and

unemployment r a t e s of construction workers in the regions in question led us to define several proxy variables to capture the variat ion i n the local ava i l ab i l i t y of labor. However, several of these variables, such as regional population and average comnunity s ize , could serve as proxies fo r both regional a t t ract iveness and the local ava i l ab i l i t y of labor. The supply of labor implications of these variables are included in our discussion of the regional cha rac t e r i s t i c variables.

During our p ro f i l e analysis , we had observed a re la t ionship between craf t- specif ic migrant proportions a t a s i t e and the distance between the s i t e and the hi r ing hall of t he union local w i t h jur isdic t ion over the project . Because workers must report t o union hi r ing ha l l s f o r job r e f e r r a l , i t can be argued t h a t union hiring ha l l s are l i ke ly t o be located near construction employment opportunit ies and a1 so t ha t workers

are more l i ke ly t o l i v e near t h e i r hir ing ha l l s . Thus, f o r the purpose of t h i s analysis we used distance from the s i t e t o the hir ing hal l of the

union local w i t h jur isdic t ion over the project (DLOCAL) has a proxy fo r

the local ava i l ab i l i t y of labor. As expected, the coeff ic ient est imate

was found t o be p o s i t i v e and s i g n i f i c a n t . Since t h e f u r t h e r a construc-

t i o n s i t e i s loca ted from the union h i r i n g h a l l o f a p a r t i c u l a r c r a f t the

lower t h e l o c a l a v a i l a b i l i t y o f labor , one would expect t o observe h igher

migrant p r o p o r t i o n among the c r a f t groups which have h i r i n g h a l l s a t

g rea ter d is tance from the cons t ruc t i on s i t e .

5. Regional Charac te r i s t i cs

Regional c h a r a c t e r i s t i c s were in t roduced as measures o f t h e a t t r a c-

t iveness o f t h e region. However, as mentioned above, some o f these v a r i -

ables cou ld a l so be considered t o be prox ies o f t he l o c a l a v a i l a b i l i t y o f

labor . Since opposi te s igns are imp l i ed by these two f a c t o r s and there

i s no a p r i o r i reason t o argue which e f f e c t would be dominant, t h e s ign

o f these va r iab les cou ld be e i t h e r p o s i t i v e o r negat ive. I f t h e e f f e c t

due t o l abo r supply was l a r g e r than the e f f e c t due t o reg iona l a t t r a c-

t iveness, then one would expect t o observe a negat ive assoc ia t i on between

these va r iab les and migrant propor t ions.

Among t h e 3 reg iona l c h a r a c t e r i s t i c va r i ab les which cou ld serve as

proxy va r iab les f o r both reg iona l a t t rac t i veness and t h e l o c a l a v a i l a b i l -

i t y o f 1 abor-- regional populat ion, and average community s i zes w i t h i n 10

and 25 m i les o f t h e s i te- - on ly t h e average community s i z e w i t h i n 25 m i les

o f t he s i t e (COMSZ25) was found t o be nega t i ve l y associated w i t h migrant p ropor t ion . A s i m i l a r negat ive assoc ia t ion was n o t found i n t h e case of

average community s i z e w i t h i n 10 m i les o f the s i t e (COMSZ10). The oppo-

s i t e signs o f these c o e f f i c i e n t s cou ld be i n t e r p r e t e d as suggest ing t h a t

average community s i z e very near t he s i t e ( w i t h i n 10 m i l e s ) serves more

as a proxy f o r a t t rac t i veness because the l a r g e s t o f these communities

are i n v a r i a b l y t o o small t o p rov ide a s i g n i f i c a n t pool o f cons t ruc t i on

workers. Such i s , o f course, n o t t h e case when one considers comnunit ies

loca ted w i t h i n 25 m i les o f t he s i t e . The a t t rac t i veness e f f e c t i s

c l e a r l y dominant i n the case o f reg iona l popu la t ion (RPOP).

The c o e f f i c i e n t est imates o f the two remaining reg iona l v a r i a b l e s

(housing vacancy r a t e and popu la t ion growth) were a l so found t o be h i g h l y

s i g n i f i c a n t . Housing vacancy r a t e (VACRT) was found t o be the most

important v a r i a b l e i n exp la in ing t h e migrant p ropor t ions across s i t e s .

Higher vacancy r a t e s were associated w i t h h igher migrant p ropor t ions .

Population growth (RPOPGR) was found to be negatively associated with migrant proportions. This resul t appears to suggest that population growth may be regarded by movers as a negative quality of a region. This i s not unreasonable, since rapid population growth can be associated with

shortage of housing and various services, which may be important elements i n the decision process of inmigrating workers.

6 . Control Variables Three variables i n t h i s category were included in the final equa-

tion. Two were dummy variables to capture the remaining mean differences

among workers from the three scarcity groups. Only the dumny variable for workers from common c ra f t ( C O M ) was found t o be s t a t i s t i c a l l y signif-

icant. This suggests that holding other variables constant, on average, workers from the common c ra f t group have lower migrant proportions than workers from the other c raf t groups. The f inal control variable which we included was a variable which ref lec ts the s ize ( in megawatts) of the units under construction (MWATTS). The positive and highly significant coefficient estimate indicates that larger plants, on average, have higher migrant proportions associated with construction than one might

have expected.

Nonconstruction Worker Equation

In the case of the nonconstruction worker equation the final specification was much simpler. As can be seen in Table C-2, only 5 variables

were included in the f inal specification. A single dummy variable which was defined to capture the average differences between management and cler ical workers was found to explain almost 75 percent of the variation in the dependent variable. However, four other variables--regional popu- 1 ation, regional unemployment ra te , number of other nuclear power plants under construction in the region, and plant size--also entered the f ina l

equation. These variables helped to explain only an additional 12 percent of the variation in migrant proportions among nonconstruction workers. All four variables were s ignif icant a t or above the 95 percent

conf i dence 1 eve1 . The specific vari,ables which were included in the nonconstruction

worker equation differed to a large extent from those which were included

i n the construction worker equation. The single most important variable

in the nonconstruction worker equation was the management-clerical dumny (MGCL) . This imp1 ies tha t the variation in migrant proportions among nonconstruction workers i s mostly due to differences i n migrant propor-

tions of the management and cler ical groups. The management workers had very high migrant proportions and the cler ical workers very low migrant proportions.

The coefficient estimates of the overall unemployment r a t e i n the region ( R U N ) and the regional population (RPOP) were both found to be negative and highly s ignif icant . The unemployment ra te variable can be interpreted to mean that i f there i s a higher avai labi l i ty of labor in

the area, one would expect to observe lower migrant proportions. The regional population variable, on the other hand, could r e f l ec t the general attractiveness of the area t o inmigrating workers or could

re f lec t the s ize of the pool of local labor. The observed negative coef- f i c i en t estimate suggests that with increasing regional population, the e f fec t of the associated larger number of locally available workers i s greater than the effect of the associated increased attractiveness of the area.

The number of other nuclear power plants currently under construction i n the region ( O N C ) was entered into the equation as an indication of the competing demand for labor. However, the estimated coefficient of the variable had an unexpected negative sign. I t i s possible that the nega- t ive coefficient of t h i s variable i s a reflection of the stage of project completion of the other power plants. In general these plants were far- ther along than our study s i t e s . Thus , i t i s possible tha t workers were transferred from these plants to the s i t e s included in our study. How- ever, owing to the proximity of the s i t e s , many workers d i d not have to

move because they lived within commuting distance of both construction

s i t e s .

Finally, the s ize of the units under construction (MWATTS) entered the equation and had an expected positive sign. Thus, as was observed in

the construction worker equation, larger plants also have greater migrant proportions among the i r nonconstruction workers. This relationship was

found to be very significant. Unfortunately, detailed labor requirement data were not available for

the nonconstruction workforce. Indeed, the only variable which was

a v a i l a b l e f o r t he nonconstruct ion group was the number o f workers on s i t e

a t t he t ime o f the survey. Th is va r i ab le , however, d i d no t en ter the

f i n a l nonconstruct ion worker equation.

DEFINITION OF VARIABLES - MIGRANT PROPORTIONS

I. Income Potential

A. Wage rate (WAGE)--the straight-time hourly wage rate (first

shift) for a journeyman as specified in the collective bargaining

agreement of the union local with jurisdiction over the project.

B. Overtime rate (0TIME)--the daily overtime rate (i .e., double-time

was defined as "2.0").

C. Fringe benefits (FRINGE)--the total dollar value of all fringe

benefits paid per hour worked.

D. Travel allowance (TALLOW)--a dummy variable indicating whether or

not a particular craft had a travel allowance provision specified

in its collective bargaining agreement.


A. Expected continuity of employment (C0NT)--the number of quarters

in which projected average daily employment for a particular

craft is greater than or equal to the average daily employment of

the previous quarter.

B. Expected duration of employment (DEMP)--the number of quarters in

which projected average daily employment for a particular craft is greater than or equal to 25 percent of the highest projected

average daily employment for any quarter.

C. Expected growth of employment opportunities at the time of the

survey (GREMP)--the ratio of the number of workers of a partic-

ular craft on site at the time of the survey to the projected

average dai ly employment of the four highest consecutive quarters

over the remaining construction period.

D. Total projected employment (TEMP)--the total number of man-hours

projected for a craft over the entire construction period.

E. Number of workers on site at the time of the survey (NCRAFT)--the

number of workers of a particular craft who completed the con-

struction worker survey.

F. Overall stage of project completion (PEAK)--a dummy variable

indicating whether or not total employment at the site had

reached the peak stage (had been relatively constant over a

period of time) .

G. Expected peak employment (NPEAK)--the projected average daily employment for a particular craft for the highest projected quar-

ter.

H. Expected duration of peak (DPEAK)--the number of quarters in

which projected average daily employment for a particular craft

is greater than or equal to 75 percent of the highest projected

average daily employment for any quarter.

111. Competing Demand for Labor

A. Concurrent labor demand within a 50-mile radius of the site

(DDR5O)--the average annual labor requirements for a particular

craft (in thousands of man-hours) at all other power plant con-

struction projects within 50 miles of the site over the period of

construct ion (from the year construct ion began through the year

of the survey).

B. Concurrent labor demand within a 120-mile radius of the site

(DDR120) --the average annual 1 abor requirements for a particular

craft (in thousands of man-hours) at all other power plant con-

struction projects within 120 miles of the site over the period

of construction (from the year construction began through the

year of the survey). C. Change in concurrent labor demand within a 50-mile radius of the

site (CHDDR50)--the change in labor requirements for a particular

craft (in thousands of man-hours) at a1 1 other power plant con-

struction projects within 50 miles of the site over the period of construct ion (the difference between requirements in the year

construction began and the year of the survey).

D. Change in concurrent labor demand within a 120-mile radius of the

site (CHDDR120)--the change in labor requirements for a partic-

ular craft (in thousands of man-hours) at all other power plant

construction projects within 120 miles of the site over the

period of construction (the difference between requirements in

the year construct ion (the difference between requirements in the

year construction began and the year of the survey).

E. Other nuclear power plants already built in the region (0NB)--the

total number of other nuclear power plant units already completed

within 50 miles of the construction site.

F. Other nuclear power plants currently under construction in the region (0NC)--the total number of other nuclear power plant units

currently under construction within 50 miles of the construction

site.

