Developing an Interregional Input–Output Table for Cross-Border ...

ECONOMICS AND RESEARCH DEPARTMENTERD OCCASIONAL STATISTICAL PAPER SERIES

Developing an Interregional Input–OutputTable for Cross-border Economies:

An Application toLao People’s Democratic Republic

and Thailand

Benson Sim, Francisco Secretario, and Eric Suan

July 2007

About the Paper

Benson Sim, Francisco Secretario, and Eric Suan measure the extent of economic interdependency between Mukdahan province in Thailand and Savannakhet province in Lao People’s Democratic Republic by developing an interregional input–output table using the Chenery-Moses model in conjunction with popular data reduction methods such as the simple location quotient method in the input–output tables literature.

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ERD Occasional Statistical Paper1 1ERD Occasional Statistical Paper1 1 16/08/2007 10:39:00 AM16/08/2007 10:39:00 AM

ERD Occasional Statistical Paper Series No. 1

Developing an Interregional Input–Output Table

for Cross-border Economies: An Application to

Lao People's Democratic Republic and Thailand


July 2007

Benson Sim is a Statistician, Francisco Secretario a Technical Consultant, and Eric Suan an Assistant Economics and Statistics Analyst in the Development Indicators and Policy Research Division, Economics and Research Department, Asian Development Bank (ADB). This paper stems from the report on “Estimating An Empirical Interregional Input-Output Table for Mukdahan and Savannakhet” prepared under a project carried out by Francisco Secretario for ADB. The authors are thankful to the various government agencies in Lao People’s Democratic Republic and Thailand for providing the data for the study. The authors are also grateful to Tun Lin, Dalisay Maligalig, and Fan Zhai of the Economics and Research Department and two anonymous referees for their useful comments and constructive suggestions; and Abuzar Asra for his valuable encouragement and guidance during the inital stage of this study.

Asian Development Bank6 ADB Avenue, Mandaluyong City1550 Metro Manila, Philippineswww.adb.org/economics

©2007 by Asian Development BankJuly 2007ISSN 1995-2996

The views expressed in this paperare those of the author(s) and do notnecessarily reflect the views or policiesof the Asian Development Bank.

Foreword

The ERD Occasional Statistical Paper Series is based on papers prepared by staff of the Economics and Research Department, their consultants, or resource persons. The purpose of the Series is three fold. First, it deals with studies on the quality and comparability of the data compiled by the Asian Development Bank from national sources in its developing member countries and data prepared by international organizations. Second, it attempts to fill information gaps by deriving new statistical series from available data. Third, it presents new applications of statistical methods for use in the ADB’s operational work and member countries. The Series papers are prepared mainly for internal readership within the Asian Development Bank, but may be accessed by interested external readers.

Contents

Abstract vii

I. Introduction 1

II. Literature Review 1

III. The Mukdahan–Savannakhet IRIO Framework 2

A. The Ideal Mukdahan–Savannakhet IRIO Model 2 B. Modified IRIO Table for Mukdahan and Savannakhet 5

IV. Developing The Mukdahan–Savannakhet Modified IRIO Table 8

A. Phase 1: Estimation of Inputs, Final Local Demand, and External Trade 8 B. Phase 2: Conversion of Competitive Flows to Noncompetitive Flows and Estimation of Regional Input Coefficients 14 C. Phase 3: Reconciliation and Revalidation of the Integrated IRIO Table 15

V. Main Results and Applications 15

A. Analysis of Economic Structure 15 B. Interregional Analysis and Applications 23 C. Impact Analysis 29

VI. Data Issues 35

VII. Conclusion 36

Appendix 1: List of Input–Output Tables 38Appendix 2: Correspondence between 20 Industries, 10 Major Industries, and 3 Major Sectors 39

Selected References 40

Abstract

This paper constructs a modified interregional input–output (IRIO) table to link the economies of the province of Mukdahan in Thailand and the neighboring Lao People's Democratic Republic province of Savannakhet using the Chenery-Moses model in conjunction with popular data reduction methods such as the simple location quotient method in the input–output (IO) tables literature. A hybrid approach was used to construct the IRIO table. This involved using primary data collected from a specially conducted survey to develop the Savannakhet portion of the table and indirect methods to construct the Mukdahan portion of the table as well as the trade flows. Results showed that the value of trade of these provinces with the rest of the world was much higher than the trade between them. The results also showed that in both provinces, industries in the services sector were found to have generally higher value-added multipliers than industries in the manufacturing sector. The agriculture and forestry industry in Savannakhet and the manufacturing industries in both provinces had high backward and forward linkages. Exports to the rest of the world and consumption were found to have the highest employment multipliers in Mukdahan and Savannakhet, respectively. Mukdahan was also found to have higher net foreign exchange earnings, implying that the Thai province may be able to add greater value to its exports than the Lao PDR province. Finally, the study outlines some key data and methodological issues that could bias the quality of the findings, and suggests solutions to enhance the accuracy and reliability of the results.

I. IntroductIon

Economic interdependence between Lao People’s Democratic Republic (Lao PDR) and Thailand has increased substantially since the latter formally opened its border with the former in the late 1980s. The level of economic interdependency between these two countries was further boosted in 1992 when they and other countries of the Greater Mekong Subregion (GMS) embarked on a program of economic cooperation (known as the GMS Program) to promote development through closer economic linkages; and in 1997 when Lao PDR became a full member of the Association of Southeast Asian Nations (ASEAN).1

This paper measures the extent of economic interdependency between Lao PDR and Thailand at the subnational level by constructing an interregional input–output (IRIO) table that links the cross-border economies of Mukdahan province in Thailand with Savannakhet province in Lao PDR using the Chenery-Moses model in conjunction with popular data reduction methods such as the simple location quotient method in the input–output (IO) tables literature. An IRIO table provides a fairly compact, comprehensive, and detailed accounting framework to model and measure the economic interrelationships between industries located in the study regions. Similar to a single-region IO table, an IRIO table can be used to estimate the magnitude of an external “shock” on major macroeconomic indicators such as output, value-added, income, and employment. However, unlike its single-region counterpart, an IRIO table can also be applied to capture and assess the interregional spillover and feedback effects arising from an exogenous change in demand for the output of any one of the study regions. In other words, constructing an IRIO table will not only allow us to estimate the stimulus to production outside the study region benefiting from, say, an increase in foreign

� The countries of the GMS comprise Cambodia, People’sRepublicofChina,LaoPDR,Myanmar,Thailand,andVietNam.

demand for its output, but also the resultant impact on its output arising from the production stimulus it causes in the other study regions.

The paper is structured as follows. Section II provides a brief survey of the development of IO tables. The accounting framework used to develop the IRIO table for Mukdahan and Savannakhet is outlined in Section III. The methods and data used to construct the modified IRIO table for Savannakhet and Mukdahan are described in Section IV and main results are discussed in Section V. In Section VI, the major data issues that could affect the results are presented, while Section VII concludes.

II. LIteraturerevIew

The basic framework for IO analysis has its antecedents in the Tableau Economique developed by the French economist Francois Quesnay nearly 250 years ago. Quesnay’s tableau describes the relationships between sales and purchases of the various industries of an economy. More than a hundred years later, Leon Walras adapted his model to provide a more concise theoretical formulation of an economic system including consumer purchases and economic representation of technology. However, it was not until the 20th century that Leontief (1936) greatly simplified Walras’ theoretical formulation by assuming the fixity of both technology and trading patterns over time to develop an IO model of the 1919 United States (US) economy to estimate the effects of the end of the First World War on national employment.

The field of IO analysis was advanced further when Isard (1951) extended the work of Leontief to analyze IO tables at the subnational level by publishing a seminal paper on the theoretical structure of interregional IO tables under the assumption that the sectoral and geographical origin of each delivery can be specified. His model has been described as “ideal” by Richardson (1972) because identical sectors in different regions are treated as distinctly separate

2 Benson Sim, Francisco Secretario, and Eric Suan

ERD OCCASiONAl StAtiStiCAl PAPER SERiES Issue No. 1

industries, so that interregional trade flows by region of origin and destination and by industry of source and purchasing sector are fully specified. However, data at this very detailed level of disaggregation are mostly not readily available. Thus, detailed and comprehensive surveys to collect data on regional purchases by sector and regional sales by sector will need to be undertaken. Unfortunately, there is usually not enough time and/or financial resources to conduct this kind of data gathering exercise. Consequently, the “ideal” model has rarely been implemented empirically in its entirety. This has resulted in the development of models that require considerably less data to be statistically implemented. Examples include the Chenery-Moses model, intranational model, and gravity model, all of which involve the calculation of interregional trade flows without having to trace the individual firm’s nonlocal sales and purchases.2 In addition, data reduction methods using secondary data (such as national IO coefficients and other published information) to derive local IO coefficients have also been developed for use in conjunction with these models. Examples include the use of procedures such as the simple location quotient method and commodity balance approaches to split national coefficients into local coefficients and imported inputs. Moreover, to reduce the enormous time and resources needed to conduct full-scale surveys, a hybrid or mongrel approach to constructing IRIO tables has also been utilized. This essentially involves conducting surveys to collect the necessary data for the most prominent or important sectors of the economies concerned and using various nonsurvey methods to obtain the estimates for the other sectors.3

The development of these simplifying models and procedures has resulted in a vast amount of IO work at the interregional level. For example, in recent years, IRIO tables have been developed for European countries such as Austria (Fritz et al. 2006), Finland (Piispala 2000), Italy (Benvenuti and Paniccià 2003), and Spain (Verdura 2000). In the Asian context, various separate studies have been conducted recently to develop IRIO tables for countries such as Japan (Ishikawa and Miyagi 2004), People’s Republic of China (PRC) (Okamoto et al. 2005 and Okuda et al.

� The Chenery-Moses model has also been described as themultiregionalIOmodelbyIsardetal.(�998)aswellasMillerandBlair(�985).

� AverygooddescriptionofthemodelsandtechniquescanbefoundinRichardson(�97�).

2004), Philippines (Secretario 1994 and Secretario et al. 2002), and Viet Nam (Secretario et al. 2003a and 2003b). At the supra-national level, the Institute of Developing Economies–Japan External Trade Organization has been compiling international IO tables linking countries in Asia and the Pacific region since the 1970s. Currently, these tables are available for reference years 1975, 1985, 1990, 1995, and 2000.

A rather unique study covering regions located in different countries was also conducted by Ichihashi (2000) to assess the economic dependency between Hiroshima (a prefecture in Japan) and Heilongjiang (a province of the PRC). To our knowledge, this study appears to be the only one that has been conducted so far to measure economic dependence between regions located in different countries in Asia. However, the study only made use of the separate IO tables for each region to assess economic dependence in terms of net exports. There was no attempt to develop a full-fledged set of IRIO tables for analysis. The paucity of studies to construct multicountry IRIO tables at the subnational level could be mainly due to the severe problems and constraints inherent in collecting and assembling consistent and reliable subnational data for the regions concerned. Thus, our study to develop an IRIO table for Mukdahan and Savannakhet constitutes a very useful contribution to the literature of IRIO tables.

III. theMukdahan–Savannakhet IrIoFraMework

A. The Ideal Mukdahan–Savannakhet IRIO Model

Assuming the availability of an ideal data set, the economic flows between Mukdahan and Savannakhet can be presented in the form of the Isard-type IRIO table in Figure 1. The flows in the model are valued at producers’ prices (i.e., prices net of trade and transport margins, but gross of product taxes), while the reference year for the model is 2003.4 The model contains 20 industries, four final local demand components, and four primary inputs or value-added

� �00� is used as the reference year for the model to ensureconsistency with the reference year of the Savannakhet IOtabledevelopedbyAsraetal.(�006).Aswillbeseenlater,theSavannakhetIOtablewillbeheavilyusedinthedevelopmentoftheSavannakhetportionofthemodifiedIRIOtableinourstudy.

July 2007 �

DevelopINg aN INterregIoNal INput–output table for Cross-borDer eCoNomIes: aN applICatIoN to lao people's DemoCratIC republIC aND thaIlaND

components in each province. The model also contains a third region—rest of the world (ROW)—which groups, for convenience, all areas (rest of Thailand, rest of Lao PDR, and all foreign territories) outside the two provinces.

The notations used in Figure 1 are defined as follows:

XDD is a 20 × 20 matrix, where each element is a flow from one of the 20 industries to another of the 20 industries in Mukdahan.

XDS is a 20 × 20 matrix containing analogous interindustry flows, but from Mukdahan to Savannakhet.

YDD is a column vector of 20 elements, where each element represents a flow from one of the 20 industries in Mukdahan to final local demand (i.e., private consumption expenditure, government consumption expenditure, gross fixed capital formation, and change in inventories) in the same province.

YDS is a column vector of 20 elements containing analogous final demand flows, but from Mukdahan to Savannakhet.

ED is a column vector of 20 elements, where each element is an export of Mukdahan by industry to the ROW.

XD is a column vector of 20 elements, with each element representing the gross output of each of the 20 industries in Mukdahan.

XSD is a 20 × 20 matrix, where each element is a flow from one of the 20 industries in Savannakhet to another of the 20 industries in Mukdahan.

XSS is a 20 × 20 matrix containing analogous interindustry flows, but within Savannakhet.

YSD is a column vector of 20 elements, where each element represents a flow from one of the 20 industries in Savannakhet to final local demand (i.e., private consumption expenditure, government consumption expenditure, gross fixed capital formation, and change in inventories) in Mukdahan.

YSS is a column vector of 20 elements containing analogous final demand flows, but within Savannakhet.

ES is a column vector of 20 elements, where each element is an export of Savannakhet by industry to the ROW.

Figure 1. Accounting Framework for 200� Mukdahan–Savannakhetinterregional iO table, Noncompetitive type

to

From

intermediate Demand Final Demand

total Gross OutputMKD SVK MKD SVK ROW

1…j…20 1…j…20 E M

intermediate

inputs

MKD

1:i:

20

XDD XDS YDD YDS ED 0 XD

SVK

1:i:

20

XSD XSS YSD YSS ES 0 XS

ROW

1:i:

20

IMWD IMWS FMWD FMWS 0 MT 0

Gross Value Added VD' VS' 0 0 0 tT

total Gross input XD' XS'

MKD means Mukdahan; SVK means Savannakhet; ROW means rest of world; E means exports to ROW; M means imports from ROW.Source: Developed by the authors.