IV. Local Availability of Labor

A. Distance to the union hiring ha1 1 (DL0CAL)--the distance (in

miles) from the construction site to the hiring hall of the union

local with jurisdiction over the project.

B. Regional overall unemployment rate (RUN)--the average unemploy-

ment rate (weighted by civilian labor force) of all counties in

the region within 50 miles of the construction site over the

period of construction (from the year construction began through

the year of the survey).

C. Local overall unemployment rate (LUN)--the average unemployment

rate (weighted by civilian labor force) of all counties in the

local area (the county in which the site is located plus any

adjoining county within 15 highway miles of the site) over the

period of construction (from the year construction began through

the year of the survey).

D. Regional construction unemployment rate (RCUN)--a construction unemployment rate for the region calculated from the overall

unemployment rate as defined above (RUN) based upon a relation-

ship derived from data at the state level.

E. Local construction unemployment rate (LCUN)--a construction unemployment rate for the local area calculated from the overall

unemployment rate as defined above (LUN) based upon a relation-

ship derived from data at the state level.

V . Regional Characteristics

A. Regional population (RP0P)--total population of all counties

within 50 miles of the construction site for the year in which

construction began.

B. Growth in regional population (RP0PGR)--change in the population

of the region (all counties within 50 miles of the site) between

1970 and 1975 expressed as a proportion of the 1970 population.

C. Averaae size of communities within 10 miles of the site

(COMSZ10)--the total population of communities within 10 miles of the construction site divided by the number of communities.

D. Averaae size of communities within 25 miles of the site

(COMSZ25)--the total population of communities within 25 miles of

the construction site divided by the number of communities.

E. Housing vacancy rate (VACRT)--the number of vacant units divided

by total housing units in 1970 for counties in the local area

multiplied by 100.

F . Percent owner-occupied housing (PCTOWN) --owner-occupied housing units as a proportion of all occupied housing units in 1970 for

counties in the local area.

G. Number of housing units per capita (PCHSG)--total housing units

in the local area in 1970 divided by the 1970 population.

H. Number of mobile homes per capita (PCMH)--total number of mobile

homes in the local area in 1970 divided by the 1970 population.

I. Regional per capita income (RPC1)--weighted average of per capita

income (weighted by population) of counties within 50 miles of

the site for the year construction began.

VI. Control Variables A. Scarce (SCAR)--a dummy variable indicating whether or not a craft

belonged to the scarce craft group.

B. Common (C0M)--a dummy variable indicating whether or not a craft

belonged to the common craft group.

C. ---a dummy variable indicating whether a particular reactor is a pressurized water reactor or a boiling

water reactor.

D. Size of units (MWATT)--the total number of megawatts in a1 1 units under construction at the site.

E. Management (MGCL) --a dummy variable indicating whether or not

nonconstruction workers belonged to the management group.

APPENDIX D

RESIDENTIAL LOCATION MULTIVARIATE ANALYSIS

APPENDIX D

RESIDENTIAL LOCATION MULTIVARIATE ANALYSIS

This Appendix presents a more detailed discussion of the residential

location analysis which was conducted in the multivariate analysis por-

tion of this study. The purpose of the analysis was to explain the

observed variation in residential location patterns of inmigrating

workers across the sites included in our sample. The results of this

analysis served as the basis for specifying procedures for forecasting

residential location patterns at future nuclear power plant construction

sites. The discussion is divided into three sections. The first section

discusses the factors involved in residential location decisions, noting

several factors which may be special considerations of construction

workers. The second section describes the residential location model and

the third section describes the analysis results.

FACTORS INVOLVED IN RESIDENTIAL LOCATION DECISIONS

Numerous factors underlie most residential location decisions.

Decisions are governed by the needs of an individual or family--the pref-

erence for a particular size and housing type--and the availability and cost of housing, as well as the general attractiveness of the area and

the proximity of the location to work, schools, shopping, and various

other services. One important factor, and a factor which is likely to be

of particular importance in the context of this study, is the residential

location with respect to the place of employment. An important factor in many individuals' residential location decisions is the desire to mini-

mize the time and cost associated with the journey-to-work. Since in

this study we focus upon a specific work place, it is logical to examine

residential location patterns of inmigrating workers in terms of the

distance from the construction site.

The special nature of the construction industry has some implications

regarding movers' residential location decisions. Many of the workers

move to the area to work on the project with the intention of leaving the

area upon completion of the project. Especially among the more special-

ized construction crafts, many movers are employed for jobs of rather

limited duration. Some of these movers do not relocate their families.

In fact, many live in the area only during the workweek and return to

t h e i r permanent residence each weekend. It i s q u i t e l i k e l y t h a t min i-

miz ing the t ime and cos t associated w i t h g e t t i n g t o work i s the major

f a c t o r i n t he r e s i d e n t i a l l o c a t i o n decis ions o f these temporary and t ran-

s i e n t movers.

While workers may seek t o l i v e as c lose t o the s i t e as possib le,

o ther f a c t o r s en te r t he r e s i d e n t i a l l o c a t i o n decis ion. The importance o f

o ther f ac to rs , however, may d i f f e r f o r d i f f e r e n t groups o f workers. For

example, a worker who re locates h i s fami ly , and i n p a r t i c u l a r a permanent

mover who expects t o remain i n the area upon complet ion o f t h e p ro jec t ,

i s much more l i k e l y t o consider o ther f a c t o r s such as the q u a l i t y o f

schools, shopping and services, and perhaps the l o c a t i o n o f o ther employ-

ment o p p o r t u n i t i e s i n the area. Larger popu la t ion centers i n general

r e f l e c t t h e a v a i l a b i l i t y o f goods and services, i n c l u d i n g t h e a v a i l a b i l t y

o f housing and, as such, may serve t o a t t r a c t i nm ig ra t i ng workers.

Furthermore, because d i f f e r e n t groups o f workers d i f f e r i n t he na ture o f

employment oppor tun i t i es ( i .e., t he expected du ra t i on and c o n t i n u i t y of

employment), i n t h e i r i n t e n t i o n t o remain i n the area, and i n t he l i k e l i -

hood o f r e l o c a t i n g t h e i r f am i l i es , one might a lso expect t o observe d i f-

ferences i n r e s i d e n t i a l l o c a t i o n decisions. Indeed, d i f f e rences i n the

r e s i d e n t i a l l o c a t i o n pa t te rns o f opera t ing and cons t ruc t i on workforces

have been observed a t energy development p r o j e c t s i n t he Great P la ins . 1

I n summary, t he r e s i d e n t i a l l o c a t i o n decis ions o f movers a t a l a r g e

cons t ruc t i on p r o j e c t are l i k e l y t o depend upon the housing a v a i l a b i l i t y ,

reg iona l a t t rac t i veness and workforce composit ion a t the s i t e . We ana-

l y z e the e f f e c t s o f these f a c t o r s on the r e s i d e n t i a l l o c a t i o n decis ions

o f movers among the surveys inc luded i n our sample w i t h i n the framework

of a mod i f ied g r a v i t y model. We use the s p e c i f i c a t i o n o f a g r a v i t y model

o n l y as a s t a r t i n g p o i n t i n the development o f our r e s i d e n t i a l l o c a t i o n

model. The way i n which we modify the g r a v i t y model i n an attempt t o

overcome some o f t he weaknesses o f g r a v i t y models i s described i n t h e

fo l l ow ing sect ion.

IJ. S. Wieland, F. L. L e i s t r i t z , and 5. H. Murdock, " Charac te r i s t i cs and Res iden t i a l Pat terns o f Enerqy-Related Work Forces i n the Northern Great Pla ins," Western Journal o r - ~ ~ r i c u l t u r a l Economics, (Ju ly , 1979), pp. 57-68.

RESIDENTIAL LOCATION MODEL

The g r a v i t y model captures the t rade- of fs between the s i z e of commun-

i t i e s and the d is tance o f communities from t h e i r p lace o f work which

workers face i n making r e s i d e n t i a l l o c a t i o n decis ions. The bas ic form of

the g r a v i t y model i s as fo l l ows :

where :

Iij = t h e number o f workers r e s i d i n g i n community j, who

worked a t s i t e i;

POPj = popu la t ion o f conmunity j;

DISTij = d is tance between community j and s i t e i;

a = the exponent o f populat ion;

B = the exponent o f distance; and

A = the constant o f p r o p o r t i o n a l i t y .

I n the g r a v i t y model, popu la t ion acts as a proxy f o r both the a t t r a c-

t iveness o f a community and the a b i l i t y o f the community t o absorb inmi- grants. Distance, on the o ther hand, acts as a proxy fo r the cos ts (bo th

i n terms o f t ime and money) associated w i t h l o c a t i n g away from one's

p lace o f work. The values o f t he est imated exponents are determined by

the choices made by i n d i v i d u a l s which, i n tu rn , depend upon t h e i r per-

sonal t as tes and preferences, t he nature o f t h e i r employment, and the

geography o f t he reg ion ( i .e., the number, sizes, and types o f communi-

t i e s a v a i l a b l e i n the area surrounding the s i t e s ) . Accordingly, t he

exponents are l i k e l y t o vary across s i t e s and across d i f f e r e n t groups of

workers a t the same s i t e ( i .e., construct ionlnon- construct i o n workers,

s k i 1 l e d l u n s k i l l e d workers). It i s f o r t h i s reason t h a t exponent e s t i -

mates obtained from the es t ima t ion o f a g r a v i t y model a t one s i t e do n o t

u s u a l l y perform very we l l i n p r e d i c t i n g r e s i d e n t i a l l o c a t i o n pa t te rns a t

another s i t e .

To overcome these l i m i t a t i o n s we modify t h e g r a v i t y model t o a l l ow

both popu la t ion and d is tance exponents t o vary across worker groups and

across s i t e s as fo l l ows :

where :

PMOVEi j k = t h e p ropo r t i on o f movers f rom worker group k who work a t s i t e i and res ide i n community j;

popu la t ion o f comnunity j a t s i t e i;

dis tance between community j and s i t e i;

t h e exponent o f popu la t ion a t s i t e i f o r worker group k;

t he exponent o f d is tance a t s i t e i f o r worker group k ;

t h e constant of p r o p o r t i o n a l i t y ;

p r o j e c t c h a r a c t e r i s t i c s a t s i t e i; and

reg iona l c h a r a c t e r i s t i c s o f s i t e i.

A l i n e a r es t ima t ing equat ion o f the f o l l o w i n g form can be s p e c i f i e d

by app ly ing a l oga r i t hm ic t rans format ion t o the above equat ion and assum-

i n g t h a t the popu la t ion (a ) and d is tance ( B ) exponents are a l i n e a r func-

t i o n o f vec tors o f t he reg iona l (Y) and p r o j e c t (X) c h a r a c t e r i s t i c s .

( 3 ) LnPMOVEi jk = LnA + (al + a2Xi + a3Yi)LnPOPi - (bl + b2Xi + b3Yi)

LnDISTij + " i j

This equat ion a l lows each s i t e t o have i t s own popu la t ion and d i s-

tance exponents. The popu la t ion and d is tance exponents i n t h i s equat ion

are g iven by (al + a2Xik + a3Y1) and (bl + b2Xik + b3Yi) respec t i ve l y .