� Benson Sim, Francisco Secretario, and Eric Suan


XS is a column vector of 20 elements, with each element representing the gross output of each of the 20 industries in Savannakhet.

IMWD is a 20 × 20 matrix, where each element is a flow from one of the 20 industries from the ROW to another of the 20 industries in Mukdahan.

IMWS is a 20 × 20 matrix containing analogous flows from the ROW to Savannakhet.

FMWD is a column vector of 20 elements, where each element is a flow from one of the 20 industries from the ROW to the final local demand in Mukdahan.

FMWS is a column vector containing analogous flows from the ROW to Savannakhet.

MT is a column vector of 20 elements, with each element representing the total imports (with a negative sign) by industry of Mukdahan and Savannakhet.

VD' is a row vector of 20 elements, with each element defining the primary inputs (i.e., compensation of employees, indirect taxes less subsidies, depreciation, and gross operating surplus) by industry flowing into Mukdahan.

VS' is a row vector of 20 elements containing analogous flows into Savannakhet.

TT is the total value of tariff or import duties and taxes generated in both Mukdahan and Savannakhet.

XD' is a row vector of 20 elements defining total input by industry for Mukdahan.

XS' is a row vector of 20 elements defining total input by industry for Savannakhet.

The outlined IRIO model is of the noncompetitive, open, and static variety. It is noncompetitive because it makes an explicit distinction between regionally produced and nonregionally produced goods and services. Such a distinction provides a better reflection of the use of local production technology and inputs in the production of output in each province. The “openness” of the model is derived from the fact that economic activities are split into the intermediate and final demand categories. The transactions in the former category can be explained by the model, while the latter category contains exogenous transactions that must be initially known or given. The static

nature of the model is a consequence of the absence of a time dimension from it.

A system of IRIO tables is balanced, implying that the supply and demand sides are equal. Using Figure 1, this equality can be translated into the following accounting identities:

x xiD

ijD

j= =∑ ∑=

1

20

1

20

(i.e., total output of industry i summed over all the 20 industries in Mukdahan is equal to total input of industry j summed over the same industries), and

x xiS

ijS

j= =∑ ∑=

1

20

1

20

(i.e., total output of industry i summed over all the 20 industries in Savannakhet is equal to total input of industry j summed over the same industries).

Figure 1 can also be used to form the following balancing equations in matrix form:

XD = XDDi + XDSi + YDD + YDS + ED (1)

XS = XSDi + XSSi + YSD + YSS + ES (2)

In both equations, i represents a column vector of appropriate ones. The first term on the right hand side of equation (1) represents interindustry sales in Mukdahan; the second term denotes the interregional trade flows from Mukdahan to Savannakhet; the third and fourth terms represent the sales of the output of Mukdahan to final local demand in Mukdahan and Savannakhet, respectively; while the last term represents the exports of Mukdahan to the ROW. An analogous explanation applies to equation (2).

Using Leontief’s assumption of linearity or first-order homogeneity in the production functions, we can define the following regional input coefficients in matrix form:

A XDD DD D=

−

X1

ˆ (3)

A XDS DS S=

−

X1

ˆ

(4)

July 2007 �


A XSD SD D=

−X

1

ˆ (5)

A XSS SS S=

−X

1

ˆ

(6)

Equations (3) and (6) represent the matrices of intraregional direct input coefficients, while equations (4) and (5) stand for the matrices of interregional trade coefficients. Substituting these structural equations into equations (1) and (2), we have:

XD = ADDXD + ADSXS + YDD + YDS + ED (7)

XS = ASDXD + ASSXS + YSD + YSS + ES (8)

Combining equations (7) and (8), we have:

X

X

A A

A A

X

X

Y

Y

D

S

DD DS

SD SS

D

S

D

S

=

+

(9)

where YD = YDD + YDS + ED and YD = YSD + YSS + ES.

In equation (9), YD and YS are column vectors of 20 elements each, with each element representing the sum of flows from one of the 20 industries in Mukdahan and Savannakhet, respectively, to final demand in Mukdahan and Savannakhet and the ROW.

Simplifying equation (9), we have:

X

X

I 00 I

A A

A A

Y

Y

D

S

DD DS

SD SS

D

S

=

−

−1

(10)Equation (10) can be further simplified and shown

its generalized form as:

X = BY (11)

where X is the matrix of regional outputs, X

X

D

S

; Y

is the matrix of final demand, Y

Y

D

S

; and B is the

interregional Leontief inverse matrix, I 00 I

A A

A A

DD DS

SD SS

−

−1 .

In order to measure the spillover and feedback effects caused by interregional trading, equation (9) can first be expanded to obtain the following simultaneous equations:

X I A A X YD DD DS S D= −( ) +( )−1

(12)

X I A A X YS SS SD D S= −( ) +( )−1 (13)

Equations (12) and (13) can then be further expanded and rearranged to obtain the following matrices:

X

X

F 0

0 F

I S

S I

M 0

0 M

YD

S

D

S

DS

SD

D

S

=

DD

SY

(14)

where M I A M I A

S M A S M A

F I S S

D DD S SS

DS D DS SD S SD

D DS SD

= −( ) = −( )= =

= −( )

− −

−

1 1,

,11 1, F I S SS SD DS= −( )−

The unknowns MD and MS, SDS and SSD, and FD and FS account for the intraregional linkages and interregional spillover and feedback effects, respectively.

B. ModifiedIRIOTableforMukdahan and Savannakhet

Unfortunately, the data needed to implement the “ideal” framework outlined in Figure 1, in particular, the interregional interindustry flows, are mostly not readily available. This means that equation (11) cannot be readily used to estimate the Leontief inverse. Instead, we will rely on the Chenery-Moses model independently developed by Chenery (1956) and Moses (1955) to develop a modified IRIO table to link the economies of Mukdahan and Savannakhet in our study.5 The starting point for the development of the modified IRIO table is the intraregional IO framework in Figure 2.

The notations used in Figure 2 are defined as follows:

5 AnearlycomparisonoftheIsardandChenery-MosesmodelscanbefoundinHartwick(�97�).TheChenery-Mosesmodelovercomes the severe data needs of the Isard model, whichrequiresdataontheshipmentsofgoodsbetweensectorsandbetweenregions,byrequiringonlydataontheflowofgoodsbysectorfromtheorigintothedestinationregion.



X.D is a 20 × 20 matrix, where each element is a flow from one of the 20 industries (regardless of origin) to another of the 20 industries in Mukdahan.

Y.D is a column vector of 20 elements, where each element represents a flow from one of the 20 industries (regardless of origin) to final local demand (i.e., private consumption expenditure, government consumption expenditure, gross fixed capital formation, and change in inventories) in Mukdahan.

EDS is a column vector of 20 elements, where each element is an export of Mukdahan by industry to Savannakhet.

EDW is a column vector of 20 elements containing analogous flows to the ROW.

XD is a column vector of 20 elements, with each element representing the gross output of each of the 20 industries in Mukdahan.

X.s is a 20 × 20 matrix, where each element is a flow from one of the 20 industries (regardless of origin) to another of the 20 industries in Savannakhet.

Y.s is a column vector of 20 elements, where each element represents a flow from one of the 20 industries (regardless of origin) to final local demand (i.e., private consumption expenditure, government consumption expenditure, gross fixed capital formation, and change in inventories) in Savannakhet.

ESD is a column vector of 20 elements, where each element is an export of Savannakhet by industry to Mukdahan.

ESW is a column vector of 20 elements containing analogous flows to the ROW.

XS is a column vector of 20 elements, with each element representing the gross output of each of the 20 industries in Savannakhet.

MSD is a column vector of 20 elements defining imports (with a negative sign) by industry from Savannakhet to Mukdahan.

MWD is a column vector of 20 elements containing analogous flows from the ROW into Mukdahan.

MDS is a column vector of 20 elements defining imports (with a negative sign) by industry from Mukdahan to Savannakhet.

MWS is a column vector of 20 elements containing analogous flows from the ROW into Savannakhet.

VD' is a row vector of 20 elements defining the primary inputs (i.e., compensation of employees, indirect taxes less subsidies, depreciation, and gross operating surplus) by industry flowing into Mukdahan.

VS' is a row vector of 20 elements containing analogous flows into Savannakhet.

TD is the total value of import duties and taxes generated in Mukdahan.

TS is the total value of import duties and taxes generated in Savannakhet.

XD' is a row vector of 20 elements, with each element defining total input by industry for Mukdahan.

XS' is a row vector of 20 elements, with each element defining total input by industry for Savannakhet.

Figure 2. Accounting Framework for 200� intraregional iO tableMukdahan Savannakhet

intermediate Demand

Final Demand

tGO

intermediateDemand

Final Demand

tGO

local Exports imports

local

Exports imports

1... j … 20 SVK ROW SVK ROW 1... j … 20 MKD ROW MKD ROW12:i:

1920

X.D Y.D EDS EDW MSD MWD XD X.s Y.s ESD ESW MDS MWS XS

GVA

VD' tD VS' tS

TGI XD' XS'

TGO means total gross output; TGI means total gross input; GVA means gross value added; ROW means rest of world; MKD means Mukdahan; SVK means Savannakhet. Source: Developed by the authors.

July 2007 7


As can be observed from Figure 2, the basic idea of the modified IRIO table is that intraregional IO tables that make use of transactions data that are more readily available or derivable are developed first. For instance, information on the amount of input from industry i to be used by industry j in, say, Mukdahan (i.e., xij

D. ) is likely to be more easily obtainable than information on the amount of input from industry i from Savannakhet used by industry j in Mukdahan (i.e., xij

SD ).Using the data in Figure 2, we can define the

following regional technical coefficients in matrix form:A X.D .D D

= ( )X$-1

(15)A X.S .S S

= ( )−

X$1 (16)

The interconnections among the regions in the modified IRIO table framework are captured in the form of an interregional trade coefficients matrix in a very different manner from the “ideal” IRIO framework. In the modified IRIO table framework, trade flows are estimated by product in order to exploit the types of data likely to be available. The elements of the interregional trade coefficient matrix, denoted by ci

RS (R, S = Mukdahan and Savannakhet), show the proportion of all of product i used in region S that comes from each region R.6 Interregional trade coefficients are obtained from the flow from R to S divided by the total inflow into the latter and are defined as:

ct

tiRS i

RS

iRS

R

n=

∑.

.

where (n = Mukdahan, Savannakhet) (17)

In equation (17), tiRS. denotes the amount of

product i that is shipped from region R to region S, irrespective of the industry of destination in the latter. These flows will include shipments to the producing sectors as well as final demand in the destination region, implying that the proportion of the supply of goods and services in each sector in the destination region that comes from the shipping region is the same.

6 Asthereare�0productsinourmodel,therewillbe�0suchmatricesinall.

The interregional trade coefficients can be rearranged in the form of a column vector for each origin-destination pair of regions, which can also be transformed into a diagonal matrix as follows:

(18)

(19)

Using the matrices for the regional technical coefficients and interregional trade coefficients, we can estimate the regional input coefficients in equation (9) as follows:

A ADD DD .D≈ C$ (20)

A ADS DS .S≈ C$

(21)

A ASD SD .D≈ C$

(22)

A ASS SS .S≈ C$

(23)

As the trade coefficient information used in our modified IRIO framework is of an origin-to-destination format, it also includes shipments not only to industries, but final demand as well. Consequently, in the modified IRIO framework, a final demand term, such as Y.D, is taken to be satisfied from a “pool” of goods, i.e., partly by purchases from industries in the region and partly by purchases from industries outside the region.

C CDD DS=

=

c

c

c

c

DD

nDD

DS

nDS

1 1

.

.

.,

.

.

.

=

=,...

,...

C CSS SD

c

c

c

c

SS

nSS

SD

n

1 1

SSD

Cc

c

Cc

c

DD

nDD

DS

nDS

$K

M O M

L

$K

M O M

L

DD DS=

=

1 10

0

0

0

,,

Cc

c

Cc

c

SS

nSS

SD

nSD

$K

M O M

L

$K

M O M

L

SS SD=

=

1 10

0

0

0

,

=( )n 20



Given this view, the fundamental equations in our modified IRIO table can be written in matrix form as

X

X

A

A

X

X

D

S

DD DS

SD SS

D

S

D

S

=

C C

C C

$ $

$ $

.

.

0

0

+

+

C C

C C

$ $

$ $

DD DS

SD SS

D

S

DW

SW

Y

Y

E

E

.

.

−

M

M

WD

WS

(24)which can be reduced to

X

X

I 00 I

A A

A A

D

S

DD .D DS .S

SD .D SS .S

=

−

C C

C C

$ $

$ $

+

−1

C C

C C

$ $

$ $

DD DS

SD SS

D

S

DWY

Y

E

E

.

. SSW

WD

WS

M

M

−

(25)

To obtain the interregional and spillover effects, equation (24) can first be expanded to obtain the following simultaneous equations:

X I A A X Y Y E MD DD D DS S S DD D DS S D D= −

+ + + −

−C C C C$ $ $ $. .

1

(26)

X I A A X Y Y E MS SS S SD D D SS S SD D S S= −

+ + + −

−C C C C$ $ $ $. .

1

(27)

Equations (26) and (27) can be further expanded and rearranged to obtain the following matrices:

X

X

0

0

I

I

0

0

D

S

D

S

DS

SD

D

S

=

F

F

S

S

M

M

%

%

%

%

+

C C

C C

$ $

$ $

DD DS

SD SS

D

S

DW

SW

Y

Y

E

E

.