Thus, t h e magnitude o f t h e popu la t ion and d is tance exponents i s no t

f i xed , b u t r a t h e r depends upon the reg iona l and p r o j e c t c h a r a c t e r i s t i c s

of t h e s i t e i n quest ion. Equation (3 ) can be r e w r i t t e n as fo l l ows :

( 4 ) LnPMOVEi = LnA + alLnPOPij + a2XiLnPOPij + a3YiLnPOPij -

where:

LnA, al, a*, a3, bl, bp, and b3 are the c o e f f i c i e n t s

t o be estimated.

We used t h i s very general form o f t he g r a v i t y model t o begin our

empi r ica l work. However, dur ing our p re l im ina ry ana lys is we found two

reasons t o modify our s p e c i f i c a t i o n . F i r s t , the popu la t ion i n t e r a c t i o n

terms and the d is tance i n t e r a c t i o n terms contained i n equat ion (4 ) were

found t o be h i g h l y cor re la ted . This was due t o the f a c t t h a t l a rge r

communities are genera l l y located f a r t h e r from cons t ruc t i on s i t e s and the

same se t o f reg iona l and p r o j e c t c h a r a c t e r i s t i c s were defined t o exp la in

the v a r i a t i o n s i n the popu la t ion and d is tance exponents. Since there was

no st rong t h e o r e t i c a l bas is t o j u s t i f y us ing d i f f e r e n t sets of X and Y

va r i ab les t o exp la in the v a r i a t i o n s i n the popu la t ion and d is tance expo-

nents, i n our ana lys is we rev i sed our s p e c i f i c a t i o n and assumed the popu-

l a t i o n exponent t o be f i x e d f o r a l l s i t e s and allowed o n l y the d is tance

exponent t o vary across s i t es .

Second, we est imated t h e bas ic g r a v i t y model as s p e c i f i e d i n equat ion

( 1) separate ly f o r 3 major worker groups--nonconstruction workers, scarce

cons t ruc t i on c r a f t s and o ther cons t ruc t i on c ra f t s- - fo r each survey t o

conf irm whether o r no t the d is tance exponents o f the th ree groups were

d i f f e ren t . This hypothesis was tes ted us ing the standard Chow t e s t . We found t h a t i n on l y a few cases were the d is tance exponents found t o be

s i g n i f i c a n t l y d i f f e r e n t among worker groups a t a s i t e . Accordingly, we

rev i sed our s p e c i f i c a t i o n t o a l l ow the g r a v i t y model exponents t o vary

across s i t e s b u t no t across worker groups. The s p e c i f i c a t i o n which was

f i n a l l y est imated was as fo l l ows :

( 5 ) LnPMOVEij = LnA + aLnPOPij + blLnDISTi - b2XiLnDISTi

D e f i n i t i o n o f Var iables

Several var iab les were def ined t o capture the i n f l uence of the v a r i -

ous reg iona l and p r o j e c t c h a r a c t e r i s t i c s upon the d is tance exponent. I n

general 4 groups o f va r i ab les were examined. These inc lude reg iona l

a t t rac t iveness , housing a v a i l a b i l i t y , workforce composit ion and o the r

p r o j e c t c h a r a c t e r i s t i c s and c o n t r o l var iables. The s p e c i f i c va r i ab les

which were examined i n each group a re discussed b r i e f l y below. The pre-

c i s e v a r i a b l e d e f i n i t i o n s are inc luded a t t h e end o f t h i s appendix.

1. Reaional A t t r a c t i v e n e s s

Several v a r i a b l e s were de f i ned i n an at tempt t o r e f l e c t t h e a t t r a c-

t i veness o f t he area t o i n m i g r a t i n g workers. These v a r i a b l e s i nc l ude :

e d i s tance f rom t h e s i t e t o t he neares t SMSA (DSMSA) ;

e employment i n t he r e t a i l t r ade i n d u s t r y i n t h e l o c a l area (RETEMP) ;

employment i n the s e r v i c e i n d u s t r i e s i n the l o c a l areas (SVCEMP);

e popu la t i on growth i n t he l o c a l area (LPOPGR); and

e pe r c a p i t a income i n t he l o c a l area (LPCI).

D is tance f rom t h e neares t SMSA and pe r c a p i t a income were inc luded t o

cap tu re t h e general a t t r a c t i v e n e s s o f t h e area immediate ly surrounding

t he s i t e . S i m i l a r l y , employment i n t he s e r v i c e i n d u s t r i e s and employment

i n t h e r e t a i l t r a d e i n d u s t r i e s i n t he l o c a l area were inc luded as surro-

gates f o r ameni t ies and se rv i ces i n nearby communities. F i n a l l y , popula-

t i o n change i n t h e l o c a l area was inc luded because r a p i d p o p u l a t i o n

growth i n t h e area immediate ly surrounding t he s i t e cou ld be assoc ia ted

w i t h shortages o f housing and var ious serv ices, f a c t o r s which c o u l d

i n f l u e n c e movers' r e s i d e n t i a l l o c a t i o n pa t t e rns .

The d i s t r i b u t i o n o f popu la t i on and communities around t h e s i t e a re

impor tan t determinants o f t h e r e s i d e n t i a l l o c a t i o n p a t t e r n s of i nm ig ra t -

i n g workers. To summarize t he popu la t i on and comnunity i n f o r m a t i o n

around a s i t e , we def ined popu la t i on s izes, numbers o f communities and

average community s i z e s f o r va r ious d i s tance i n t e r v a l s f rom t h e s i t e .

S p e c i f i c a l l y , the f o l l o w i n g v a r i a b l e s were considered:

t h e popu la t i on o f comnuni t ies w i t h i n 10, 15, 20, and 25 m i l e s o f t h e s i t e (POP10, POP15, POP20, POP25);

e t h e number o f communities w i t h i n 10, 15, 20, and 25 m i l e s o f t h e s i t e (NCMTY10, NCMTY15, NCMTY20, NCMTY25); and

e t h e avera e s i z e o f comnuni t ies w i t h 10, 15, 20 and 25 m i l e s o f t h e s i t e PcoMszio, COMSZ15, COMSZZO, COMSZ25).

These d i s tance i n t e r v a l s were chosen a r b i t r a r i l y . Several i n t e r v a l s

were se lec ted t o exp lo re t he d i s t r i b u t i o n o f popu la t i on and communit ies

surrounding t h e s i t e i n an e f f o r t t o i d e n t i f y t h e s e t o f v a r i a b l e s which

bes t e x p l a i n t h e r e s i d e n t i a l l o c a t i o n d i f f e r e n c e s across va r i ous worker

groups .


The a v a i l a b i l i t y o f housing i n t h e l o c a l area cou ld be a key de te r-

minant o f t h e r e s i d e n t i a l l o c a t i o n p a t t e r n s o f i n m i g r a t i n g workers.

Accord ing ly , we considered t h e f o l l o w i n g housing a v a i l a b i l i t y v a r i a b l e s

i n t h i s ana lys is :

housing vacancy r a t e (VACRT) ;

m number o f mob i le homes pe r c a p i t a (PCMH);

e percen t owner-occupied hous i n g (PCTOWN) ; and

e number o f housing u n i t s per c a p i t a (PCHSG).

3 . Workforce composi t ion and Other P r o j e c t C h a r a c t e r i s t i c s

We examined severa l v a r i a b l e s i n an at tempt t o capture t he res iden-

t i a l l o c a t i o n preferences o f d i f f e r e n t groups o f workers. Th is was done

by i n t r o d u c i n g v a r i a b l e s de f ined t o r e f l e c t d i f f e r e n c e s i n workforce

composi t ion a t t h e t ime o f t h e survey. These v a r i a b l e s inc luded :

t o t a l number o f movers (NMOVE) ;

e p r o p o r t i o n o f movers f rom scarce c r a f t s (PS);

e p r o p o r t i o n o f movers f rom o t h e r c o n s t r u c t i o n c r a f t s (PO);

e a dummy v a r i a b l e i n d i c a t i n g whether o r n o t t o t a l employment a t t h e s i t e had reached t he peak stage (PEAK); and

e a dumm v a r i a b l e i n d i c a t i n g whether o r n o t t o t a l employment a t r the s i e had reached the postpeak stage (PPEAK).

4. Contro l Var iab les

I n a d d i t i o n t o t he above v a r i a b l e s we i d e n t i f i e d one c o n t r o l v a r i a b l e

which cou ld a l so serve t o e x p l a i n t h e v a r i a t i o n i n r e s i d e n t i a l l o c a t i o n

pa t t e rns . The f o l l o w i n g v a r i a b l e was considered:

e a dummy v a r i a b l e t o i d e n t i f y whether t h e s i t e i s l oca ted i n t h e Nor th o r i n t h e South (REGION).

F i n a l S p e c i f i c a t i o n

The s e l e c t i o n o f t h e s p e c i f i c v a r i a b l e s inc luded i n t h e f i n a l spec i-

f i c a t i o n was made based on e m p i r i c a l examinat ion o f t he es t imated equa-

t i o n s under a l t e r n a t i v e s p e c i f i c a t i o n s , i.e., i n c l u s i o n and exc lus ion of

d i f f e r e n t se t s o f va r i ab les . The dec is ions rega rd ing i n c l u s i o n and

exc lus ion o f va r i ab les , as w e l l as t h e r e t e n t i o n o f v a r i a b l e s i n t he

equat ion, was based upon t h r e e cons idera t ions .

F i r s t , a l l v a r i a b l e s which were de f ined t o cap tu re t h e same f a c t o r

were examined f o r c o l i n e a r i t y . Var iab les which had s imple c o r r e l a t i o n

c o e f f i c i e n t s o f .7 o r more o r which were a l t e r n a t i v e measures o f t he same

c h a r a c t e r i s t i c , were n o t inc luded i n the equat ion simultaneously. I n

such cases, s e l e c t i o n o f t h e v a r i a b l e f o r i n c l u s i o n i n t h e f i n a l s p e c i f i -

c a t i o n was made based upon a comparison of the performance o f the v a r i -

ables i n var ious regression equat ions ( i .e., t h e v a r i a b l e which improved 2 the R t he most o r had the most s i g n i f i c a n t c o e f f i c i e n t was selected) .

Second, va r i ab les which were def ined t o r e f l e c t d i f f e r e n t f a c t o r s

were a l so tes ted f o r c o l i n e a r i t y . Between co l i nea r var iab les ( va r i ab les

w i t h simple c o r r e l a t i o n c o e f f i c i e n t s o f .7 o r more) t he v a r i a b l e which we

selected f o r i n c l u s i o n i n the f i n a l s p e c i f i c a t i o n was the v a r i a b l e which,

i n our judgment, had a st ronger t h e o r e t i c a l bas is f o r i n c l u s i o n i n t he

equat ion. I n cases i n which we had no a p r i o r i t h e o r e t i c a l bas is f o r

making t h i s determinat ion, we selected the v a r i a b l e which had h igher n

exp lanatory power ( i .e., y i e l d e d a h igher increase i n R ~ ) .

F i n a l l y , h i g h l y s i g n i f i c a n t va r i ab les were examined t o determine

whether o r no t they were i r r e l e v a n t t o our s p e c i f i c a t i o n . A v a r i a b l e was

considered t o be i r r e l e v a n t i f (a) i f i t had a h igh ' t ' value, (b ) the

magnitude o f i t s standardized beta c o e f f i c i e n t was r e l a t i v e l y small, and

( c ) i n c l u s i o n o r exc lus ion o f t h e va r iab les from the est imated equat ion

d i d no t s i g n i f i c a n t l y a l t e r the magnitude o r s i g n i f i c a n c e o f o the r coef-

f i c i e n t est imates. A l l such va r iab les were excluded from the f i n a l

s p e c i f i c a t i o n .