. −

M

M

WD

WS

%

%

(28)

where, M C M C

S M C

$ $

% $

D DD .D S SS .S

DS D DS .S

I A I A

A

= −

= −

=

− −1 1

,

,,

,

S M C

F S S F S S

% $

% % % % % %

SD S SD .D

D DS SD S SD DS

A

I I

=

= −( ) = −( )− −1 1

%

%

%

%

Equation (25) and, by extension, equation (28) are the equations that can be estimated using more readily available or derivable data. In equation

(28), the unknowns MD% and MS% , SDS% and SSD% , and FD% and FS% account for the intraregional linkages

and interregional spillover and feedback effects, respectively, in the modified IRIO framework.

Iv. deveLopIngtheMukdahan– SavannakhetModIFIedIrIotabLe

In many countries, IO tables are typically developed using the cost or expenditure method. This means that the tables are formed by merging the cost or input structures of industries as well as the consumption patterns of the components of final demand. Such a column-wise method of constructing IO tables is used because of the dearth of data that trace the flow of outputs from producer to consumer.

Likewise, the modified IRIO table in our study was developed using the cost method. The construction of the modified IRIO table was generally carried out using the 1968 System of National Accounts guidelines in three major phases:

Phase 1: Estimation of Inputs, Final Local Demand, and External Trade

Phase 2: Conversion of Competitive Flows to Noncompetitive Flows and Estimation of Regional Input Coefficients

Phase 3: Reconciliation and Revalidation of the Integrated IRIO table

As the source data were valued in the respective currencies of Thailand and Lao PDR, they were converted into US dollars using the nominal average exchange rates for 2003 during the process of developing the modified IRIO table.7

A. Phase 1: Estimation of Inputs, Final Local Demand, and External Trade

This phase involves the development of separate intraprovincial competitive IO tables (as shown in Figure 2) for Mukdahan and Savannakhet by deriving estimates of inputs, final local demand, and external trade. The bulk of the work in this phase was devoted to the construction of the intra-Mukdahan IO table as a survey-based IO table for Savannakhet has already 7 The exchange rates used were US$� = �9.5097 Baht and

US$�=9,6��Kips.

July 2007 �


been developed in a separate unpublished study by Asra, Secretario, and Suan (2006).8

1. Compilation Methodology and Data Sources

The more appropriate method of estimating the inputs is to conduct specialized IO surveys of enterprises and use public administrative/regulatory reports to obtain primary data on production costs. This method was used to construct the IO table for Savannakhet. However, due to time and budgetary constraints, no surveys were conducted in the case of Mukdahan. Instead, a nonsurvey method was used to construct the intra-Mukdahan IO table using solely the following secondary statistical information provided by various government agencies such as the Thai National Statistical Office and Thai National Economic and Social Development Board.9

(i) National Input–Output Table for Thailand for Year 2000

(ii) Gross Provincial Product (GPP) by Sector for Mukdahan for year 2003

(iii) 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region

(iv) 2003 Survey of Household Income and Expenditure for the Northeastern Region

(v) Exports/Imports Data from Mukdahan Customs Office

(vi) Exports/Imports Data from Savannakhet Customs Office

(vii) Thailand Foreign Trade Statistics(viii) Other relevant data from administrative reports

such as cost and returns data for agriculture, government budget, etc.

2. The Intra-Mukdahan IO Table

Given the above statistical information, the competitive intra-Mukdahan IO table was developed using the following steps:

8 Moredetailsontheconstructionofthistablecanbeobtainedfromthestudy.

9 Since a survey-based approach was used to develop the IOtable for Savannakhet, this means that a hybrid approachinvolvingtheuseofsurveysandnonsurveymethodswasusedtodevelopourmodifiedIRIOtable.

Step 1. Estimation of Inputs (i.e., X.D and VD)Step 2. Estimation of Final Local Demand Vectors

(i.e., Y.D);Step 3. Estimation of External Trade VectorsStep 4. Balancing the Intra-Mukdahan IO Table

(i) Step 1: Estimation of Inputs (X.D and VD)

Inputs for the 20 industries in Mukdahan were estimated by assuming that their input structure can be proxied by the corresponding IO coefficients from the Thailand IO table. As the national IO table is split into 180 industries, they were merged and combined to conform to the sectoral breakdown of the Mukdahan IO table before the national IO coefficients were applied. The national IO coefficients for 14 of the 20 industries as outlined in Data Set A were further modified using data from the sources listed in order to generate a set of input ratios that were more reflective of Mukdahan’s production cost structure.

Intermediate and value-added ratios for the crops and livestock, poultry, and fishery industries were derived from costs and returns survey data for crops cultivation and livestock raising provided by the Bureau of Agricultural Economics, Ministry of Agriculture.

As Mukdahan is one of the provinces in the northeastern region of Thailand, the 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region (SE) was used to modify the national coefficients for the manufacturing (05-11) as well as the private services industries (16-18 and 20) on the basis that the production cost structure for the province could be proxied by the regional one. Where necessary, the industries in the survey were first grouped to fit into the sectoral breakdown of the Mukdahan IO table before the national coefficients were modified. In the case of public administration, input indicators derived from the government budget report of the Mukdahan provincial government were used.

For the remaining six industries listed below, the corresponding national IO coefficients were adopted as proxies due to the unavailability of appropriate subnational indicators:



Industry 03: Forestry and loggingIndustry 04: Mining and quarryingIndustry 12: Electricity and water supplyIndustry 13: ConstructionIndustry 14: TransportationIndustry 15: Post and telecommunications

Data Set A. Data Sources for Estimating Mukdahan’s input Structure

industry Data Source01 Crops Bureau of Agricultural Economics, Ministry of Agriculture02 Livestock and poultry, fishery Bureau of Agricultural Economics, Ministry of Agriculture05 Food, beverage, and tobacco 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region06 Textiles, garments, and leather products 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region

07 Wood and paper products; printing/publishing 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region

08 Chemical products; petroleum 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region

09 Nonmetallic mineral products 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region

10 Metal products, machinery, equipment, and spare parts 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region

11 Other manufactured goods 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region16 Wholesale and retail trade 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region17 Banking, insurance, business services 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region18 Real estate and ownership of dwellings 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region19 Public administration Government Budget, Mukdahan Provincial Government20 Personal, social, and community services 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region

Source: Compiled by the authors.

a. ModifyingtheNationalIOCoefficients

The input structures for the 14 industries listed in Data Set A were estimated as follows. Intermediate input ratios were obtained from the following formula:

aTIIR

TIIRaij

D jSE

jN ij

N. =

(29)

where aijD. is the estimated coefficient for

Mukdahan’s consumption of product i by industry j;

TIIR jSE is the ratio of the total intermediate input of industry j to its corresponding revenue (or output), as derived from the SE;

TIIR jN is the ratio of the total intermediate input of industry j to its corresponding output, as recorded in the national IO table; and

aijN is the coefficient for the nation’s consumption of

product i by industry j.Primary input (value-added) ratios were estimated

using the following relationship:

bg

gbpj

D jSE

jN pj

N=

var

var (30)

where bpjD is the ratio of Mukdahan’s value added, p, for industry j to its corresponding gross output, x j

D ;g j

SEvar is the ratio of gross value added (GVA) of industry j to its total revenue (or output), as derived from the SE;

g jNvar is the ratio of the GVA of the nation’s industry j to its corresponding gross output, and

bpjN is the national GVA coefficient of industry j for

primary input p.

This modified set of input coefficients, when multiplied by an estimated vector of gross outputs, gives the monetary value of input transactions in Mukdahan. Mathematically, the sum of the intermediate and primary input coefficients should be equal to one. In cases where the sum of these coefficients was not equal to unity, proportional adjustments were made to ensure that they added up to one.

July 2007 11


BD is the matrix of primary input coefficients for Mukdahan;

ˆ DX is the diagonal matrix of sectoral gross outputs for Mukdahan; and

i is a column vector of appropriate ones.

(ii) Step 2: Estimation of Final Local Demand Vectors

The Mukdahan IO model classifies exogenous final demand into four components of final local (domestic) demand and four categories of external trade. The estimation of the final local demand components was done independently using the data sources in Data Set B.

a. PCE Vector

Total PCE was first estimated by multiplying the average household expenditure for Mukdahan, as reported in the 2003 Survey of Household Income and Expenditure for the Northeastern Region, by the estimated number of households in the province for the same year. The PCE vector was then obtained by multiplying the estimated total PCE for Mukdahan by a vector of expenditure patterns derived from the same household survey. As the PCE data are disaggregated in terms of commodities, they were allocated to the appropriate industry in the Mukdahan IO table before the vector of expenditure patterns was obtained. Moreover, as the resulting PCE vector was initially valued at purchaser’s price, it was converted to producer’s price by netting out the trade and transport margins on PCE on goods at purchaser’s price. Trade and transport margin ratios derived from the national IO table were used in the netting out process. On the other hand, no margins were applied to household expenditure on services.

b. Estimation of Gross Output

Given estimates of GPP or gross value added by industry for Mukdahan for the year 2003 and the input coefficient matrix, gross output was estimated using the following formula:

xGVA

GVARjD j

D

jD

= (31)

where x jD is the estimated gross output of industry j

in Mukdahan for j = 1,2,...,20GVAj

D is the given gross value added (or total primary input) of industry j in Mukdahan; and

GVAR jD is the gross value added ratio of industry j in

Mukdahan.

c. Calculating the Input Transactions

The estimates of inputs were then calculated as follows. Intermediate input transactions were estimated using the following relationship:

X A.D .D= XD$ (32)

where X.D is the matrix of intermediate input transactions of the competitive-import type for Mukdahan;

A.D is the matrix of regional technical coefficients for Mukdahan; and

ˆ DX is the diagonal matrix of sectoral gross outputs for Mukdahan.

Estimates of primary input transactions were obtained using the following relationship:

V B X iD D D '= ( )ˆ (33)

where VD is the primary input or value added column vector for Mukdahan;

Data Set B. Data Sources for Estimating Mukdahan’s Final local Demand Final local Demand Data Source

B-1. Private consumption expenditure (PCE) 2003 Survey of Household Income and Expenditure for the Northeastern RegionB-2. Government consumption expenditure (GCE) Mukdahan Provincial Government Budget Report, 2003B-3. Gross fixed capital formation (GFCF) 2003 Survey of Establishments for the Industry and Services sectors for the Northeastern

RegionB-4. Change in inventories (CI) 2003 Survey of Establishments for the Industry and Services sectors for the Northeastern

RegionSource: Compiled by the authors.



b. GCE Vector

No entries were recorded in the GCE vector, except for the cell related to public administration. In this cell, the total gross output that is consistent with national accounts concept was recorded.

c. GFCF and CI Vectors

The GFCF and CI vectors were approximated based on regional ratios derived from the 2003 Survey of Establishments for the Industry and Services Sectors for the Northeastern Region. For example, capital expenditure-to-output ratios by industry and by type of durable equipment as estimated from the survey were applied to the corresponding Mukdahan output estimates to obtain an estimate of expenditure for durable equipment. To complete the GFCF vector, the total value of output of construction less expenditure by industries and households for housing repair and maintenance was recorded in this GFCF vector.

Similarly, the estimates of CI were obtained by applying the ratio of change in stocks to total output or revenue for each industry from the survey to the corresponding total output. As these estimates are perceived to be weak, the CI estimates were later accordingly adjusted during the reconciliation and revalidation phase.

Merging the results of Steps 1 and 2 with a residual vector of net exports resulted in the following equation: X X Y E MD .D .D D= + + −( ) (34)

The next step was to split the residual net exports vector into its four components as follows:

E M E E M MD DS DW SD WD−( ) = +( ) − +( )

(35)

(iii) Step 3: Estimation of External Trade Vectors

The following data on Mukdahan's external trade were available (see Data Set C):

Data Set C. Data Sources for Estimating Mukdahan’s External trade

External trade Data SourceC-1. Mukdahan exports to Savannakhet, EDS

Available by product from Mukdahan Customs and Immigration Office

C-2. Mukdahan imports from Savannakhet, MSD

Available by product from Mukdahan Customs and Immigration Office

C-3. Mukdahan exports to ROW, EWS

Available from Mukdahan Customs and Immigration Office

C-4. Mukdahan imports from ROW, MWD

Available from Mukdahan Customs and Immigration Office

Source: Compiled by the authors.

Breaking up the net exports vector into its four components required an assessment of the raw data collected from the Mukdahan Customs Office as external trade data compiled by line agencies do not usually conform to the producer-to-user concept in IO accounting. The need to distinguish direct users from traders or middlemen as well as foreign trade transactions such as in-transit/cross hauling deliveries should also be taken into account and rationalized before the development of the external trade vectors.

An assessment of the four data sets found that data sets C-1 and C-2 were useful for measuring the external trade between Mukdahan and Savannakhet. A better understanding of the nature of these two datasets was obtained after a series of interviews and discussions with trade experts from Mukdahan’s Customs Office. In contrast, data sets C-3 and C-4 (Mukdahan trade data with ROW) were found to be not so useful as the product classification was too aggregated and information on the origin and destination of the products by province was too vague.10

Making data sets C-3 and C-4 useful would require time-consuming and costly special surveys to be conducted or special tabulations of export/import customs manifests to determine the origin-destination of trade flows at the subnational level. Due to the lack of budgetary resources, the missing data were estimated using the simple location quotient (SLQ) method.

�0 Thisisunderstandablesinceinmanycountries,foreigntradestatisticsarenormallycompiledatthenationallevelonly.

July 2007 1�


a. SLQ Method

The first step in splitting the net exports vector was to calculate by the SLQ method Mukdahan’s total imports, whether sourced from Savannakhet or from ROW. The SLQ method assumes that the needs of region R for output i in each industry relative to the needs for output i in each of these industries nationally are the same as the ratio of the total regional to the total national output. In equation form, the SLQ is calculated as:

SLQ

QT

QT

iR

iR

R

iN

N

=

(36)

whereSLQi

R is the simple location quotient of product i in region R;

QiR is a measure of economic activity of industry i in

region R;Qi

N is a measure of economic activity of industry i in the nation;

TR is a measure of aggregate economic activity in region R; and

TN is a measure of aggregate economic activity in the nation.