RESULTS

The r e s u l t s o f t h e f i n a l s p e c i f i c a t i o n o f t he r e s i d e n t i a l l o c a t i o n

equat ion are presented i n Table D-1. I n general, the equat ion performed

q u i t e we l l , exp la in ing over 60 percent o f the v a r i a t i o n i n r e s i d e n t i a l

l o c a t i o n pa t te rns among the 24 surveys inc luded i n the equation. For the

most par t , v a r i a b l e c o e f f i c i e n t est imates were found t o be s t a t i s t i c a l l y

s i g n i f i c a n t and were o f the expected sign. The est imated c o e f f i c i e n t s

were a lso found t o be robust . The s ign and s i g n i f i c a n c e of key va r iab les

were no t s e n s i t i v e t o the i n c l u s i o n and exc lus ion o f o ther va r i ab les i n

t he equat ion. These r e s u l t s suggest t h a t the explanatory va r iab les

inc luded i n the est imated equat ion do, indeed, capture many of t he fac-

t o r s under ly ing the v a r i a t i o n i n r e s i d e n t i a l l o c a t i o n pa t te rns .

As expected, our m u l t i v a r i a t e ana lys is d i d i n d i c a t e t h a t the propor-

t i o n o f movers l o c a t i n g i n a p a r t i c u l a r comnunity i s p o s i t i v e l y r e l a t e d

TABLE D-1

Restdential Location Regression Results

Dependent vartable Ln PMOVE Mean -4.999

Variable Coef f tc ient t

Ln POP

Ln DIST

Distance In te rac t ion Terms

RETEMP * Ln DIST

DSMSA * Ln DIST

VACRT * Ln DIST

PCMH * Ln DIST

NMOVE * Ln DIST

PS * Ln DIST

PO * Ln DIST

REG I ON

Constant

t o comnunity s i z e (POP), and nega t i ve l y r e l a t e d t o the d is tance from the

cons t ruc t i on s i t e (DIST). Both va r iab les were s i g n i f i c a n t a t t h e 99

percent conf idence l e v e l . E igh t o the r va r i ab les were inc luded i n the

f i n a l s p e c i f i c a t i o n i n an attempt t o capture d i f f e rences i n the d is tance

exponent as a f u n c t i o n o f reg iona l a t t rac t iveness , housing a v a i l a b i l i t y ,

workforce composit ion and o ther p r o j e c t c h a r a c t e r i s t i c s , and c o n t r o l

var iab les . O f these 8 var iab les , 7 were s i g n i f i c a n t a t o r above t h e 95

percent conf idence l e v e l .

I n t h e g r a v i t y model es t ima t ion t h e d is tance c o e f f i c i e n t has a nega-

t i v e s ign ( i n d i c a t i n g an inverse r e l a t i o n s h i p between d is tance and the

dependent v a r i a b l e ) . A h igher d is tance exponent can be i n t e r p r e t e d t o

mean t h a t movers w i l l tend t o l o c a t e nearer the cons t ruc t i on s i t e and a

smal ler d is tance exponent means t h a t movers w i l l tend t o l oca te f a r t h e r

away. I n the modi f ied g r a v i t y model as s p e c i f i e d i n the previous sec-

t i o n , t he est imate o f t h e d is tance exponent i s given by the l i n e a r com-

b i n a t i o n o f the d is tance term and the var ious i n t e r a c t i o n terms. Thus,

t he c o e f f i c i e n t est imates o f t h e i n t e r a c t i o n terms a f f e c t the magnitude

o f the d is tance exponent-- increasing i t i f the c o e f f i c i e n t i s negat ive

and decreasing i t i f t h e c o e f f i c i e n t i s p o s i t i v e . The c o e f f i c i e n t e s t i -

mates of the var ious i n t e r a c t i o n terms can, there fore , be examined t o

determine the i n f l uence of these va r iab les upon the d is tance c o e f f i - c i e n t . The r e s u l t s of t he regress ion equat ion w i t h respect t o each o f

t h e explanatory fac to rs i d e n t i f i e d above are b r i e f l y discussed below.

Regional A t t rac t i veness

Several va r i ab les were def ined t o capture the general a t t rac t i veness

of the area immediately surrounding the s i t e . Two o f these var iables- -

d is tance from the nearest SMSA (DSMSA) and employment i n r e t a i l t rade

i n d u s t r i e s i n t he l o c a l area (RETEMP)--entered the f i n a l equation. The

negat ive c o e f f i c i e n t est imate o f t he r e t a i l t rade v a r i a b l e imp l i es t h a t

s i t e s w i t h h igher r e t a i l t rade a c t i v i t y i n the l o c a l area are more l i k e l y

t o have h igher p ropor t ions o f movers l i v i n g c lose t o the s i t e than are

s i t e s w i t h lower r e t a i l a c t i v i t y i n t he l o c a l area. S i m i l a r l y , w i t h

respect t o d is tance from the nearest SMSA, t he p o s i t i v e c o e f f i c i e n t e s t i -

mate i nd i ca tes t h a t those s i t e s a t g rea ter distances from the nearest

SMSA have smal ler d is tance exponents and the re fo re lower p ropor t ions of

movers living in communities near the construction site. Sites which are

located nearer SMSA's, on the other hand, have correspondingly higher

proportions of movers living in communities immediately surrounding the

construction site. Thus, evidence suggests that workers prefer to live

closer to SMSAs. These results are consistent with what one would expect

to observe. The estimated coefficient of the retail trade variable was

significant at the 95 percent confidence level. In the case of the dis-

tance from the nearest SMSA, however, the coefficient was not found to be

significantly different from zero at the 90 percent confidence level.

In addition, we examined the importance of several variables which

were intended to capture distribution of population and communities sur-

rounding the construction site. To summarize the population and commun-

ity characteristics of a site, we defined population sizes, numbers of

communities and average community sizes for various distance intervals

from the site. These variables, however, did not enter our final equa-

tion.

Housing Availability

The availability of housing in the local area is clearly a factor in the residential location decisions of inmigrating workers. Accordingly,

we considered the following housing availability variables in this analysis: housing vacancy rate (VACRT); percent owner-occupied housing

(PCTOWN) ; number of housing units per capita (PCHSG) ; and number of

mobile homes per capita (PCHH). Two of these variables, namely vacancy

rate and number of mobile homes per capita, entered the final equation. As expected, both coefficient estimates were negative and highly signifi-

cant. Thus, these results indicate that higher vacancy rates and mobile

homes per capita in the local area are associated with higher proportions

of movers living in nearby communities. The importance of mobile homes

reflects the temporary nature of employment in the construction indus-

try . 2

2 ~ n our profile analysis we observed that rather large proportions of movers 1 ive in mobile homes, especially in Southern sites. Twenty of the 24 surveys included in this analysis were conducted at Southern sites.

Workforce Composition and Other P r o j e c t Charac te r i s t i cs

I n add i t ion , several va r i ab les were examined i n an attempt t o capture

t h e r e s i d e n t i a l l o c a t i o n preferences o f d i f f e r e n t groups of movers. This

was done by i n t roduc ing va r iab les def ined t o r e f l e c t d i f f e rences i n work-

f o r c e composit ion a t t he s i t e a t t h e t ime o f t he survey. Three such

var iab les- - to ta l number o f movers a t t he s i t e (NMOVE), p ropor t ions o f

movers from the scarce c r a f t s (PS), and p ropo r t i on o f movers from the

common and abundant c r a f t s (PO)--were inc luded i n the f i n a l equation.

Our r e s u l t s i n d i c a t e t h a t t he t o t a l number o f movers i s an important

var iab le . As the t o t a l number o f movers increases, h igher p ropo r t i ons o f

movers tend t o l oca te nearer t he cons t ruc t i on s i t e . S i m i l a r l y , i f t h e

the p ropo r t i on o f cons t ruc t i on movers i s h igher (compared w i t h noncon-

s t r u c t i o n movers), then one observes h igher p ropor t ions o f movers l i v i n g

nearer the cons t ruc t i on s i t e . Among cons t ruc t i on movers, i f the propor-

t i o n o f movers from.scarce c r a f t s i s higher, then h igher p ropo r t i ons o f

movers are l i k e l y t o l i v e c lose r t o t he s i t e . This i s cons i s ten t w i t h

t h e d i f f e rences i n the p o t e n t i a l du ra t i on of employment a t the s i t e among

the var ious worker groups. C lear ly , movers whose employment p o t e n t i a l a t

t h e s i t e i s o f a sho r te r du ra t i on are w i l l i n g t o l i v e c lose r t o t h e s i t e

than o the r workers, desp i te the r e l a t i v e l y l ess a t t r a c t i v e communities

and a v a i l a b l e housing c l o s e r t o t h e s i t e . The 2 va r iab les which were in t roduced t o capture o v e r a l l stage o f p r o j e c t complet ion (PEAK and

PPEAK) d i d no t en ter our f i n a l equat ion.

Cont ro l Var iables

F i n a l l y , we examined t h e e f f e c t o f several c o n t r o l va r i ab les upon the

d is tance exponent. Only one--REGION--was shown t o be s i g n i f i c a n t . The

reg ion v a r i a b l e i s a dummy v a r i a b l e which was def ined t o have a value of

one i f the s i t e was located i n t he South and zero otherwise. Thus, the

r e s u l t s suggest t h a t ho ld ing o the r va r i ab les constant, on average, movers

i n the South tend t o l i v e f a r t h e r from the cons t ruc t i on s i t e than movers

i n t he North.

D i f fe rences i n Distance Exponents

Perhaps a b e t t e r understanding o f these r e s u l t s can be achieved by

examining the d is tance exponents imp l i ed by the est imated equation. The

c o e f f i c i e n t est imates were used t o est imate d is tance exponents f o r each

o f t he 24 surveys inc luded i n our analys is . These est imates are pre-

sented i n Table D-2. The d is tance exponents thus computed ranged from

approximately 1.2 t o 1.6. It i s important t o note t h a t d is tance expo-

nents vary no t o n l y across s i t e s , bu t a lso a t the same s i t e a t d i f f e r e n t

stages o f p r o j e c t completion. The reason f o r t h i s i s t h a t although most

va r i ab les included i n the equat ion are s i t e- s p e c i f i c var iables, the work-

force composit ion va r iab les are survey-specif i c . Thus, as workforce

composit ion changes, so a lso does the d is tance exponent. Comparing e s t i -

mated exponents f o r those s i t e s a t which m u l t i p l e surveys were conducted,

i t can be seen t h a t d is tance exponents, i n general, increase as construc-

t i o n on the p r o j e c t progresses toward peak employment. This i s because

i n r e l a t i o n t o the nonconstruct ion workforce the s i z e o f the cons t ruc t i on

workforce increases du r ing peak employment. This r e l a t i o n s h i p i s perhaps

bes t i l l u s t r a t e d by a comparison o f the th ree surveys conducted a t S i t e

10. One w i l l note t h a t t h e est imated d is tance exponent o f t he second

survey (10.2) which was conducted dur ing peak employment was h igher than

t h e est imated d is tance exponent o f t he f i r s t survey (10.1) which was

conducted dur ing the prepeak stage. Furthermore, one w i l l observe t h a t

as employment decreased du r ing the postpeak stage (10.3), the est imated

d is tance exponent a lso decreased. This imp l ies t h a t as employment

decreases a t a s i t e , t h e movers 1 i v i n g nearer t he s i t e are the f i r s t t o leave. This i s cons is ten t w i t h the evidence found dur ing our p r o f i l e

ana lys is t h a t temporary movers are more l i k e l y t o l oca te c lose r t o t h e

s i t e than are permanent movers.