An SLQ is a measure of a region’s self-sufficiency in production. From equation (36), it can be inferred that if SLQi

R is less than 1, region R is presumed to import some of the output of product i from elsewhere. Conversely, if SLQi

R is equal to or greater than 1, region R is viewed as self-sufficient with respect to its output i.

The SLQ method was used to quantify the total imports of Mukdahan by product, regardless of the geographic source. SLQs were estimated using sectoral GVA as measures of economic activity since such data are available at the provincial and national levels.

b. Estimating the Import Vectors

By the SLQ approach, the import content of the intersectoral transactions in the IO table of the competitive type was calculated as:

tm 1 SLQ xij i ij= −( ) (37)

where tmij is the total import content value of product i consumed by industry j,

(1–SLQi) is the import content ratio of product i, and xij is the total value of product i consumed by column

industry j. If SLQi ≥ 1.0, then tmij = 0.

Using equation (37), a total imports table for Mukdahan was constructed, the row sums of which represented an initial estimate for the column vector of total imports, MTD, which in the case of Mukdahan’s economy, is equal to Mukdahan’s imports from Savannakhet plus imports from the ROW, i.e., MTD = MSD + MWD.

Given the available data for column vector MSD, the unknown ROW imports vector, MWD, was then residually calculated as:

MWD = MTD – MSD (38)

Solving equation (38), the remaining unknown vector, EDW, was residually obtained from equation (35) as:

EDW = (E – M)D – EDS + (MSD + MWD) (39)

In general, a similar approach was also used to split Savannakhet’s total exports and total imports into their respective destinations and origins.

c. Reconciling and Revalidating the External Trade Vectors

The reconciliation process took into consideration the following accounting identities in a bi-region IRIO framework:

(i) Mukdahan’s outflows to Savannakhet = Savannakhet’s inflows from Mukdahan, i.e., EDS = MDS

(ii) Mukdahan’s inflows from Savannakhet = Savannakhet’s outflows to Mukdahan, i.e., MSD = ESD

Moreover, overall intersectoral adjustments had to be made to correct counterintuitive results such as negative entries in the residual exports vector as

1� Benson Sim, Francisco Secretario, and Eric Suan


well as exports exceeding outputs before the external trade data for both Mukdahan and Savannakhet were finalized.

(iv) Step 4: Balancing the Intra-Mukdahan IO Table

The intra-Mukdahan IO table of the competitive type was initially formed by integrating the estimated intermediate (production input) and final demand blocks. This process, however, resulted in an unbalanced IO table, whereby the row totals in most of the sectors were observed to be not equal to their corresponding column totals. This result was primarily due to the independent data sources used in estimating the column vectors. Consequently, the IO table had to be balanced in order to ensure the equality of the respective column and row totals.

A modified RAS method of balancing was used in this study. The method initially involved a cross-examination of the cell elements in those sectors where the differences between the row and column totals were observed to be significantly large. Revision of initial cell entries was done by referring to appropriate available indicators such as those derived from the Thai national IO table. Intuitive judgment was quite heavily used in the cell-by-cell revision process, after which the simple bi-proportional RAS method was applied when the column-row differentials were found to be significantly small.

B. Phase 2: Conversion of Competitive Flows to Noncompetitive Flows and Estimation of RegionalInputCoefficients11

This phase involved the development of the modified IRIO table using the competitive intraregional IO tables for both provinces. As the data on intermediate flows and final demand, which had been derived up to this stage were of the competitive type, their import content had to be removed. This was done by constructing satellite tables on imports.

�� The detailed process involved in obtaining the regionaltechnical coefficients and interregional trade coefficients inthisphasehasbeendescribedearlierinSectionIII.

1. Estimation of Mukdahan’s Noncompetitive Flows

The estimates of imports, MSD and MWD, were split into their intermediate input requirements and final local demand requirements using the following series of equations:

X X TCSD SDD= ( )ˆ. (40)

where XSD and X.D are as defined earlier and TCSDˆ is a diagonal matrix of interregional trade coefficients,

tciSD m

tdiSD

iD..= ,where mi

SD. is Mukdahan’s import

of product i from Savannakhet; and tdiD is the total

supply of product i in Mukdahan.I WD WDM X TC.D= ( )ˆ (41)where lMWD is as defined earlier and TCWDˆ is a

diagonal matrix of trade coefficients, tciWD m

tdiWD

iD..= ,

where miWD. is Mukdahan’s import of product i from

ROW.

XDD = X.D – XSD – IMWD (42)

where XDD is as defined earlier.

Y TC YSD SD .D=

ˆ (43)

F WD WDM TC Y.D= ( )ˆ (44)

YDD = Y.D – YSD – FMWD (45)

where YSD, Y.D, FMWD and YDD are as defined earlier.

2. Estimation of Savannakhet’s Noncompetitive Flows

Similarly, the estimates of imports, MDS and MWS, were split into their intermediate input requirements and final local demand requirements using the same method.

July 2007 1�


3. EstimationofRegionalInputCoefficients

The data obtained were then used to implement the Chenery-Moses model to convert the intraregional IO tables for the two provinces into a modified IRIO table so that the regional input coefficients and Leontief inverse could be estimated.12

C. Phase 3: Reconciliation and Revalidation of the Integrated IRIO Table

The final phase in the overall compilation process involved the revalidation of the estimates. The revalidation process involved performing consistency checks on the overall framework and the cell entries in the various blocks of the table. Special attention was paid to the trade flow estimates since these were mainly derived through indirect methods.

v. MaInreSuLtSandappLIcatIonS

This section describes and explains the key results and applications of the study. A comparison of the economies of both provinces is made first, before the findings of applications such as multiplier, linkage, and impact analyses, and spillover and feedback effects are presented and analyzed. For the purpose of this paper, the results are presented based on the IO tables for 10 major industries, which are further aggregated into three major sectors, where appropriate.13

A. Analysis of Economic Structure

This subsection compares and analyzes the economies of both provinces. The supply and demand situation, sources of intermediate inputs, self-sufficiency rates, as well as structure of output, GPP, and demand for 2003 are examined.

�� ThesoftcopyoftheintraregionalMukdahanandSavannakhetaswellastheIRIOtablesatthe�0-industryand�0-industrylevels (as listed in Appendix �) can be obtained from theauthorsuponrequest.

�� The table mapping the �0 industries into the �0 majorindustries and threemajor sectors ispresented inAppendix�.

1. Supply and Demand

The economy of Mukdahan is smaller than that of Savannakhet in terms of the volume of economic activities. As shown in Table 1, its total available supply of goods and services in 2003 amounted to US$601.9 million at current producers’ prices, compared to Savannakhet’s US$811.5 million.

In Mukdahan, local production accounted for 77.1% of total supply, slightly lower than Savannakhet’s 80.7%. Mukdahan’s economy is therefore more dependent on imports than Savannakhet’s, with imports comprising 22.9% of its total supply, against 19.3% in the case of Savannakhet’s. Both economies are also highly dependent on imports from the ROW, while Savannakhet is relatively slightly more dependent on Mukdahan for its supply requirements.

Compared to Savannakhet, local (domestic) demand accounted for a lower proportion of total demand in Mukdahan. One significant finding is the higher share of investment in total demand in Savannakhet (15.0%) than in Mukdahan (10.4%). As can be observed below, this could be due to the higher concentration of manufacturing industries in the economy of Savannakhet.

2. Output Structure

Both provinces appear to have different patterns of production. Table 2 shows that in 2003, a large share of economic activities in Mukdahan was concentrated in the services sector (47% of its total output), versus only 20.8% in Savannakhet. On the other hand, the industry sector in Savannakhet contributed proportionally more to output than its counterpart in Mukdahan. Specifically, the manufacturing industry in Savannakhet had a share of 34.0% in Savannakhet’s output, which was much higher than the corresponding share of 23.9% in Mukdahan. The agriculture and forestry sector in Mukdahan contributed 17.4% to total output, which was much lower than the corresponding share of 26.6% in Savannakhet.



Table 1. Supply and Demand, 200�

item

Mukdahan Savannakhet total

US$M Percent US$M Percent US$M Percent

i. total Supply �01.� 100.0 �11.� 100.0 1,�1�.� 100.0

A. Production ��.2 77.1 ��.7 �0.7 1,11�.� 7�.2

B. imports 1�7.� 22.� 1��.� 1�.� 2��.� 20.�

1) Interregional Inflows 2.1 0.3 6.8 0.8 8.8 0.6

2) ROW 135.7 22.5 150.0 18.5 285.7 20.2

ii. total Demand �01.� 100.0 �11.� 100.0 1,�1�.� 100.0

A. Domestic (local) Demand �0�.1 ��.� 7�2.� �0.� 1,2��.� �7.�

1) Intermediate 232.0 38.5 315.9 38.9 547.9 38.8

2) Final 272.2 45.2 416.6 51.3 688.8 48.7

2.1) Consumption 209.5 34.8 295.3 36.4 504.8 35.7

2.2) Investment 62.6 10.4 121.3 15.0 184.0 13.0

B. Exports �7.� 1�.2 7�.0 �.7 17�.� 12.�

1) Interregional Outflows 6.8 1.1 2.1 0.3 8.8 0.6

2) ROW 91.1 15.1 76.9 9.5 167.9 11.9ROW means rest of world.Note: Figures may not add up to totals due to rounding.Source: Authors’ calculations.

Table 2. Output Structure, 200�

Sector



All Sectors ��.2 100.0 ��.7 100.0 1,11�.� 100.0

i Agriculture and Forestry �1.0 17.� 17�.� 2�.� 2��.� 22.�

1 Agriculture and forestry 81.0 17.4 173.9 26.6 254.9 22.8

ii industry 1��.� ��.� ��.� �2.� �0�.� ��.�

2 Mining and quarrying 4.2 0.9 32.6 5.0 36.8 3.3

� Manufacturing 110.8 23.9 222.7 34.0 333.4 29.8

� Electricity and water supply 6.7 1.4 4.8 0.7 11.5 1.0

� Construction 43.2 9.3 84.5 12.9 127.7 11.4

iii Services 21�.� �7.0 1��.2 20.� ��.� �1.7

� Transportation and communications 21.1 4.5 1.3 0.2 22.4 2.0

7 Wholesale and retail trade 48.5 10.4 51.8 7.9 100.3 9.0

� Finance, real estate, and business services 27.4 5.9 15.7 2.4 43.1 3.9

� Public administration 32.1 6.9 12.6 1.9 44.7 4.0

10 Personal, social, and community services 89.3 19.2 54.8 8.4 144.0 12.9Note: Figures may not add up to totals due to rounding.Source: Authors’ calculations.

July 2007 17


3. Input Structure

At the aggregate level, the input or production cost structure in both provinces appears to be rather similar. In Mukdahan, 50.0% of every dollar of production cost in 2003 went to the purchase of intermediate inputs, with the remainder going to primary input payments or value-added to the economy. In Savannakhet, the share of intermediate inputs in production was slightly lower (48.3%), while the value-added share was higher than Mukdahan’s (Table 3).

However, some differences can be observed in the cost structure of the various sectors. Proportionally, the manufacturing, electricity and water supply, and construction industries in the industry sector in Mukdahan tend to make more use of intermediate inputs than their counterparts in Savannakhet, so that the GVA ratios for the latter were higher. This suggests that the industry sector in Savannakhet may be a more efficient user of intermediate inputs than its counterpart in Mukdahan. A similar result is observed in the case of the agricultural and forestry sector and the transportation and communications; finance, real estate, and business services; and public administration industries.

4. Sources of Intermediate Inputs

The IRIO table makes it possible to determine the origin of intermediate inputs consumed in production. The results, as shown in Table 4, can be regarded as direct measures of import dependency in production.

As can be observed from Table 4, production activities in both provinces appear to be quite dependent on imports from the ROW. Imports from the ROW accounted for approximately 40% and 32% of intermediate inputs in Mukdahan and Savannakhet, respectively, in 2003. Both provinces also tend to rely very heavily on locally produced products to satisfy their intermediate input requirements. In sharp contrast, the dependence of each province on the products of the other province for intermediate inputs is observed to be very minimal.

An assessment of the various industries shows that the manufacturing industries in both provinces tend to source a rather high proportion of their intermediate inputs locally. In contrast, the transportation and communications industries in both provinces are found to be highly import-dependent. This could be because most of the fuel requirements of the transportation industries in the two provinces are imported from the ROW.



Table 3. input Structure, 200� (expressed as ratios to gross outputs, in percent)

SectorMukdahan Savannakhet

tii tPi = GVA tii tPi = GVA

All Sectors �0.0 �0.0 ��.� �1.7

i Agriculture and Forestry ��.� ��.7 2�.� 70.�

1 Agriculture and forestry 36.3 63.7 29.5 70.5

ii industry 71.� 2�.� �2.1 �7.�

2 Mining and quarrying 29.9 70.1 56.0 44.0

� Manufacturing 75.3 24.7 67.4 32.6

� Electricity and water supply 49.1 50.9 39.9 60.1

� Construction 68.9 31.1 51.9 48.1

iii Services ��.� �1.1 �7.1 �2.�

� Transportation and communications 50.3 49.7 36.6 63.4

7 Wholesale and retail trade 16.9 83.1 26.5 73.5

� Finance, real estate, and business services 38.5 61.5 11.2 88.8

� Public administration 40.5 59.5 34.1 65.9

10 Personal, social, and community services 47.7 52.3 55.4 44.6TII means total intermediate inputs; TPI means total primary inputs; GVA means gross value-added.Source: Authors’ calculations.

Table 4. intermediate input Consumption by Source, 200�(expressed as ratios to total intermediate inputs, in percent)

Sector

Mukdahan SavannakhetSource of intermediate inputs Source of intermediate inputs

MKD SVK ROW MKD SVK ROWAll Sectors ��.� 0.7 ��.� 0.� �7.� �1.�

i Agriculture and Forestry �2.� 0.� �7.0 0.� 7�.� 2�.�1 Agriculture and forestry 52.8 0.3 47.0 0.9 75.3 23.8ii industry ��.� 0.� �0.1 0.� 7�.2 2�.�2 Mining and quarrying 40.0 0.1 59.9 0.4 18.8 80.8� Manufacturing 72.4 0.6 27.0 0.4 90.4 9.2� Electricity and water supply 41.5 0.1 58.4 0.4 69.8 29.8� Construction 25.5 0.7 73.8 2.6 37.3 60.1iii Services �2.1 1.1 ��.� 0.� ��.1 ��.�� Transportation and communications 34.3 0.3 65.4 0.5 39.3 60.27 Wholesale and retail trade 61.3 1.0 37.7 0.6 32.0 67.3� Finance, real estate, and business services 68.1 2.9 29.0 0.8 77.2 22.0� Public administration 82.9 1.1 16.0 0.6 60.5 38.910 Personal, social, and community services 61.3 0.9 37.8 0.5 32.0 67.5

MKD means Mukdahan; SVK means Savannakhet; ROW means rest of world.Source: Authors’ calculations.

5. Gross Provincial Product

Table 5 presents the estimates of GPP and its breakdown for both provinces for 2003.14 It can be �� GPPisthesumofGVAfromproduction,customsduties,and

importtaxes.

observed that, in absolute terms, Savannakhet’s GPP was 1.4 times larger than Mukdahan’s. However, as Savannakhet’s 2003 population (803,000) was 2.3 times higher than Mukdahan’s (348,000), this means that the per capita GPP of the latter (US$668) was higher than that of the former (US$415).

July 2007 1�


Table 5. Estimates of Gross Provincial Product, 200�

GPP Component



CE Compensation of employees 78.5 32.0 117.5 33.5 196.1 32.9

Pt-S Production taxes less subsidies 7.8 3.2 12.5 3.6 20.3 3.4

GOS Gross operating surplus 145.9 59.5 208.6 59.5 354.5 59.5

Dt Duties and import taxes 12.9 5.3 12.0 3.4 24.9 4.2

Gross Provincial Product 2��.1 100.0 ��0.7 100.0 ��.� 100.0GPP means gross provincial product.Note: Figures may not add up to totals due to rounding.Source: Authors’ calculations.

In both Mukdahan and Savannakhet, gross operating surplus contributed the largest share (approximately 60%) to GPP, with the share of labor payments in both provinces at around one third.

A sectoral breakdown of the GVA of both provinces (Table 5a) reveals that in 2003, the top three contributors to GVA in Mukdahan were agriculture and forestry (22.2%); personal, social, and community services (20.1%); and wholesale and retail trade (17.4%). In Savannakhet, the top three contributors to GPP were agriculture and forestry

(36.2%), manufacturing (21.5), and construction (12.0%).

On the whole, it can be observed from Table 5a that GVA in Savannakhet is quite evenly distributed across the agricultural and forestry, industry, and services sectors, while GVA in Mukdahan is heavily concentrated in the services sector. This difference in the composition of GVA of the two provinces could be due to the fact that both provinces are at different stages of economic development.

Table 5a. Composition of GVA by Sector, 200�

Sector



All Sectors 2�2.2 100.0 ��.7 100.0 �71.0 100.0

i Agriculture and Forestry �1.� 22.2 122.� ��.2 17�.1 �0.�

1 Agriculture and forestry 51.6 22.2 122.5 36.2 174.1 30.5

ii industry �7.2 20.� 1�0.� ��.� 177.7 �1.1

2 Mining and quarrying 2.9 1.3 14.3 4.2 17.3 3.0

� Manufacturing 27.4 11.8 72.7 21.5 100.1 17.5

� Electricity and water supply 3.4 1.5 2.9 0.8 6.3 1.1

� Construction 13.4 5.8 40.7 12.0 54.1 9.5

iii Services 1��.� �7.� ��.7 2�.� 21�.1 ��.�

� Transportation and communications 10.5 4.5 0.8 0.2 11.3 2.0

7 Wholesale and retail trade 40.3 17.4 38.1 11.3 78.4 13.7

� Finance, real estate, and business services 16.9 7.3 14.0 4.1 30.8 5.4

� Public administration 19.1 8.2 8.3 2.5 27.4 4.8

10 Personal, social, and community services 46.7 20.1 24.4 7.2 71.2 12.5Note: Figures may not add up to totals due to rounding.Source: Authors’ calculations.



6. Structure of Demand

Table 6 shows the distribution of the total supply of goods and services for intermediate and final use in both provinces in 2003. It can be observed that at the aggregate level, both areas have a similar structure of demand. In 2003, approximately 39% of the total supply of goods and services in both provinces was consumed by the production sectors, while the remaining 61% was absorbed by final local demand and external demand.

However, fairly significant differences can be observed in the structure of demand of the various sectors. For instance, slightly over half of Mukdahan’s supply of agriculture and forestry products was consumed by intermediate demand in 2003. In contrast, a hefty 72.6% of Savannakhet’s

supply of agriculture and forestry products was absorbed by the intermediate sectors. This could be attributed to the fact that in Savannakhet, a large proportion of the supply of agriculture and forestry products, notably paddy, livestock, and poultry, was used as intermediate inputs by the food manufacturing sector, while in Mukdahan, a large share of its supply of agricultural crops was exported to the ROW.

Further, nearly all the supply of the construction industry and all the supply of public administration were absorbed by final demand. This is because in national and IO accounting, the output of the construction industry, save for expenditure on minor repairs and maintenance, is capitalized and thus, counted in gross fixed capital formation, while the output of public administration is treated as final consumption demand.

Table 6. Structure of Demand by Usage and by Sector, 200�(expressed as percentage share of total supply)

Sector

Mukdahan Savannakhetintermediate

(percent)Final

(percent)total Supply

(US$M)intermediate

(percent)Final

(percent)total Supply

(US$M)

All Sectors ��.� �1.� �01.� ��.� �1.1 �11.�i Agriculture and Forestry �2.� �7.� ��.1 72.� 27.� 17�.11 Agriculture and forestry 52.5 47.5 94.1 72.6 27.4 176.1ii industry �1.� ��.� 27�.1 2�.� 71.� �77.72 Mining and quarrying 62.8 37.2 6.2 0.9 99.1 32.9� Manufacturing 48.1 51.9 210.9 35.8 64.2 345.1� Electricity and water supply 59.1 40.9 15.8 69.6 30.4 15.2� Construction 0.9 99.1 43.2 2.5 97.5 84.5iii Services 2�.1 70.� 2�1.7 �2.� �7.2 1�7.7� Transportation and communications 47.8 52.2 31.3 33.6 66.4 22.67 Wholesale and retail trade 41.3 58.7 48.5 51.1 48.9 51.8� Finance, real estate, and business services 39.8 60.2 30.5 41.9 58.1 15.7� Public administration 0.0 100.0 32.1 0.0 100.0 12.610 Personal, social, and community services 22.8 77.2 89.3 20.0 80.0 54.9

Note: Figures may not add up to totals due to rounding.Source: Authors’ calculations.

July 2007 21


7. Structure of Final Demand

Table 6a compares the structure of final demand by expenditure component and by sector for the year 2003. Savannakhet had a higher investment rate (24.5%) than Mukdahan (16.9%) in 2003. This could be due to the more significant role played by the manufacturing industries in the economy of the former. In contrast, Mukdahan appears to be more

export-oriented than Savannakhet. Exports took up 26.4% of the final demand of Mukdahan, versus 15.9% in the case of Savannakhet.

Table 6b presents the distribution of the components of final local demand by origin for 2003. In both areas, the bulk of final consumption demand was sourced locally. Interregional flows of goods for final use were not as significant as imports from the ROW.

Table 6a. Structure of Final Demand by Expenditure Component and by Sector, 200�(expressed as percentage share of total final demand )

Sector

Mukdahan Savannakhet

C i E tFD C i E tFD

(percent) (percent) (percent) (US$M) (percent) (percent) (percent) (US$M)All Sectors ��.� 1�.� 2�.� �70.0 ��.� 2�.� 1�.� ��.�

i Agriculture and Forestry �1.� �.� �2.� ��.7 �7.� 27.� ��.7 ��.21 Agriculture and forestry 41.5 5.6 52.9 44.7 37.4 27.9 34.7 48.2ii industry ��.� ��.7 17.� 1�1.1 ��.� �0.1 1�.1 ��1.�2 Mining and quarrying 0.0 0.0 100.0 2.3 0.0 5.6 94.4 32.6� Manufacturing 60.8 15.1 24.1 109.5 82.0 8.6 9.4 221.7� Electricity and water supply 100.0 0.0 0.0 6.5 100.0 0.0 0.0 4.6� Construction 0.3 99.4 0.3 42.8 0.6 99.4 0.0 82.4iii Services 71.� 0.� 27.� 1��.2 ��.1 �.� 10.0 10�.0� Transportation and communications 55.1 0.9 44.0 16.4 81.5 12.5 6.0 15.07 Wholesale and retail trade 75.6 3.2 21.2 28.5 63.9 12.8 23.2 25.3� Finance, real estate, and business services 100.0 0.0 0.0 18.4 100.0 0.0 0.0 9.1� Public administration 100.0 0.0 0.0 32.1 100.0 0.0 0.0 12.610 Personal, social, and community services 53.5 0.0 46.5 68.9 91.2 0.0 8.8 43.9

TFD means total final demand; C means final consumption demand, which is the sum of private and government consumption expenditures; I means investment demand, which is the sum of gross fixed capital formation and change in inventories; E means exports to all destinations.Note: 0.0 denotes value is less than half of unit employed. Figures may not add up to totals due to rounding.Source: Authors’ calculations.

Table 6b. Distribution of Final local Demand by Component and by Origin, 200�(percent)

to Mukdahan Savannakhet

From C i total C i total

Mukdahan 82.2 89.5 83.9 85.0 91.5 86.9

Savannakhet 0.2 0.0 0.1 1.4 0.1 1.0

ROW 17.6 10.4 16.0 13.6 8.5 12.1

total 100.0 100.0 100.0 100.0 100.0 100.0

total (US$M) 20�.� �2.� 272.2 2��.� 121.� �1�.�ROW means rest of world; C means final consumption demand, which is the sum of private and government consumption expenditures; I means investment demand, which is the sum of gross fixed capital formation and change in inventories.Note: 0.0 denotes value is less than half of unit employed. Figures may not add up to totals due to rounding.Source: Authors’ calculations.



hand, a sector with SSR < 1 suggests that imports are needed to meet that sector’s total domestic demand.

Table 7 presents the regional self-sufficiency rates by sector for 2003. It can be observed that, on the whole, both provinces were quite dependent on imports to satisfy the needs of domestic demand as their overall SSRs were below unity. Four out of the 10 major industries in Mukdahan and three in Savannakhet were found to be less than self-sufficient. In contrast, the mining and quarrying industry in Savannakhet was found to have a very high SSR of 15.287. This could be because of the extraordinarily high demand from the ROW for its main output of gold ingots for reprocessing and refining. The table also shows that the transportation and communications industry in Savannakhet had a very low SSR in 2003. This could be due to its heavy dependence on external sources for its supply of transportation services.

Table 7. Self-Sufficiency Rates, 200�

SectorSelf-Sufficiency Rates


All Sectors 0.�21 0.��

i Agriculture and Forestry 1.1�� 1.0�1

1 Agriculture and forestry 1.149 1.091

ii industry 0.��7 0.�0�

2 Mining and quarrying 1.075 15.287

� Manufacturing 0.600 0.687

� Electricity and water supply 0.423 0.314

� Construction 1.003 1.000

iii Services 1.172 0.�27

� Transportation and communications 0.875 0.061

7 Wholesale and retail trade 1.142 1.128

� Finance, real estate, and business services 0.898 1.000

� Public administration 1.000 1.000

10 Personal, social, and community services 1.561 1.073Source: Authors’ calculations.

8. Self-SufficiencyRates

The self-sufficiency rate is defined as the ratio of total production to total local demand, so that in each region, we have

SSRx

TLDiR i

R

iR

= (46)

where SSR i

R is the self-sufficiency rate of product i in region R;

x iR is the gross output of product i in region R; and

TLDiR

is the total local demand for product i in region

R, R = Mukdahan, Savannakhet.

A sector with SSR ≥ 1 means that its output is sufficient to sustain its local demand. On the other

July 2007 2�


B. Interregional Analysis and Applications

This section analyses the economic relationship between the two provinces in terms of interregional trade. The findings of applications such as multiplier, linkage and impact analyses, in addition to spillover and feedback effects are also presented and analyzed.

1. Interregional Trade

A salient feature of the IRIO table is interregional trade. In our study, interregional outflows/inflows of products are explicitly recorded as separate submatrices. Thus, our IRIO table can be used to determine the extent of Mukdahan’s dependence on Savannakhet’s products and vice versa. Moreover, the Leontief inverse can be exploited to measure the spillover and feedback effects of interregional trade on the two economies.

Table 8 summarizes, in matrix format, the origin-destination of trade outflows (or exports) and inflows (or imports) of products for 2003. The row entries describe a region’s outflows of its outputs to its partner region and the exogenous region (ROW), while the column entries record a region’s inflows from its partner region and the ROW.

As can be observed from Table 8, total interregional and foreign trade of the two provinces amounted to US$462.5 million in 2003. The bulk of

the transactions (US$453.6 million) was conducted with the ROW. Mukdahan’s exports to the ROW amounted to US$91.1 million, with services contributing nearly half the amount (Table 8a). As its imports from the ROW totaled US$135.7 million, it had a negative trade balance of US$44.6 million with this region. Similarly, Savannakhet had a negative trade balance of US$73.1 million with the ROW since its imports of US$150.0 million from this region were higher than the corresponding exports of US$76.9 million. Unlike Mukdahan, however, the mining and quarrying industry was the top foreign export earner for Savannakhet in 2003 (Table 8a). As explained above, this could be due to the demand from the ROW for its gold ingots.