TABLE D-2

Distance Coef f ic ients as Estimated Based Upon the Residential Location Equation


Number

Estimated Di stance

Coef f ic ient

REFERENCES

Wieland, J. S.; L e i s t r i t z , F.L.; and Murdock, S. H. " C h a r a c t e r i s t i c s and Res iden t i a l Pa t te rns o f Energy-Related Work Forces i n t he Nor thern Great Plains." Western ~ o u r n a l of A g r i c u l t u r a l Economics, ( Ju l y , 1979), pp. 57-68.

DEFINITION OF VARIABLES - RESIDENTIAL LOCATION

I. Reaional A t t rac t i veness

A. Dis tance f rom t h e nearest SMSA (DSMSA)--distance o f t h e s i t e ( i n

hundreds o f m i l e s ) f rom t h e c e n t r a l c i t y o f t h e nearest SMSA.

B. Employment i n t h e r e t a i l t r ade i n d u s t r y i n t he l o c a l area

(RETEMP)--per c a p i t a employment i n r e t a i l t r ade i n t h e l o c a l area

f o r t h e year cons t ruc t i on began (i .e., t o t a l number o f workers

employed i n r e t a i l t r ade d i v i d e d by the popu la t ion o f t he i o c a l

area) m u l t i p l i e d by the popu la t ion o f a l l communities w i t h i n 15

m i l e s o f t h e s i t e ( i n thousands).

C. Employment i n t he se rv i ce i n d u s t r y i n t h e l o c a l area (SVCEMP)--

per c a p i t a employment i n serv ices i n t he l o c a l area f o r t h e year

cons t ruc t i o n began ( i .e., t o t a l number o f workers employment i n

t h e se rv i ce i n d u s t r y d i v i d e d by the popu la t ion o f t h e l o c a l area)

m u l t i p l i e d by t h e popu la t ion o f a l l c o m u n i t i e s w i t h i n 15 m i l e s

o f t h e s i t e ( i n thousands).

D. Growth i n l o c a l popu la t ion (LP0PGR)--change i n t h e popu la t i on o f

t h e l o c a l area between 1970 and 1975 expressed as a p r o p o r t i o n o f

t h e 1970 populat ion.

E. Local per c a p i t a income (LPCI) --weighted average (weighted by popu la t i on ) o f count ies i n t h e l o c a l area ( t h e county i n which

t h e s i t e i s loca ted p lus any ad jo in ing county w i t h i n 15 highway

m i l e s o f t he s i t e ) f o r t he year cons t ruc t i on began.

F. Populat ion o f nearby communities (POP10, POP15, POP20, POP25)--

t h e t o t a l popu la t i on o f communities ( i n thousands) w i t h i n 10, 15,

20, and 25 m i l es o f t he s i t e .

G. Number o f nearby communities (NCMTY10, NCMTY15, NCMTY20,

NCMTY25)--the number o f communities w i t h i n 10, 15, 20, and 25

m i l e s o f t he s i t e .

H. Average s i z e o f nearby comnun i t i e s ( COMSZ 10, COMSZ15, COMSZ20,

COMSZ25)--the t o t a l popu la t ion o f communities d i v i d e d by the

number o f communities w i t h i n 10, 15, 20, and 25 m i l e s o f t h e s i t e .


A. Housing vacancy r a t e (VACRT)--the number o f vacant u n i t s d i v i d e d

by t o t a l housing u n i t s i n 1970 f o r count ies i n t h e l o c a l area

mu1 t i p 1 i e d by 100.

B. Number o f mobi le homes uer c a p i t a (PCMHI--total number o f mob i le

homes i n t he l o c a l area i n 1970 d i v i ded by the 1970 popu la t ion .

C. Percent owner-occupied housing (PCTOWN) --owner-occupied housing

u n i t s as a p ropo r t i on o f a l l occupied housing u n i t s i n 1970 f o r

count ies i n the l o c a l area.

D. Number o f housing u n i t s per c a p i t a (PCHSG)--total housing u n i t s

i n t he l o c a l area i n 1970 d i v i ded by t h e 1970 populat ion.

111. Workforce Composition and Other P r o j e c t Cha rac te r i s t i cs

A. To ta l number o f movers (NM0VE)--the t o t a l number o f movers f o r

a l l worker groups a t t h e s i t e a t t he t ime o f t h e survey ( i n hun-

dreds o f movers).

B. Prouor t ion o f movers f rom scarce c r a f t s (PSI- - the t o t a l number o f

movers from scarce c r a f t s d i v i ded by the t o t a l number o f movers

a t t h e s i t e a t t h e t ime o f t he survey.

C. P ropor t ion o f movers f rom o t h e r cons t ruc t i on c r a f t s (PO)-- the

t o t a l number o f movers f rom the common and abundant c r a f t s

d i v i ded by the t o t a l number o f movers a t t he s i t e a t the t ime o f

t h e survey.

D. Peak employment (PEAK)--a dummy v a r i a b l e i n d i c a t i n g whether o r

no t t o t a l employment a t t he s i t e had reached the peak stage (had

been r e l a t i v e l y constant over a pe r i od o f t ime) .

E. Postpeak employment (PPEAK)--a dummy v a r i a b l e i n d i c a t i n g whether

o r no t t o t a l employment a t t h e s i t e had reached the postpeak

stage (had begun t o dec l i ne ) .

I V . Contro l Var iab les

A. Region (REGION)--a dummy v a r i a b l e i n d i c a t i n g whether o r no t the

s i t e i s loca ted i n the Nor th o r i n the South.

APPENDIX E

V A L I D I T Y OF THE FORECASTING PROCEDURES

APPENDIX E

VAL IDITY OF THE FORECASTING PROCEDURES

In this appendix we provide some evidence regarding the validity of

the forecasting procedures described in Chapter IV of this report. This

discussion is divided into 3 sections. The expected accuracy of the

proposed procedures for predicting migrant proportions and residential

location patterns of inmigrating workers is discussed in the first two

sections. The final section includes a brief discussion of the validity

of the procedures for predicting other variables important in socio-

economic impact assessment, i.e., the number of movers who will relocate

their families, the intention of movers to remain in the area beyond

completion of the project, the type of housing selected and marital

status of inmigrating workers.

MIGRANT PROPORTIONS

Results of the estimated model were used to establish the validity of

the proposed procedures to estimate the overall migrant proportions at

nuclear power plant construction sites. The validity of the model, and

therefore of the forecasting procedures developed from them, is attested by (1) the large amount of variation explained by the model, (2) robust-

ness of the estimated coefficients and residuals, (3) consistency of the

explained variation, and (4) the difference in the predicted and actual overall migrant proportions in the 21 surveys included in the sample.

Explained Variation - Over seventy percent of the variation in migrant proportions among

the surveys included in the study is explained by the estimated construc-

tion worker equation. This imp1 ies a correlation between actual and

predicted values of 85 percent. Since we are interested in overall mi-

grant proportions rather than in the migrant proportions of workers in

individual crafts, the estimated equation can be expected to perform even

better. If the unexplained variation is due to random errors associated

with the variables included in the equation, then the correlation between

o v e r a l l (aggregated across 7 c r a f t s ) ac tua l and p red i c ted migrant propor-

t i o n s would be much higher. And, indeed, i t was 95 percent i n the case

o f cons t ruc t i on worker equation. I n t he case o f the nonconstruct ion

worker equat ion n e a r l y 85 percent o f t he v a r i a t i o n i n migrant p ropo r t i ons

i s expla ined by the est imated equation. This suggests t h a t t he est imated

equations can be expected t o p r e d i c t extremely w e l l a t s i t e s w i t h charac-

t e r i s t i c s which are w i t h i n the range o f c h a r a c t e r i s t i c s o f t h e s i t e s

inc luded i n our sample.

Robustness o f t he C o e f f i c i e n t s ---- The c o e f f i c i e n t est imates o f key va r iab les i n our equat ions were

found t o be s t a b l e w i t h respect t o ( 1 ) i n c l u s i o n and exc lus ion o f c o n t r o l

va r i ab les i n t he equat ion (discussed i n Appendix C o f t h i s r e p o r t ) , and

( 2 ) es t ima t ing the equat ion us ing subsets o f the data, i .e., es t ima t ing

t h e equat ion exc lud ing a1 1 observat ions ( a t o t a l o f 7 c r a f t groups) f rom

one s i t e a t a t ime. We est imated f i v e such equations separa te ly f o r

cons t ruc t i on and nonconstruct ion workers. Tables E-1 and E-2 present a

comparison of these regression r e s u l t s . The equations i n which s i n g l e

s i t e s were excluded e x h i b i t e d remarkable consistency when compared w i t h

t h e equat ion which inc luded a l l s i t e s (as w e l l as when compared w i t h the

equat ions which excluded o ther s i n g l e s i t e s ) . I n t he case o f both t h e cons t ruc t i on and nonconstruct ion worker equations, the magnitude and

s i g n i f i c a n c e o f t he c o e f f i c i e n t estiamates do no t show much v a r i a t i o n

across equations. The s ign o f each c o e f f i c i e n t est imate i s t he same i n

a l l equat ions. F i n a l l y , i t should be noted t h a t t he re i s no s i g n i f i c a n t

l oss i n t he amount o f v a r i a t i o n expla ined when the equat ion i s est imated

us ing subsets o f t he data.

As a more formal t e s t , we used the "F" values associated w i t h the

Chow t e s t t o determine whether o r n o t the excluded observat ions may be

considered t o come from the same populat ion.1 With the except ion o f

l ~ o t e t h a t t h i s i s a spec ia l case o f t he Chow t e s t i n which t h e number o f observat ions associated w i t h the excluded s i t e i s l ess than the number o f parameters. Under these cond i t ions a v a r i a n t o f t h e t e s t can be performed as suggested by Johnson. See J. Johnson, Econometric Methods, (New York: McGraw H i l l Book Company, Inc., 1972), p. 207.

TABLE E-1

Construction Worker Migrant Propor t ion Regression Results f o r Subsets o f S i tes

(standard e r r o r i n parentheses)

A l l S i tes

fZ2 = .71

$ = .67

Excluding Excluding Survey 1.0 Survey 2.0

2 R = . 7 1 ~ ' = . 7 2

3 = .66 ?iZ = .68

Excl udi ng Excluding Survey 3.0 Survey 4.0

R ~ = .73 R ~ = .73

$ = . 6 9 ' j i 2 = . 6 8

Excluding Survey 8.0

= .67

x2 =62

Income 'po ten t ia l

Wage

Labor Requirements

Conti r ~ u i t y o f Employment

Duration o f Employment I

Durat ion o f Employment I1

Duration o f Employment 111

Prepeak Stage

Pos tpeak Stage -.52* -. 55* -. 54* - .49* -.45* (. 18) ( . I91 ( -18) ( . I71 (.18)


Employment a t o t h e r .48* p a r e r p l a n t s i n ( . l o ) the region

Local Avai 1 abi 1 i t y o f Labor

Distance f r o m the .21* union loca l ( . I21


Regional Population 1.71 *

Regional Population -1.11 * Growth (.24)

Average .Comnuni t y -3.1 l* Size - 25 mi les (.56)

Average Community 1.49* S i z e - l o m i l e s (.28)

Housing vacancy ra te .16*. (2.75)

Control Variables

Comnon -6.26* (2.71)

Scarce

Size o f Uni ts 1.45* I.%* 1.52* 1.49* ( .56)

1.15* (1.01) (.56) (.64) (.59)

Constant

Chw t e s t

* Coef f i c ien t i s s i g n i f i c a n t a t the 90% confidence l e v e l .