Total interregional trade is observed to be very minimal at a little less than US$9 million. Mukdahan’s exports to Savannakhet amounted to US$6.8 million, while Savannakhet exported a mere US$2.1 million to its partner province, Mukdahan. As can be observed from Table 8a, manufacturing products accounted for the bulk of interregional trade transactions. The above results suggest that the proximity of the two provinces to each other may not have resulted in a high level of interregional trade between them. This could be because the demand requirements of each province can be satisfied more effectively by the ROW (which includes the other provinces in the neighboring country) than its adjacent province.



Table 8. Origin–Destination Matrix of trade Flows, 200�

Destination

Origin

Mukdahan Savannakhet ROW total

US$M

Percent to total

inflows US$M

Percent to total

inflows US$M

Percent to total

inflows US$M

Percent to total

inflows

Mukdahan 6.8 4.3 91.1 54.2 97.8 21.2

Savannakhet 2.1 1.5 76.9 45.8 79.0 17.0

ROW 135.7 98.5 150.0 95.7 285.7 61.8

total 1�7.� 100.0 1��.� 100.0 1�7.� 100.0 ��2.� 100.0ROW means rest of world.Note: Figures may not add up to totals due to rounding. Source: Authors’ calculations.

Table 8a. interregional trade by Product Group and by type of Demand, 200�(US$ million)

Destination Mukdahan Savannakhet ROW

total Outflows

Origin/Product Group iD FDD iD FDD Value Percent

MKD

Agriculture and forestry 0.0 0.0 23.6 23.6 24.2

Mining and quarrying 0.0 0.0 2.3 2.3 2.4Manufacturing 2.3 3.8 20.3 26.4 27.0

Services 0.2 0.4 44.8 45.4 46.5

Subtotal 2.� �.2 �1.1 �7.� 100.0

SVK

Agriculture and forestry 0.2 0.1 16.4 16.7 21.2

Mining and quarrying 0.0 0.0 30.7 30.7 38.9Manufacturing 1.4 0.2 19.2 20.8 26.4

Services 0.1 0.0 10.5 10.6 13.5

Subtotal 1.7 0.� 7�.� 7�.0 100.0

ROW

Agriculture and forestry 9.9 2.9 1.5 0.8 15.0 5.3

Mining and quarrying 2.0 0.0 0.0 0.3 2.3 0.8Manufacturing 65.7 32.8 83.8 32.5 214.8 75.2

Services 14.6 7.7 14.5 16.8 53.6 18.8

Subtotal �2.2 ��.� ��.7 �0.� 2��.7 100.0

total inflows ��.� ��.� 102.� ��.� 1�7.� ��2.�ID means intermediate demand; FDD means final domestic demand; MKD means Mukdahan; SVK means Savannakhet; ROW means rest of world. Note: 0.0 denotes value is less than half of unit employed. Figures may not add up to totals due to rounding. Source: Authors’ calculations.

July 2007 2�


2. Multiplier Analysis

A very useful analytical application of IO tables is IO multipliers. A multiplier is a ratio that quantifies the effect on the whole economy arising from the initial effect of an exogenous change in any of the final demand components. It is the amount by which the initial effect is magnified (or multiplied) to become a total effect. The relationship between the first-order change and the total effect on the economy generated by the change is known as the multiplier effect.

Depending on the purpose of the analysis, different kinds of multipliers can be computed. The most common kinds include the output, value-added (VA), employment, import, and income multipliers. For ease of comparison, multipliers are typically expressed in terms of a unit of exogenous change in final demand.

Multipliers can be generated using the open and closed IO models. Multipliers generated in the open model measure the direct and indirect effects arising from a change in final demand and are known as simple multipliers. Multipliers generated in the closed

model (where households are treated as endogenous) measure not only the direct and indirect effects, but also the induced effect due to the spending of households, as a result of a change in final demand, and are known as total multipliers. Our analysis will focus on simple multipliers as our IRIO table belongs to the open variety.

Table 9 presents the various simple multipliers for the 10 major industries in both provinces for 2003. At the overall economy level, Savannakhet had higher average output, VA, income, and employment multipliers than Mukdahan. This suggests that a change in final demand for the output of an average industry would have a greater impact on these key macroeconomic indicators in Savannakhet than in Mukdahan. In 2003, the manufacturing industries in both provinces had the highest output multipliers among all the major industries. The values of their output multipliers were higher than the corresponding provincial averages. This implies that the manufacturing industries in both provinces had a greater impact on the output of their respective economies than the typical or average industry.

Table 9. Simple Multipliers by industry: Mukdahan and Savannakhet, 200�(per US$ million change in final demand)

industry

Output (US$M)Value-added

(US$M) import (US$M) income (US$M)Employment

('000 persons)

MKD SVK MKD SVK MKD SVK MKD SVK MKD SVK

1 Agriculture and forestry 1.261 1.350 0.803 0.951 0.215 0.095 0.235 0.324 2.342 2.110

2 Mining and quarrying 1.160 1.141 0.813 0.502 0.208 0.517 0.197 0.176 0.005 0.062

� Manufacturing 1.781 1.822 0.440 0.595 0.362 0.113 0.128 0.188 0.059 0.245

� Electricity and water supply 1.252 1.367 0.638 0.822 0.359 0.162 0.222 0.208 0.028 0.035

� Construction 1.221 1.303 0.380 0.627 0.621 0.406 0.125 0.239 0.063 0.307

� Transportation and communications 1.228 1.188 0.611 0.753 0.403 0.262 0.208 0.299 0.104 0.151

7 Wholesale and retail trade 1.139 1.113 0.946 0.818 0.073 0.198 0.327 0.261 0.264 0.425

�Finance, real estate, and business services 1.378 1.103 0.847 0.980 0.154 0.027 0.156 0.136 0.059 0.110

� Public administration 1.487 1.269 0.885 0.836 0.096 0.168 0.811 0.836 0.238 0.426

10 Personal, social, and community services 1.445 1.266 0.757 0.565 0.260 0.473 0.178 0.205 0.183 0.683

All industries (weighted average) 1.�2� 1.�� 0.71� 0.770 0.2�2 0.2�0 0.2�� 0.2�7 0.�7� 0.��0MKD means Mukdahan; SVK means Savannakhet.Source: Authors’ calculations.



whole system. This ratio is described by Rasmussen (1957) as the index of the power of dispersion, µj , and is defined mathematically as

µ j

iji

n

i

n

ijj

n

r

nr

= =

= =

∑

∑ ∑1

1 1

1

(47)where the rij is the element of the Leontief inverse. The higher the value of µj, the stronger is influence of industry j as a user of intermediate inputs.

A forward linkage indicates the relative importance of an industry as a supplier of inputs to the entire production system. It measures the output increases that will occur in industries that use the inputs supplied by the industry concerned. A forward linkage can be expressed as the ratio of the sum of the elements along a row of the Leontief inverse to the average of the entire system. This ratio is described by Rasmussen (1957) as the index of sensitivity, µi, and is defined mathematically as

µi

ijj

n

i

n

ijj

n

r

nr

= =

= =

∑

∑ ∑1

1 1

1

(48)The higher the value of µi, the greater is the

influence of industry i as a supplier of intermediate inputs to the entire production system.

The estimated linkages for the industries in this study are presented in Table 10. As can be seen, the estimated values of the backward and forward linkages in both provinces appear to be quite low. Only four industries in Mukdahan and three industries in Savannakhet had values for backward linkages greater than one in 2003. In the case of forward linkages, five industries in Mukdahan and four in Savannakhet had values higher than one. One likely reason for these rather low values could be the high reliance of both provinces on the outside world for their supply requirements.

In both provinces, industries in the services sector generally had higher VA multipliers than industries in the manufacturing sector. This could be due to the higher dependence of the services sector on the domestic industries, rather than imports, for their input requirements. Consequently, more VA was generated in the economies of both provinces by the consumption of the output of the services industries than that of the manufacturing sector. The relatively low import requirements of the services industries can be inferred from the values of their import multipliers, which were generally lower than those of the manufacturing sector.

The income and employment multipliers for the agriculture and fishery, wholesale and retail trade, and public administration industries in both provinces were generally higher than those of most other industries. This can be attributed to the highly labor-intensive nature of these industries. Interestingly, the electricity and water supply industries in both provinces had one of the lowest employment multipliers but fairly high income multipliers among all the industries. This suggests that any increase in final demand for the output of these industries would have a proportionally greater effect on income than employment and, hence, result in a relatively high increase in average earnings.

3. Backward and Forward Linkages

Linkages reflect the dependence of industries on one another in an economy and measure the potential stimulus that will be induced in other industries arising from an increase in activity in a particular industry. In essence, there are two types of linkages, namely, backward linkages and forward linkages.

A backward linkage is a measure of the relative importance of an industry as a user of inputs from the entire production system. It measures the output increases that will occur in industries that supply inputs to the industry concerned. A backward linkage can be computed as the ratio of the sum of the elements of a column of the Leontief inverse to the average of the

July 2007 27


Table 10. interregional total Backward–Forward linkages, 200�

industry

Mukdahan SavannakhettBl

indextFl

indextBl

indextFl

index



� Manufacturing 1.356 1.223 1.387 1.221


� Construction 0.930 0.773 0.992 0.813





10 Personal, social, and community services 1.100 1.239 0.963 1.036TBL means total backward linkage; TFL means total forward linkage. Source: Authors’ calculations.

It is possible to split the industries in question according to their calculated degrees of interdependencies. Industries with linkages greater than or equal to unity are defined as industries with high interdependencies, while those with linkages below unity are considered as industries with low interdependencies. Based on these definitions, Chenery and Clark (1959) classified industries into the following four groups:

GROUP I: HIGH µj, HIGH µi GROUP II: HIGH µj, LOW µiGROUP III: LOW µj, HIGH µi GROUP IV: LOW µj, LOW µi

Industries belonging to Groups I and II are those whose production processes are characterized by relatively high usage of intermediate inputs. An expansion in these industries would have a considerable impact on the whole economic system. This is particularly so for industries in Group I since, in addition to having high values of µj, they are also characterized by large values of µi, which means that a major portion of their outputs is also absorbed by the system.

Industries classified under Groups III and IV are both characterized by low values of µj as they tend to maintain a cost structure that is biased toward the

use of primary inputs rather than intermediate inputs. In addition, industries that belong to Group IV do not depend extensively on the system of productive sectors for their intermediate input requirements, while their products are not utilized much by other industries as they are mainly channeled directly to final consumption.

The classification of industries in this manner is particularly useful to economic planners and policymakers in the assessment and setting of industrial priorities in regional development. For example, industries under Group I could be considered the top priority industries in development policy due to their high linkages with the productive system as users and providers of inputs.

Grouping the industries in this study according to the classification scheme of Chenery and Clark (1959) reveals that many industries in both provinces belong to Group IV (Table 10a). On the other hand, only two industries in Savannakhet and three industries in Mukdahan are classified in Group I. In particular, the agriculture and forestry industry in Savannakhet as well as the manufacturing industries in both provinces are classified under this group. This suggests that on the basis of the estimated linkage results, these industries can be given higher priority in the development of policies to enhance the economies of both provinces.



Table 10a. Grouping of industries Based on their Degrees of interdependencies, 200�

Forward linkage

High low

Backward linkage

High

GROUP i GROUP ii

S01 Agriculture and forestry S04 Electricity and water supply

D03 Manufacturing D09 Public administration

S03 Manufacturing

D08 Finance, real estate, and business services

D10 Personal, social, and community services

low

GROUP iii GROUP iV

D01 Agriculture and forestry D02 Mining and quarrying

D07 Wholesale and retail trade S02 Mining and quarrying

S07 Wholesale and retail trade D04 Electricity and water supply

S10 Personal, social, and community services D05 Construction

S05 Construction

D06 Transportation and communications

S06 Transportation and communications

S08 Finance, real estate, and business services

S09 Public administration Source: Authors’ calculations.

4. Spillover and Feedback Effects

A single-region IO table essentially assumes that imports from suppliers and exports to buyers outside the economy are treated as exogenous. However, such a table will not allow us to capture the interregional economic spillover and feedback effects in an economic system. These effects can be illustrated as follows. Suppose there is an increase in demand by the ROW for the products of the manufacturing industry in Mukdahan. This will result in an increase in the output of the manufacturing industry in the Thai province, which could result in an increase in demand for relevant inputs from suppliers outside the province, say, Savannakhet. This new demand for the output of the suppliers in Savannakhet will create an increase in their output and, directly and indirectly, the output of other industries in the Lao PDR province. This stimulus of new output in Savannakhet due to new output in Mukdahan is known as the interregional spillover effect. In addition, suppose that the stimulated production in Savannakhet includes increased output of industries that use inputs from Mukdahan in their production process. Thus, the increased manufacturing production in Mukdahan leads to increased output of

its suppliers in Savannakhet, which, in turn, leads to more production in Mukdahan. This is known as the interregional feedback effect. These interregional effects can be measured within the context of an IRIO table.

This subsection quantifies the spillover and feedback effects due to interregional trade in products to sustain regional final demand.

Table 11 shows that, because of weak interregional linkages among and between sectors, the estimated spillover and feedback effects appear to be insignificant.15 The average spillover effect in Savannakhet due to its trade transactions with Mukdahan is estimated to be a low US$5 for every US$1,000 increase in final demand, while the estimated spillover effect for Mukdahan is a little higher at US$6 per US$1,000 increase in final demand. Feedback effects in both regions are also found to be very negligible. The results suggest that both provinces rely heavily on the ROW for products used in production.

�5 Thesespilloverandfeedbackeffectswerecomputedfromthematrices %SDS and�SSD ,and %FD and %FS inequation(�8).

July 2007 2�


Table 11. interregional Spillover and Feedback Effects, 200�(per US$1 change in final demand)

industry


Spillover Feedback Spillover Feedback



� Manufacturing 0.00703 0.00003 0.00455 0.00003


� Construction 0.00827 0.00004 0.02381 0.00014





10 Personal, social, and community services 0.00754 0.00003 0.00466 0.00002 total 0.0��2 0.0002� 0.0�2�� 0.0002� Average 0.00�� 0.0000� 0.00�2� 0.0000�

Note: 0.00000 denotes value is less than half of unit employed.Source: Authors’ calculations.

C. Impact Analysis

Different components of final demand will almost inevitably have different effects on output, GVA, employment, and import requirements. This section quantifies the impact of the different components of final demand on these macroeconomic indicators.

1. Impact on Regional Production

Table 12 summarizes the impact of final demand on production for the 10 major industries for 2003. The row entries in the table describe how sectoral output is induced by each type of final demand in both regions. Conversely, the column entries in the table record the breakdown of sectoral output required from both regions to satisfy the needs of each type of final demand in one region. The column sums can be interpreted to be the total output induced by each type of final demand in each region.

It can be observed from Table 12 that, in both regions, the bulk of output requirements was induced by final consumption. In 2003, final consumption in

Mukdahan and Savannakhet accounted for 22.5% and 36.5% of the combined production of US$1,119 million in both provinces, respectively. As a result, consumption in both provinces had the largest simple output multipliers among all the final demand components.16 On the other hand, investment demand in Mukdahan accounted for a mere 6.6% of combined production, versus 13.4% in Savannakhet. In addition, ROW export demand in Mukdahan registered a 11.6% share of induced output, compared to Savannakhet’s 9.3%.

�6 To illustrate, every US$� increase in consumption inMukdahanandSavannakhetwouldgenerateUS$�.�59andUS$�.599worthofoutput,respectively.

�0 Benson Sim, Francisco Secretario, and Eric Suan


Table 12. impact of Final Demand on Output by Sector, 200�

Region / Sector

Mukdahan (US$M) Savannakhet (US$M)

totalC i ESub– total C i E

Sub– total

Mukdahan

i Agriculture and Forestry ��.0 �.� ��.1 7�.� 1.7 0.� 0.1 2.2 �1.0D01 Agriculture and forestry 36.0 6.6 36.1 78.8 1.7 0.4 0.1 2.2 81.0

ii industry ��.7 ��.� ��.� 1�7.2 �.� 1.� 0.� 7.7 1��.�D02 Mining and quarrying 0.6 1.1 2.5 4.2 0.0 0.0 0.0 0.0 4.2D0� Manufacturing 58.5 13.0 31.7 103.2 5.9 1.4 0.3 7.6 110.8D0� Electricity and water supply 5.3 0.2 1.1 6.6 0.1 0.0 0.0 0.1 6.7D0� Construction 0.4 42.6 0.2 43.2 0.0 0.0 0.0 0.0 43.2iii Services 1��.7 10.1 �7.� 21�.� 1.2 0.� 0.1 1.7 21�.�

D0� Transportation and communications 9.8 2.0 8.6 20.4 0.5 0.2 0.0 0.8 21.1D07 Wholesale and retail trade 30.5 5.9 11.5 47.9 0.5 0.1 0.0 0.6 48.5D0� Finance, real estate, and business services 23.2 1.4 2.6 27.2 0.2 0.0 0.0 0.2 27.4D0� Public administration 32.1 0.0 0.0 32.1 0.0 0.0 0.0 0.0 32.1D10 Personal, social, and community services 53.2 0.8 35.1 89.1 0.1 0.0 0.0 0.1 89.3

Subtotal 2��.� 7�.7 12�.� ��2.� �.� 2.� 0.� 11.� ��.2

Savannakhet

i Agriculture and Forestry 0.� 0.2 0.� 1.� 11�.7 2�.� �0.� 172.� 17�.�S01 Agriculture and forestry 0.9 0.2 0.3 1.4 115.7 25.9 30.9 172.5 173.9

ii industry 1.2 0.� 0.� 1.� 1�0.� 10�.� ��.� ��2.7 ��.�S02 Mining and quarrying 0.0 0.0 0.0 0.0 0.0 1.8 30.7 32.6 32.6S0� Manufacturing 1.2 0.3 0.3 1.8 175.0 21.4 24.4 220.9 222.7S0� Electricity and water supply 0.0 0.0 0.0 0.0 3.2 0.4 1.2 4.8 4.8S0� Construction 0.0 0.0 0.0 0.0 2.1 82.2 0.2 84.5 84.5iii Services 0.2 0.1 0.1 0.� 10�.2 1�.0 1�.7 1��.� 1��.2

S0� Transportation and communications 0.1 0.0 0.0 0.1 0.3 0.1 0.8 1.2 1.3S07 Wholesale and retail trade 0.1 0.0 0.0 0.1 31.4 10.4 9.9 51.7 51.8S0� Finance, real estate, and business services 0.0 0.0 0.0 0.0 13.6 1.2 0.9 15.7 15.7S0� Public administration 0.0 0.0 0.0 0.0 12.6 0.0 0.0 12.6 12.6S10 Personal, social, and community services 0.0 0.0 0.0 0.0 45.3 4.3 5.1 54.7 54.8

Subtotal 2.� 0.� 0.7 �.� ��.2 1�7.� 10�.1 ��1.2 ��.7total induced Output (US$M) 2�1.� 7�.2 1�0.1 ��.1 �0�.1 1�0.1 10�.� ��2.� 1,11�.�Percent Distribution 22.� �.� 11.� �0.� ��.� 1�.� �.� ��.2 100.0total Final Demand (US$M) 172.� ��.1 �1.1 �1�.� 2��.2 111.1 7�.� ��.1 7�2.�Simple Output Multiplier (per US$M change) 1.�� 1.�2� 1.�2� 1.�2� 1.�� 1.��1 1.��0 1.�� 1.��7

C means final consumption demand, which is the sum of private and government consumption expenditures; I means investment demand, which is the sum of gross fixed capital formation and change in inventories; E means exports to ROW.Note: 0.0 denotes value is less than half of unit employed. Figures may not add up to totals due to rounding.Source: Authors’ calculations.

July 2007 �1


As well, Savannakhet’s demand for Mukdahan’s products is higher than Mukdahan’s demand for the former’s products. In 2003, Savannakhet needed a total of US$11.6 million worth of Mukdahan’s products to sustain its final demand, while Mukdahan required a total of just US$3.5 million worth of Savannakhet’s products to meet its final demand requirements.

2. Impact on Value-Added

Table 13, which presents the impact of final demand on the various factors of production for 2003, shows that 40.2% of the total GVA generated by the two economies during that year was induced by Mukdahan’s final demand and the remaining 59.8% by Savannakhet’s final demand. Of the total labor income of US$196 million, 39.7% was induced by Mukdahan’s final demand and 60.3% by Savannakhet’s final demand. Production tax payments and gross operating surplus generated in Mukdahan accounted for shares of 38.0% and 40.6% in combined tax payments and gross operating surplus respectively. In Savannakhet, the shares of production tax and gross operating surplus were 62.0% and 59.4%, respectively.

Like the case of output multipliers in the previous subsection, consumption had the highest GVA

multipliers in both provinces. This suggests that an increase in consumption demand will not only stimulate a relatively high level of output, but also GVA in both economies. The relatively high level of GVA generated in both provinces by consumption suggests that such demand might be concentrated in industries with relatively low dependence on imports for production.

Dividing the induced GVA for each of the three factors of production by their column sum results in measures of factor intensity that indicate whether the income induced by the components of final demand is labor-intensive or capital-intensive. As can be seen in Table 13a, consumption-induced income in Mukdahan can be said to be relatively labor-intensive as its ratio of 0.370 is the highest among the three components of final demand. In contrast, in the case of Savannakhet, investment-induced income tends to be relatively labor-intensive. This could be largely due to the higher share of labor-intensive construction activities in Savannakhet than in Mukdahan. Export-induced income in both provinces is relatively capital-intensive. In the case of Savannakhet, besides export-induced income, consumption-induced income also tends to be relatively capital-intensive.

Table 13. impact of Final Demand on GVA by Factor of Production, 200�

Component of GVA


totalC i ESub–total C i E

Sub–total

CE Compensation of employees 49.5 9.1 19.1 77.8 72.4 27.4 18.4 118.3 1��.1Pt-S Production tax less subsidies 4.5 1.4 1.9 7.7 6.2 4.1 2.3 12.6 20.�GOS Gross operating surplus 79.2 18.5 46.3 144.1 130.2 46.0 34.4 210.5 ��.�

total induced GVA (US$M) 1��.2 2�.0 �7.� 22�.� 20�.� 77.� ��.1 ��1.� �71.0total Final Demand (US$M) 172.� ��.1 �1.1 �1�.� 2��.2 111.1 7�.� ��.1 7�2.�Simple GVA Multiplier (per US$M change) 0.772 0.�17 0.7�0 0.71� 0.�1� 0.��7 0.717 0.770 0.7��

Contribution (percent)CE Compensation of employees 25.2 4.7 9.8 39.7 37.0 14.0 9.4 60.3 100.0

Pt-S Production tax less subsidies 22.0 6.7 9.4 38.0 30.6 19.9 11.5 62.0 100.0GOS Gross operating surplus 22.3 5.2 13.1 40.6 36.7 13.0 9.7 59.4 100.0

total induced GVA 2�.� �.1 11.� �0.2 ��.� 1�.� �.� ��.� 100.0C means final consumption demand, which is the sum of private and government consumption expenditures; I means investment demand, which is the sum of gross fixed capital formation and change in inventories; E means exports to ROW; GVA means gross value-added.Note: Gross operating surplus (GOS) includes depreciation. Figures may not add up to totals due to rounding.Source: Authors’ calculations.



Table 13a. Factor intensities induced by Final Demand, 200�

GVA Component


C i ESub–total C i E

Sub–total

CE Compensation of employees 0.370 0.313 0.287 0.�� 0.348 0.353 0.334 0.��7

Pt-S Production tax less subsidies 0.034 0.047 0.028 0.0�� 0.029 0.055 0.043 0.0�7

GOS Gross operating surplus 0.596 0.640 0.685 0.�2� 0.623 0.592 0.624 0.�1�

total induced GVA 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

C means final consumption demand, which is the sum of private and government consumption expenditures; I means investment demand, which is the sum of gross fixed capital formation and change in inventories; E means exports to ROW; GVA means gross value-added.Source: Authors’ calculations.

3. Impact on Employment

from such demand. The results provide possibly more supporting evidence that the two provinces do not appear to depend heavily on each other economically.

ROW exports and consumption had the highest employment multipliers in Mukdahan and Savannakhet, respectively. This could be due to the relatively large share of the output of highly labor-intensive industries such as agriculture and fishery in these final demand components.

Table 14 shows the employment generated in each industry by the various components of final demand in 2003. At the aggregate level, employment in both provinces is heavily influenced by intraregional factors. Of the total induced employment of 187.1 thousand workers in Mukdahan in 2003, a hefty 182.5 thousand resulted from final local demand and ROW export demand for its products. Similarly, 376.4 thousand out of the induced employment of 378.9 thousand workers in Savannakhet was derived

July 2007 ��


Table 14. impact of Final Demand on Employment by Sector, 200�

Region / Sector


totalC i ESub–total C i E

Sub–total

Mukdahan

i Agriculture and Forestry ��.� 12.� �7.1 1��.� �.2 0.� 0.1 �.1 1�0.�D01Agriculture and forestry 66.9 12.3 67.1 146.3 3.2 0.8 0.1 4.1 150.4

ii industry 2.1 2.� 1.1 �.� 0.2 0.0 0.0 0.� �.1D02Mining and quarrying 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

D0�Manufacturing 1.9 0.4 1.1 3.4 0.2 0.0 0.0 0.3 3.7

D0�Electricity and water supply 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.1

D0�Construction 0.0 2.2 0.0 2.2 0.0 0.0 0.0 0.0 2.2

iii Services 20.� 1.7 7.� �0.� 0.2 0.1 0.0 0.2 �0.�D0�Transportation and communications 0.8 0.2 0.7 1.7 0.0 0.0 0.0 0.1 1.8

D07Wholesale and retail trade 7.1 1.4 2.7 11.1 0.1 0.0 0.0 0.1 11.2

D0�Finance, real estate, and business services 1.0 0.1 0.1 1.2 0.0 0.0 0.0 0.0 1.2

D0�Public administration 5.1 0.0 0.0 5.1 0.0 0.0 0.0 0.0 5.1

D10Personal, social & community services 6.7 0.1 4.4 11.3 0.0 0.0 0.0 0.0 11.3

Subtotal ��.7 1�.� 7�.2 1�2.� �.� 0.� 0.2 �.� 1�7.1

Savannakhet

i Agriculture and Forestry 1.� 0.� 0.� 2.1 1�0.� �0.� ��.� 2��.7 271.�S01Agriculture and forestry 1.4 0.3 0.4 2.1 180.8 40.5 48.3 269.7 271.8

ii industry 0.2 0.0 0.0 0.2 2�.2 22.� �.0 �1.� �1.�S02Mining and quarrying 0.0 0.0 0.0 0.0 0.0 0.1 1.7 1.8 1.8

S0�Manufacturing 0.2 0.0 0.0 0.2 23.6 2.9 3.3 29.7 30.0

S0�Electricity and water supply 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.1

S0�Construction 0.0 0.0 0.0 0.0 0.5 19.4 0.1 19.9 19.9

iii Services 0.1 0.0 0.0 0.1 �2.1 �.� �.7 ��.2 ��.�S0�Transportation and communications 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.2

S07Wholesale and retail trade 0.0 0.0 0.0 0.1 12.0 4.0 3.8 19.7 19.8

S0�Finance, real estate, and business services 0.0 0.0 0.0 0.0 1.4 0.1 0.1 1.6 1.6

S0�Public administration 0.0 0.0 0.0 0.0 4.2 0.0 0.0 4.2 4.2

S10Personal, social, and community services 0.0 0.0 0.0 0.0 24.4 2.3 2.7 29.5 29.5