TABLE E-2

Nonconstruction Worker Migrant Propor t ion Regression Results f o r Subsets o f Si tes

(standard e r r o r i n parentheses)

Excluding Excluding Excluding Excluding Excluding A l l S i tes Survey 1.0 Survey 2.0 Survey 3.0 Survey 4.0 Survey 8.0

2 ~ ~ = . 8 6 & = . 8 8 ~ ~ = . 8 6 R = . 8 5 ~ ~ = . 8 5 I l 2 = . 8 8

Competing Demand For Labor

Other nuclear power -.40* plants under (.20) const ruct ion

Local Avai 1 ab i 1 i t y o f Labor

Regional Unemployment -.61* Rate (.30)

Regi onal Character is t i c s

Regional Populat ion

Control Variables

Occupation

Size o f Uni ts 1.05* 1.51* .81* 1.06* 1.07* .18 (.26) ( .28) (.27) (.26) (.27) ( . 38)

Constant

Chow t e s t -- 6.43 2.52 .51 .09 4.44

* C o e f f i c i e n t i s s i g n i f i c a n t a t the 90% confidence l e v e l .

o n l y one cons t ruc t ion worker equat ion and 2 nonconstruct ion worker equa-

t i ons , we were unable t o r e j e c t the n u l l hypothesis t h a t the observat ions

come from the same populat ion a t the 95 percent l e v e l o f confidence.

These r e s u l t s , therefore, seem t o suggest t h a t the under ly ing parameters

o f t he est imated model are the same f o r the excluded s i t e s as f o r the

o ther s i t e s . However, one has greater conf idence i n the case of the

cons t ruc t ion worker equat ion than i n the case o f the nonconstruct ion

worker equation.

The r e s u l t s , thus, c l e a r l y demonstrate the robustness of the e s t i -

mated model. They show t h a t there i s a systematic v a r i a t i o n i n migrant

p ropor t ions which i s s u c c e s s f u l l l y captured by our s p e c i f i c a t i o n . I f i t

were not , then the l i k e l i h o o d o f observing t h i s l e v e l o f s t a b i l i t y i n the

est imated equations and t h e i r c o e f f i c i e n t s i s extremely small.

The equat ion which was est imated excluding a p a r t i c u l a r s i t e was then

used t o p r e d i c t migrant p ropor t ions a t t h a t s i t e . Table E- 3 presents a

comparison o f these p red i c ted values w i t h both actual migrant p ropor t ions

and the migrant p ropor t ions which were pred ic ted us ing the equat ion e s t i -

mated i nc lud ing a l l s i t e s .

I n comparing actual migrant p ropor t ions w i t h migrant p ropor t ions

p red i c ted us ing the est imated equat ion i n which the p a r t i c u l a r s i t e was

excluded, some r a t h e r pronounced d i f f e rences were observed. We observed

a very pronounced d i f fe rence between actual and pred ic ted values f o r bo th

cons t ruc t i on and nonconstruct ion groups a t o n l y one s i t e . However, i n

the case o f t he nonconstruct ion group, a t two a d d i t i o n a l s i t e s the d i f -

ference between actual and p red i c ted values was greater than 20 percent-

age po in ts . Although the evidence i s by no means overwhelming, i t does

i n d i c a t e a need t o be caut ious regarding the use o f the fo recas t i ng pro-

cedures developed i n t h i s s tudy a t f u t u r e cons t ruc t i on s i t e s . It i s

important t o recognize t h a t t he fo recas t i ng procedures are no t l i k e l y t o

perform too we l l a t s i t e s w i t h important c h a r a c t e r i s t i c s ou ts ide the

range o f t he c h a r a c t e r i s t i c s o f t h e s i t e s inc luded i n our sample.

I n a l l cases the d i f f e r e n c e between actual and p red i c ted migrant

p ropor t ions was much smal ler when a l l s i t e s were included i n the e s t i -

mated equat ion compared w i t h when the s i t e i n quest ion was excluded.

This, however, i s no t s u r p r i s i n g consider ing the small number o f s i t e s i n

TABLE E-3

A Comparison o f Predicted and Actual M i grant Proportions Using Various Equation Estimates

ran t Propor t i on M i grant Proport ion Construction) (Nonconstructi on)

Survey 1.0

Actual

Predicted (a1 1 s i t e s )

Predi cted (Survey 1.0 excluded)

Survey 2.0

Ac tua 1

Predi c ted (a1 1 s i tes)

Predi c ted (Survey 2.0 excluded)

Survey 3.0

Actual

Predi cted ( a1 1 s i tes)

Predicted (Survey 3.0 excluded)

Survey 4.0

Actual

Predicted ( a l l s i t e s )

Predicted (Survey 4.0 excluded)

Survey 8.0

Actual

Predi c ted (a1 1 s i tes)

Predi cted (Survey 8.0 excluded)

our sample. I n f a c t , 4 o f t h e 9 s i t e s which were inc luded i n t h e anal-

y s i s a re TVA s i t e s and these s i t e s have many s i m i l a r c h a r a c t e r i s t i c s .

Thus, t h e exc lus ion o f a s i n g l e s i t e from our sample i s l i k e l y t o reduce

t h e range o f v a r i a t i o n i n key v a r i a b l e s which a re impor tan t f o r purposes

of gene ra l i za t i on . These r e l a t i v e l y smal l dev ia t i ons between t h e ac tua l

and p r e d i c t e d values would suggest t h a t t h e g e n e r a l i z a b i l i t y of t h e model

cou ld have been cons ide rab l y improved by a l a r g e r sample o f s i t e s i n our

da ta se t .

Consistency o f Expla ined Variance and Residuals

F u r t h e r evidence which lends conf idence i n t h e equat ion can be found

i n t h e comparison o f t h e mean square values o f t h e exp la ined v a r i a t i o n

and t he r e s i d u a l s f o r t h e var ious equat ions es t ima ted- - inc lud ing a l l

s i t e s and those i n which observa t ions f rom s i n g l e s i t e s were excluded.

These mean square values a re shown i n Table E-4. Once again, t h e c r i t i -

c a l f i n d i n g i s t h a t mean square values show very l i t t l e v a r i a t i o n . The

mean square reg ress ion ranged f r om 4.28 t o 5.29 i n t h e case o f t h e con-

s t r u c t i o n worker equa t ion and f rom 6.36 t o 6.99 i n t he case o f t h e non-

c o n s t r u c t i o n worker equat ion. Th i s i s a r e f l e c t i o n o f t h e ex is tence o f

systemat ic v a r i a t i o n i n m ig ran t p ropo r t i ons o f c r a f t s w i t h i n and across

s i t e s , and t h e a b i l i t y o f our model t o c o n s i s t e n t l y cap tu re approx imate ly

70 pe rcen t o f t h a t v a r i a t i o n . Th i s robustness and cons is tency which i s

observed i n these r e s u l t s g r e a t l y increases t h e conf idence which one

migh t have i n app ly ing these f o r e c a s t i n g procedures a t f u t u r e cons t ruc-

t i o n s i t e s .

Pred ic ted and Ac tua l Ove ra l l M ig ran t P ropo r t i on

The f i n a l t e s t o f t h e proposed f o r e c a s t i n g procedure l i e s i n how w e l l

i t would p r e d i c t t h e o v e r a l l ( f o r a l l workers) m ig ran t p r o p o r t i o n a t a

s i t e . Accord ing ly , we compared t h e p r e d i c t e d values generated by t h e

proposed f o r e c a s t i n g procedures w i t h t h e ac tua l values i n t he case of a l l

t h e 21 surveys which were inc luded i n our es t ima t i on . The o v e r a l l m i-

g r a n t p ropo r t i ons were est imated by p r e d i c t i n g t h e numbers of m ig ran ts i n

each o f t h e 7 c o n s t r u c t i o n c r a f t s us ing t h e c o e f f i c i e n t es t imates o f

c o n s t r u c t i o n equat ion. ( I t should be noted t h a t i n t h e e s t i m a t i o n o f

t h i s equat ion, a l l 7 c r a f t s were n o t inc luded i n t h e case o f a l l t h e

TABLE E-4

Summary o f Explained and Unexplained Vari a t i on i n the Estimated Equations - M i g rant Propor t i ons

Mean square Mean square regression res i d"al

Construct ion worker equat i on

A l l s i t e s

Excl ud i ng Survey 1.0

Excl udi ng Survey 2.0

Excl ud i ng Survey 3.0



Noncons t r u c t i on worker equation

A l l s i t e s 6.99

Excl udi ng Survey 1.0 6.39

Excluding Survey 2.0 6.36



Excluding Survey 8.0 6.72

surveys because i n some c r a f t s t h e r e were t o o few workers on t h e s i t e a t

t h e t ime o f t h e survey.) I n add i t i on , t h e number o f m ig ran ts was e s t i -

mated f o r t h e o t h e r c o n s t r u c t i o n c r a f t group. The numbers o f m ig ran ts

among noncons t ruc t i o n ( c l e r i c a l and management) workers were es t imated

us ing t h e c o e f f i c i e n t es t imates o f t h e noncons t ruc t ion equat ion. The

weighted average o f these numbers was used t o o b t a i n t h e o v e r a l l m ig ran t

p r o p o r t i o n p r e d i c t e d by t h e proposed f o r e c a s t i n g procedure.

A comparison o f p r e d i c t e d and t h e ac tua l o v e r a l l m ig ran t p r o p o r t i o n s

i s presented i n Table E-5. As can be seen i n t he tab le , t h e d i f f e r e n c e

between t h e ac tua l and p r e d i c t e d values, i n most cases, was sma l l . The

mean abso lu te d e v i a t i o n was o n l y 2.9 percentage p o i n t s and t h e root-mean-

square d e v i a t i o n was o n l y 3.7 percentage p o i n t s . Thus, n o t o n l y i s t h e

expected va lue o f t h e e r r o r smal l , b u t t h e l i k e l i h o o d o f a f o r e c a s t i n g

e r r o r o f 7.5 percentage p o i n t s i s low. I n f a c t , i n over 80 percen t of

t h e cases, t h e e r r o r d i d n o t exceed - + 5 percentage p o i n t s . Th i s compari-

son i l l u s t r a t e s t h e k i n d o f p r e c i s i o n one can expect f rom us ing t h e p ro-

posed procedures t o p r e d i c t m ig ran t p r o p o r t i o n a t s i t e s s i m i l a r t o those

inc luded i n our study. The r e l a t i v e l y low v a r i a t i o n i n t h e d i f f e r e n c e

between ac tua l and p r e d i c t e d o v e r a l l m ig ran t p ropo r t i ons i s an added

tes t imony o f t h e p r e c i s i o n and appropr ia teness o f t h e models used i n

develop ing t h e f o r e c a s t i n g procedure.

RESIDENTIAL LOCATION

A s i m i l a r se t of t e s t s was used t o examine t he v a l i d i t y o f t h e pro-

posed procedures f o r e s t i m a t i n g r e s i d e n t i a1 l o c a t i o n p a t t e r n s o f inmigra-

t i n g workers a t nuc lear power p l a n t c o n s t r u c t i o n s i t e s . Almost s i x t y

percen t o f t h e v a r i a t i o n i n r e s i d e n t i a l l o c a t i o n p a t t e r n s o f movers i s

exp la ined by t h e est imated equat ion. As i n t he case o f m ig ran t propor-

t i o n s , severa l o t h e r f a c t o r s a l so serve t o lend suppor t t o t h e v a l i d i t y

o f t h e model. These inc lude : ( 1 ) robustness o f t h e est imated c o e f f i-

c i e n t s and res idua l s , ( 2 ) cons is tency o f t h e exp la ined v a r i a t i o n , and ( 3 )

t h e d i f f e r e n c e s i n t h e p r e d i c t e d and ac tua l p ropo r t i ons o f movers l i v i n g

a t va r ious d i s tance i n t e r v a l s f rom t h e c o n s t r u c t i o n s i t e .

TABLE E-5

Overa l l Migrant Proport ions A Comparison o f Actual and Pred ic ted Values


N u h e r Pred ic ted Actual

21 .o

15.3

24.7

25.2

46.9

29.7

32.8

32.7

30.1

18.0

23.4

32.8

40.3

18.9

23.7

29.6

31.7

15.8

18.9

25.9

25.5

Devi a t i on

-4.1

3.9

-7.5

-2.3

-.8

-4.6

-1.5

-. 9

6.4

1.6

-4.6

-1.1

-5.7

-. 1

-. 2

-.9

4.2

5.8

2.7

-2.1

0.0

Mean absol u t e devi a t i on 2.9 Root-mean-square d e v i a t i o n 3.7

Robustness of the Coefficients ---------- The coefficient estimates of key variables were found to be stable

with respect to the inclusion and exclusion of various control variables

(see Appendix D) and also when all communities associated with single

sites were excluded from the regression. As was the case in our migrant

proportion analysis, five such equations were estimated. A comparison of

the coefficient estimates and the standard errors of equations including

all sites and in which single sites were excluded is presented in Table

E-6. As can be seen from the table, the sign significance and magnitude 2 of the coefficient estimates, as well as the corresponding R , remain

quite stable despite the exclusion of different sets of observations from

the analysis. Once again, we used the "F" values associated with the

Chow test to determine whether or not the excluded observations may be

considered to come from the same population. In all cases we were unable

to reject the null hypothesis that the observations come from the same

population at the 95 percent confidence level.

Consistency of Exained Variance and Residuals

A comparison of the mean square values of the explained variation and

the residuals for the various equations estimated--including all sites

and those in which all observations from single sites were excluded--was also made. These results are presented in Table E-7. As was true in the

case of the migrant proportion equations, one observes that the mean square values exhibit little variation when single sites are excluded.

The mean square of the regression ranged from 102.29 to 109.95 and the

mean square of the residual ranged from .860 to .880. Thus, the robust-

ness, consistency and stability of the regression equation serve to

increase our confidence in the application of these forecasting proce-

dures at future construction sites.

Predicted and Actual Residential Location Patterns

Final ly, the estimated residential location equation was examined

with respect to how well it would predict residential location patterns

among the surveys included in our study. However, owing to the number of

communities surrounding each construction site, a comparison of actual

and predicted values is more difficult than was true for migrant

TABLE E-6

Resident ia l Locat ion .Regression Results f o r Subsets o f Data (standard e r r o r i n parentheses)

Excluding Excluding Excluding Excluding Excluding A l l S i tes Survey 1.0 Survey 2.0 Survey 3.0 Survey 4.0 Survey 8.0

2 2 2 R' = .605 R = .609 R' = .608 R = .603 R = .604 R' = .600

Population .385* .383* .390* .383* .385* .380* ( .Ol8) (.018) (.019) (.019) ( .019) (.019)

Di stance -.917* -.925* -.961* - .935* - .902* -1.038* ( .168) (.170) ( .169) (.176) ( . I S ) (.201)

Distance I n t e r - ac t ion Terms

Local r e t a i 1 a c t i v i t y - .094* -. 090* -.107* -.108* - .094* -.103* (.041) ( .042) ( .047) ( .056) ( .042) (.041)

Distance from SMSA

Housing vacancy r a t e

Per cap i ta mobile homes

Total nunber o f movers

Proport ion scarce

Proport i on other const ruct ion

Region

Constant -2.897* -2.811* -2.794* -2.886* -2.953* -2.934* (.190) (.193) (.196) (.193) (.197) (.193)

Chow t e s t - - 1 .I82 1.060 .860 .730 1.072

* C o e f f i c i e n t i s s i g n i f i c a n t a t the 90% confidence l e v e l .

TABLE E-7

A1 1 s i tes

Summary o f Expl a i ned and Unexpl a i ned Vari a t i on i n the Es ti mated Equation - Resi dent i a1 Locat i on

Vian square Mean square regression res i dual

Excl ud i ng Survey 1.0 108.31 .860

Excl udi ng Survey 2.0 106.88 .862

Excl udi ng Survey 3.0 106.50 ,868



propor t ions . For t h i s reason we examined the actual and p red i c ted pro-

p o r t i o n s of movers l i v i n g i n 5-mile i n t e r v a l s o f t he s i t e . Table E-8

presents a comparison of actual and pred ic ted values f o r each o f t h e 24

surveys f o r which p r e d i c t i o n s were made.

The f i n a l two columns i n Table E-8 conta in the mean absolute devia-

t i o n between ac tua l and p red i c ted values and the root-mean-square devia-

t i o n f o r each o f t he d is tance bands. It i s i n t e r e s t i n g t o note t h a t the

h ighes t average d i f f e rences occurred i n the 6-10 and 21-25 m i l e d is tance

bands. I n most o ther d is tance bands d i f f e rences were r e l a t i v e l y smal l .

I t i s l i k e l y t h a t the observed d i f f e rences between ac tua l and p red i c ted

values stem from s p e c i f i c a t t r a c t i v e o r u n a t t r a c t i v e fea tu res o f p a r t i c u-

l a r communities surrounding a cons t ruc t i on s i t e . L im i ted resources d i d

n o t a l low us t o exp lore more f u l l y t he c h a r a c t e r i s t i c s under ly ing these

d i f f e rences . Such aspects o f the problem would undoubtedly be sub jec ts

f o r f u t u r e research e f f o r t s . Nevertheless, by u t i l i z i n g a model which

e x p l i c i t l y incorporates var ious reg iona l and p r o j e c t c h a r a c t e r i s t i c s

( i .e . , r eg iona l a t t rac t iveness , housing a v a i l a b i l i t y and workforce com-

p o s i t i o n ) , one can expect the proposed fo recas t i ng procedures t o improve

t h e accuracy o f r e s i d e n t i a l l o c a t i o n p red i c t i ons compared w i t h methods

which have been p rev ious l y used t o a l l o c a t e movers t o var ious communities

surrounding 1 arge cons t ruc t i o n p ro jec ts .

PERSONAL AND HOUSEHOLD CHARACTERISTICS OF MOVERS

Because of t h e d i f f e r e n t way i n which the procedures f o r f o r e c a s t i n g

the personal and household c h a r a c t e r i s t i c s o f movers were developed, our

examination o f t he v a l i d i t y o f t h e proposed fo recas t i ng procedures was

1 im i ted t o a comparison o f ac tua l and p red i c ted values.

The proposed fo recas t i ng procedures were used t o est imate the o v e r a l l

p ropor t ions o f movers w i t h f a m i l y present among the 24 surveys f o r which

in fo rmat ion on the r e l o c a t i o n o f dependents was avai 1 able. A comparison

o f ac tua l and p red i c ted values i s presented i n Table E-9. I n general,

t he d i f f e rences between actual and pred ic ted values were n o t very la rge .

The mean absolute dev ia t i on and the root-mean-square dev ia t i on were 5.4

and 7.5 percentage po in ts , respec t i ve l y . I n 5 ou t o f 24 cases, however,

t he d i f f e r e n c e between ac tua l and p red i c ted values exceeded 10 percentage

TABLE E-8

Proportions o f Movers Liv ing a t Various Distances from the S i t e A Comparison o f Actual and Predicted Values

Distance In te rva l (miles)

0-5

6-10

11-15

16-20

21-25

26- 30

31 - 35

36-40

41 -80

Distance In te rva l (miles)

0-5

6-10

11-15

16-20

21-25

26- 30

31 - 35

36-40

41-80

Di stance In te rva l (miles)

0-5

6-10

11-15

16-20

21 -25

26-30

31 - 35

36-40

41-80

Survey 1 .o

Act Proj

1 5

70 71

10 5

11 8

1 1

3 4

1 1

1 1

3 5

Survey 10.1

Act Proj

0 0

61 57

0 0

12 13

1 1

7 11

3 5

3 3

13 10

Survey 12.3

Act ProJ

0 3

32 45

21 9

19 15

3 5

9 7

6 6

1 2

8 9

Survey 2.0

Act Proj

18 11

31 30

2 5

6 8

20 18

13 8

1 1

1 4

8 15

Survey 10.2

Act Proj

0 0

60 60

0 0

17 8

1 1

8 7

2 3

1 2

11 20

Survey 12.4

Act Proj

0 3

31 53

22 8

23 13

3 4

7 5

3 3

3 4

8 8

Survey 3.0

Act Proj

32 37

3 9

10 12

43 24

7 8

0 1

2 4

1 4

2 2

Survey 10.3

Act Proj

0 0

42 38

0 0

18 12

1 1

10 10

4 6

2 3

23 30

Survey 13.1

Act Proj

4 5

19 35

8 10

5 7

51 16

1 2

5 1

1 1

7 23

Survey 4.0

Act Proj

9 15

14 32

7 7

44 18

7 5

2 4

7 6

1 2

9 11

Survey 11.1

Act Proj

0 0

73 66

0 0

21 22

1 5

1 3

1 0

1 3

1 1

Survey 13.2

Act Proj

3 4

16 33

13 11

7 7

44 15

1 1

5 1

1 2

9 26

Survey 8.0

Act Proj

6 13

22 36

17 10

6 12

43 16

2 3

1 2

1 1

3 6

Survey 11.2

Act Prod

0 0

65 66

2 4

21 16

3 3

1 3

1 2

1 2

6 4

Survey 13.3

Act Proj

2 5

16 41

10 10

9 6

38 12

1 2

6 1

3 3

15 20

Survey 9.1

Act Proj

13 10

62 57

4 8

3 1

4 6

3 2

1 1

2 5

9 9

Survey 9.2

Act Proj

12 10

60 56

4 7

3 1

5 6

2 2

1 2

4 5 9 11

Survey 11.3

Act Proj

0 0

66 64

2 2

20 19

3 4

1 3

1 2

2 2

6 4

Survey 13.4

Act Proj

2 5

16 44

11 10

8 6

37 11

1 2

7 1

3 3

15 18

Survey 11.4

Act Proj

0 0

56 67

1 4

33 16

3 3

1 4

1 2

2 2

3 4

Survey 9.3

11 10

56 59

6 6

1 1

4 5

4 3

2 3

2 3

14 11

Survey 12.1

Act Proj

0 0

38 40

20 10

18 23

1 5

6 4

10 8

3 3

4 9

Isle an Absolute

Deviation

3.4

9.4

4.2

5.5

7.0

1.6

1.6

1 .o 4.0

Survey 9.4

Act Proj

Survey 12.2

Act Proj

Root-Mean- Square

Deviation

4.1

12.6

6.3

8.6

17.3

2.0

2.3

1.4

6.1

* Percents may not add t o 100 due to rounding.

TABLE E-9

Propor t i on o f Movers w i t h Fami l y Present A Comparison o f Actual and Predicted Values

Survey I d e n t i f i c a t i on

Number Predi c ted Actual Devi a t i on

Mean absolute dev ia t ion 5.4 Root-mean-square dev ia t ion 7.5

p o i n t s . Th i s would suggest t h a t t h e r e may be a need f o r a more e l abo ra te

ana l ys i s o f r e l o c a t i o n o f dependents, as was conducted f o r m ig ran t p ro-

p o r t i o n s and r e s i d e n t i a l l o c a t i o n . Such an ana l ys i s c e r t a i n l y would have

produced supe r i o r p r e d i c t i o n procedures. Nonetheless, these procedures

do represen t an improvement i n f o r e c a s t i n g procedures over mere ly us ing

o v e r a l l average values across a1 1 s i t e s .

S i m i l a r l y , w i t h respec t t o i n t e n t i o n t o remain i n t h e area, t h e f o r e -

c a s t i n g procedures were used t o p r e d i c t t h e p r o p o r t i o n o f movers who a re

temporary f o r t h e 4 s i t e s i n our sample f o r which o v e r a l l i n t e n t i o n t o

remain i n t h e area cou ld be determined. A comparison o f t h e ac tua l and

p r e d i c t e d values i s presented i n Table E-10. As can be seen i n t h e

t ab le , t h e r e s u l t s were q u i t e good, w i t h a mean abso lu te d e v i a t i o n o f

o n l y 1 percentage p o i n t and a root-mean-square d e v i a t i o n o f o n l y 1.6

percentage p o i n t s . These r e s u l t s r e f l e c t o n l y 4 s i t e s and, t he re fo re ,

cannot be assumed t o be r e l i a b l e .

A comparison o f t h e ac tua l and p red i c ted p r o p o r t i o n s o f movers l i v i n g

i n each o f 4 d i f f e r e n t types o f housing among t h e 24 surveys i n our da ta

s e t i s presented i n Table E-11. I n a few instances t he d i f f e r e n c e s

between ac tua l and p r e d i c t e d values was q u i t e la rge , w h i l e i n o t h e r i n -

stances t h e d i f f e r e n c e ~ were r e l a t i v e l y smal l . Mean abso lu te d e v i a t i o n s

f o r houses, mob i le homes, apartments and o the r housing were 4.8, 6.5,

3.8, and 3.6 percentage po in t s , r e s p e c t i v e l y . The corresponding r o o t -

mean-square dev ia t i ons were 6.9, 7.9, 5.5, and 4.4 percentage po in t s .

F u r t h e r improvement i n f o r e c a s t i n g procedures can n o t be made w i t h o u t

per fo rming a m u l t i v a r i a t e ana lys is . Th i s l e v e l of accuracy, however, may

be s u f f i c i e n t f o r purposes o f r ecogn i z i ng t h e k i n d o f housing pressures

t h a t a re l i k e l y t o r e s u l t around nuc lea r power p l a n t c o n s t r u c t i o n s i t e s .

F i n a l l y , t h e proposed f o r e c a s t i n g procedures were used t o es t imate

t h e p r o p o r t i o n o f movers who a re mar r i ed a t each o f t h e 7 s i t e s i n our

da ta s e t f o r which i n f o r m a t i o n on m a r i t a l s t a t u s was a v a i l a b l e . A com-

pa r i son o f ac tua l and p r e d i c t e d values i s presented i n Table E-12. I n

general , t h e est imated p ropo r t i ons and ac tua l p ropo r t i ons were r a t h e r

c lose . The mean abso lu te d e v i a t i o n was o n l y 3.4 and t h e root-mean-square

d e v i a t i o n was 4.1.

TABLE E-10

S i t e I d e n t i f i c a t i on

Number

Percent Temporary A Comparison o f Actual and Predicted Values

Predicted

59.

53.

52.

52.

Actual Deviat ion

59. 0.

55. -2.

50. 2.

52. 0.

Mean absol ute devi a t i on 1 .O Root-mean-square dev ia t ion 1.6

TABLE E-11

Housing Choice o f Movers by Type A Comparison o f Actual and Predicted Values


Number

1 .o 2.0

3.0

4.0 .. 8.0

9.1

9.2

House (%) Predicted Actual

44.0 35.4

39.2 38.8

38.2 38.5

37.2 41.6

38.2 38.7

44.1 29.7

44.3 37.1

Mean absolute dev ia t ion

Root-man-square dev ia t ion

Deviat ion Mobile Home (%) Apartment (%)

Predicted Actual Deviat ion Predic ted Actual Deviat ion Other (%)

Predic ted Actual Deviat ion

TABLE E-12

Percent Married A Comparison o f Actual and Predicted Values

Survey I d e n t i f i c a t i on

Nunher Predi c ted

75.2

76 .1

76.2

76.4

84.7

84.6

84.7

Actual

69.9

71.5

76.6

80.7

83.8

81.1

89.2

Fkan absol u te devi ati-on 2.9

Root-mean-square dev ia t ion 3.7

REFERENCES

Johnson, J. Econometric Methods. New York: McGraw-Hill Book Company, Inc., 1972.

NUREG/CR-2002 Vol . 1&2 PNL-3757

RE

DISTRIBUTION

No. o f Copies

OFFSITE

A. A. Churm DOE Patent D i v i s i o n 9800 S. Cass Avenue Argonne, I L 60439

226 U.S. Nuclear Regulatory Commission

D i v i s i o n o f Technical I n f o r - mation and Document Cont ro l

7920 Nor fo lk Avenue Bethesda, MD 20014

2 DOE Technical In fo rmat ion Center

50 M. Kaltman S i t i n g Impact Analys is Sect ion U.S. Nuclear Regulatory

Comnission Lugenbeel B u i l d i n g Room L-237 4922 Fairmont Ave. Bethesda, MD 20115

No. o f Copies

50 D. Cleary S i t i n g Impact Analys is Sect ion U.S. Nuclear Regulatory Commission Lugenbeel B u i l d i n g 4922 Fairmont Ave. Bethesda, MD 20115

50 C. Pr ichard Environmental E f f e c t s Branch D i v i s i o n o f Safeguards, Fuel

Cycle & Environmental Research

Ma i l S t a t i o n 1130 SS U.S. Nuclear Regulatory

Commission Washington, DC 20555

ONSITE

50 P a c i f i c Northwest Laboratory

J. W . C u r r i e (20) S. Malhotra (23) Technical In fo rmat ion (5 ) Pub1 i s h i n g Coordinat ion (2)

NRC 335 Us. NUCLEAR REGULATORY C w l s l O N (7 -77)

BIBLIOGRAPHIC DATA SHEET 4. TITLE AND SUBTITLE @dd V d u m No-, if @ ~ f ~ * m )

M i g r a t i o n and R e s i d e n t i a l L o c a t i o n o f Workers a t N u c l e a r Power P l a n t C o n s t r u c t i o n S i t e s S u b t i t l e : F o r e c a s t i n g Methodo logy

7. AUTHOR LS)

Suresh M a l h o t r a and Diane Manninen 9. PERFORMING ORGANIZATION NAME AND MAILING ADDRESS (/mlud, Zip Coal

P a c i f i c Nor thwes t L a b o r a t o r y R ich land , WA 99352

1. REPORT NUMBER Urupwdbv D9Cl

NUREGICR-2002, Vo l . 1

2 (Le- Walk1

3. RECIPIENTS ACCESSION NO.

6. DATE REPORT COMPRTED MONTH

March 1981 DATE REPORT ISSUED MONTH I YEAR

Apr i 1 1981 6. L a m U m k l

8. f L e m U m k l

12. SPONSORING ORGANIZATION NAME AND MAILING ADDRESS flnclud, zw -1

D i v i - s i o n o f Safeguards, Fuel Cyc le and Env i ronmen ta l Researct,. O f f i c e o f N u c l e a r R e g u l a t g r y Research U.S. Nuc lea r R e g u l a t o r y Commission Washington, DC 20555

10. PROJECTITASWORK UNIT NO.

wNTRAcT No.

FIN B2265

1

. 13. TYPE OF REPORT PE RlOD COVE RED flnclusiw dorrl

F i n a l R e p o r t 1978-1 981

15. SUPPLEMENTARY NOTES 14. (Leu8 M-kl

n u c l e a r power p l a n t c o n s t r u c t i o n p r o j e c t s . Procedures f o r e s t i m a t i n g s e v e r a l o t h e r v a r i a b l e s wh ich have i m p o r t a n t i m p l i c a t i o n s w i t h r e s p e c t t o socioeconomic i m p a c t assessment ( i .e. r e l o c a t i o n o f dependents, i n t e n t i o n t o remain i n t h e area, t y p e o f hous ing s e l e c t e d , m a r i t a l s t a t u s , and average f a m i l y s i z e ) were a1 so developed. The a n a l y s i s was based on worke r s u r v e y d a t a f r o m 28 su rveys wh ich were conducted a t 13 n u c l e a r power p l a n t c o n s t r u c t i o n s i t e s . These s u r v e y d a t a were examined t o i d e n t i f y p a t t e r n s o f v a r i a t i o n i n v a r i a b l e s o f i n t e r e s t ac ross s i t e s as w e l l as a c r o s s v a r i o u s worke r groups. I n a d d i t i o n , c o n s i d e r a b l e secondary d a t a r e f 1 e c t i n g v a r i o u s r e g i o n a l and p r o j e c t c h a r a c t e r i s t i c s were ga the red f o r each s i t e . These d a t a were used t o e s t i m a t e t h e e f f e c t s o f f a c t o r s u n d e r l y i n g t h e observed v a r i a t i o n i n c r a f t - s p e c i f i c m i g r a n t p r o p o r t i o n s and t h e r e s i d e n t i a l l o c a t i o n p a t t e r n s o f i n m i g r a t i n g worke rs acros : s i t e s and surveys. The r e s u l t s o f t h e s e ana lyses were t h e n used as a b a s i s f o r t h e s p e c i f i c a t i o n o f t h e f o r e c a s t i n g procedures .

T

17. KEY WORDS AND DOCUMENT ANALYSIS 17r DESCRIPTORS

soc ioeconomics c o n s t r u c t i o n l a b o r fo rce r e g i o n a l impac ts

17b. IDENTIFIERSIOPEN-ENDED TERMS

1 6 - A s s T R A c T o m w ~ w * n J The p r i m a r y o b j e c t i v e o f t h i s s t u d y was t o improve t h e accu racy o f soc ioeconomic i m p a c t assessments by p r o v i d i n g an improved methodo logy f o r p r e d i c t i n t h e number o f i n m i g r a t i n g worke rs and t h e i r r e s i d e n t i a l l o c a t i o n p a t t e r n s a t f u t u r e

21. NO. OF PAGES

P.pR'CE s 18. AVAlLABl LlTY STATEMENT

U n l i m i t e d

lo. B cumn CU+S mic nportl n c l a s s i f l e d

20. C I N C ~ n ? f " a s s i % P P C '

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