Subtotal 1.� 0.� 0.� 2.� 2�7.0 ��.� �0.1 �7�.� �7�.�total induced Employment ('000 persons) �1.� 17.0 7�.7 1��.0 2�0.� 70.2 �0.2 ��1.0 ��.0Percent Distribution 1�.1 �.0 1�.� �2.7 ��.� 12.� 10.� �7.� 100.0total Final Demand (US$M) 172.� ��.1 �1.1 �1�.� 2��.2 111.1 7�.� ��.1 7�2.�Simple Employment Multiplier ('000 persons; per US$M change) 0.�2� 0.�02 0.��2 0.�7� 0.��2 0.��2 0.7�� 0.��0 0.7�2


�� Benson Sim, Francisco Secretario, and Eric Suan


4. Impact on Import Requirements

Table 15 shows the total imports generated in each industry by the various final demand components in 2003. Imports required by producers in order to sustain final demand in Mukdahan accounted for 47.0% of the combined imports of both provinces, with the remaining 53.0% accounted for by Savannakhet’s economic activities. Investment demand in both

Table 15. impact of Final Demand on imports by Sector, 200�

Region / Sector


totalC i ESub– total C i E

Sub–total

Mukdahan

i Agriculture and Forestry �.1 1.1 �.2 1�.� 0.� 0.1 0.0 0.� 1�.�D01 Agriculture and forestry 6.1 1.1 6.2 13.4 0.3 0.1 0.0 0.4 13.8

ii industry 1�.7 2�.� 7.� ��.� 1.2 0.� 0.1 1.� �7.2D02 Mining and quarrying 0.1 0.2 0.4 0.7 0.0 0.0 0.0 0.0 0.8

D0� Manufacturing 11.9 2.6 6.5 21.0 1.2 0.3 0.1 1.5 22.5

D0� Electricity and water supply 1.5 0.1 0.3 1.9 0.0 0.0 0.0 0.0 1.9

D0� Construction 0.2 21.7 0.1 22.0 0.0 0.0 0.0 0.0 22.0

iii Services 1�.� 1.� 10.2 �0.� 0.2 0.1 0.0 0.� �1.2D0� Transportation and communications 3.2 0.7 2.8 6.7 0.2 0.1 0.0 0.2 6.9

D07 Wholesale and retail trade 1.9 0.4 0.7 3.1 0.0 0.0 0.0 0.0 3.1

D0� Finance, real estate, and business services 2.6 0.2 0.3 3.0 0.0 0.0 0.0 0.0 3.1

D0� Public administration 2.1 0.0 0.0 2.1 0.0 0.0 0.0 0.0 2.1

D10 Personal, social, and community services 9.6 0.1 6.3 16.1 0.0 0.0 0.0 0.0 16.1

Subtotal ��.� 27.0 2�.� ��.� 1.7 0.� 0.1 2.� �2.2

Savannakhet

i Agriculture and Forestry 0.1 0.0 0.0 0.1 �.1 1.� 2.2 12.1 12.2S01 Agriculture and forestry 0.1 0.0 0.0 0.1 8.1 1.8 2.2 12.1 12.2

ii industry 0.1 0.0 0.0 0.1 11.� 27.� 1�.� ��.� ��.�S02 Mining and quarrying 0.0 0.0 0.0 0.0 0.0 0.8 13.9 14.8 14.8

S0� Manufacturing 0.1 0.0 0.0 0.1 10.8 1.3 1.5 13.7 13.8

S0� Electricity and water supply 0.0 0.0 0.0 0.0 0.4 0.1 0.1 0.6 0.6

S0� Construction 0.0 0.0 0.0 0.0 0.7 25.6 0.1 26.3 26.3

iii Services 0.0 0.0 0.0 0.1 2�.� �.� �.� �2.0 �2.0S0� Transportation and communications 0.0 0.0 0.0 0.0 0.1 0.0 0.2 0.3 0.3

S07 Wholesale and retail trade 0.0 0.0 0.0 0.0 5.6 1.9 1.8 9.2 9.2

S0� Finance, real estate, and business services 0.0 0.0 0.0 0.0 0.3 0.0 0.0 0.4 0.4

S0� Public administration 0.0 0.0 0.0 0.0 1.7 0.0 0.0 1.7 1.7

S10 Personal, social, and community services 0.0 0.0 0.0 0.0 16.9 1.6 1.9 20.4 20.5

Subtotal 0.2 0.0 0.1 0.� ��.� ��.1 21.7 ��.� ��.7total induced imports (US$M) ��.� 27.1 2�.7 �0.2 ��.� ��.� 21.� 101.7 1�2.0Percent Distribution 20.� 1�.1 12.� �7.0 2�.2 17.� 11.� ��.0 100.0total Final Demand (US$M) 172.� ��.1 �1.1 �1�.� 2��.2 111.1 7�.� ��.1 7�2.�Simple import Multiplier (per US$M change)

0.22� 0.�� 0.2�0 0.2�2 0.1�2 0.�0� 0.2�� 0.2�0 0.2�2


regions had the highest import multiplier effects. This could be because capital goods tend to be heavily dependent on imported materials. Conversely, consumption in both provinces had the smallest import multiplier effects. This finding provides some support to the earlier result that the high GVA multipliers for consumption in both provinces could be due to their relatively low reliance on imports.

July 2007 ��


The import multipliers for ROW exports in Mukdahan and Savannakhet were computed to be 0.260 and 0.283, respectively. These results can be used to compute the net foreign exchange earnings of each province as follows.17 The import multiplier of 0.260 for Mukdahan means that in order to produce and export US$1,000 worth of goods, it would need to import US$260 worth of intermediate inputs. As a result, net foreign exchange earnings amounting to US$740 per US$1,000 worth of exports would be generated. Likewise, the import multiplier of 0.283 for Savannakhet means that it would need to import US$283 worth of imports to support US$1,000 worth of exports, so that net foreign exchange earnings of US$717 per US$1,000 of exports, which is lower than Mukdahan’s, would be generated.

vI. dataISSueS

The reliability and quality of our results are heavily influenced by the accuracy and precision of the underlying data as well as methods used in our study. This section describes some key issues with the quality of the underlying data and methodology used in our study.

Due mainly to the lack of budgetary resources, no surveys were conducted to obtain the data required to develop an intraregional Mukdahan IO table. Instead, the various regional technical coefficients were estimated by mainly regionalizing the IO coefficients found in the Thailand IO table under the assumption that the technology of production in Mukdahan is the same as that in the national economy. However, it is very likely that firms within a given national industry will tend to produce a much wider variety of goods and services than regional firms classified in the same industry. This product-mix problem implies that it may be quite improbable for both national and regional firms to consume the same inputs in the same proportions. In addition, the trade flows were estimated indirectly using the SLQ method. This method, however, assumes the concept of maximum local production and precludes cross-hauling transactions between regions, so it is possible that the estimated trade flows may be underestimated. One way to reduce the extent of the product mix problem

�7 Net foreign exchange earnings are the difference betweendirectforeignexchangeearningsasrepresentedbyexportsandtheimportedinputsneededtoproducesuchexports.

is to increase the degree of industrial disaggregation of the IRIO table, while an effective way to deal with this problem and the limitations of the SLQ method is to consider undertaking surveys to collect the data in future updates of the IRIO table.

The IRIO table assumes that the estimated regional input coefficients are stable over time, as explained in Riefler and Tiebout (1970). This assumption of stability for the regional input coefficients entails two separate assumptions. One, it is assumed that the regional technical coefficients are stable. Two, the interregional trade coefficients are assumed to be stable as well. The first assumption is common to all IO tables, while the second assumption is unique to the interregional variety. There are, however, no overwhelming theoretical reasons for the stability of interregional trade coefficients, especially over the long run. Thus, while the IRIO table may be a useful device in predicting the short-run reaction path of the economies of both provinces, any predictive use of the table over longer time periods will need to take into consideration any variability in trading patterns.

The modified simple biproportional RAS method was extensively used to balance the intra-Mukdahan IO table as it involves a rather simple iterative procedure requiring minimal programming effort to implement. The revision process was supplemented by intuitive judgment, where appropriate. However, this method has a shortcoming in that by generating a point estimate for each relevant cell during the balancing process, it may not be flexible enough to handle data of different quality. One possible way to overcome this problem is to consider the use of the cross-entropy method in the balancing process in future studies. This method provides more flexibility in dealing with scattered and inconsistent data in the balancing procedure by defining for each cell entry a lower and upper bound, so that the additional information can be used to generate a more reliable balanced IO table. The cross entropy method will also help to eliminate the use of intuitive judgment, which may be quite arbitrary in nature, in the balancing process.18

To reduce the data requirements and time involved, the IRIO table in our study aggregated the rest of Thailand and rest of Lao PDR regions into the ROW region, which was assumed to be exogenous.

�8 More information on the cross entropy method can beobtainedfromRobinsonetal.(�00�).



Consequently, the table will not be able to measure the extent of any economic interdependence between the two provinces and the rest of Thailand and the rest of Lao PDR. Future studies to improve the model may consider endogenizing these two regions so as to improve the spatial coverage, thus enhancing its overall usefulness in regional economic policy formulations.

vII. concLuSIon

This paper has developed a modified IRIO table for the province of Mukdahan in Thailand and Lao PDR province of Savannakhet using the Chenery-Moses model. A diacritical feature of this study is that, unlike most other studies that construct IRIO tables for a single country, the IRIO table was developed to link the provinces of two different countries. A hybrid approach was used to construct the IRIO table. This essentially involved using primary data collected from a specially conducted survey to develop the Savannakhet portion of the table, and indirect methods to construct the Mukdahan portion of the table as well as the interregional trade flows. As can be observed above, an IRIO table can be used for various applications such as multiplier, linkage, and impact analyses as well as estimation of interregional spillover and feedback effects.

The analysis of the economies of both provinces revealed that Mukdahan had a higher per capita GPP than Savannakhet in 2003. GVA in Savannakhet was found to be split quite evenly across the agricultural and fishery, industry, and services sectors, while GVA in Mukdahan was found to be dominated by the services sector. One reason for the difference could be the different stages of economic development of the two provinces.

The analysis of the economic relationship between the two provinces found that the value of trade of these provinces with the ROW was much higher than the trade between them. This suggests that proximity of the two provinces to each other has not resulted in a high level of economic interdependency between them. Rather, each province appears to depend relatively more on the ROW to satisfy its demand requirements. Consequently, the estimated interregional spillover and feedback effects were found to be rather negligible.

The multiplier analysis found that the manufacturing industries in both provinces had the highest output multipliers. In both provinces, industries in the services sector were found to have generally higher VA multipliers than industries in the manufacturing sector. This could be due to the higher dependence of the services industries on the domestic industries, rather than imports, for their input requirements so that more VA was generated in the economies of both provinces by the consumption of the output of the services industries than that of the manufacturing sector. The income and employment multipliers for the agriculture and fishery, wholesale and retail trade, and public administration industries in both provinces were generally higher than those of most other industries. This could be due to the highly labor-intensive nature of these industries.

The results also showed that the agriculture and forestry industry in Savannakhet and the manufacturing industries in both provinces had high forward and backward linkages. Such industries not only tend to use intermediate inputs from the other sectors of an economy quite heavily, but also have a great influence in supplying inputs to the other sectors. This suggests that, on the basis of the estimated linkage results, these industries can be given higher priority when developing policies to enhance the economies of both provinces.

The impact analysis found that consumption in both provinces had the highest GVA and lowest imports multipliers. One likely reason for these results could be their relatively low dependence on imports. ROW exports and consumption were also found to have the highest employment multipliers in Mukdahan and Savannakhet, respectively. This could be due to the relatively large share of the output of highly labor-intensive industries in these final demand components. Mukdahan was also found to have higher net foreign exchange earnings than Savannakhet. This suggests that the Thailand province may be able to add greater value to its exports than the Lao PDR province.

The study has outlined some key data and methodological issues that could bias the quality of results. These include the product mix problem associated with the method to regionalize the national coefficients, exclusion of cross hauling transactions in the application of the SLQ method, assumption of stable interregional trade coefficients, use of the rather

July 2007 �7


mechanical modified simple biproportional RAS method in the balancing process, and assumption of the rest of Thailand and rest of Lao PDR as exogenous regions.

To overcome these problems, future updates on the IRIO table could consider undertaking partial surveys to collect primary data, at least for the more important economic sectors in both provinces;

exploring the feasibility of disaggregating the industries at a finer level; using the more sophisticated cross entropy method in the balancing process; as well as endogenizing the rest of Thailand and rest of Lao PDR regions. Implementing these solutions will help enhance the accuracy and reliability of the results and ensure that the various regional coefficients are kept up to date.



1. Basic 20-Sector Intraregional I-O Tables

Table A-1: Intra-Mukdahan Input–Output Table, Competitive TypeTable A-2: Intra-Savannakhet Input–Output Table, Competitive TypeTable A-3: Intra-Mukdahan Input–Output Table, Noncompetitive TypeTable A-4: Intra-Savannakhet Input–Output Table, Noncompetitive TypeTable A-5: Intra-Mukdahan Direct Input Coefficients, Noncompetitive TypeTable A-6: Intra-Savannakhet Direct Input Coefficients, Noncompetitive TypeTable A-7: Intra-Mukdahan Leontief Inverse, Noncompetitive TypeTable A-8: Intra-Savannakhet Leontief Inverse, Noncompetitive Type

2. Aggregated 10-Sector Intraregional I-O Tables

Table B-1: Intra-Mukdahan Input–Output Table, Competitive TypeTable B-2: Intra-Savannakhet Input–Output Table, Competitive TypeTable B-3: Intra-Mukdahan Input–Output Table, Noncompetitive TypeTable B-4: Intra-Savannakhet Input–Output Table, Noncompetitive TypeTable B-5: Intra-Mukdahan Direct Input Coefficients, Noncompetitive TypeTable B-6: Intra-Savannakhet Direct Input Coefficients, Noncompetitive TypeTable B-7: Intra-Mukdahan Leontief Inverse, Noncompetitive TypeTable B-8: Intra-Savannakhet Leontief Inverse, Noncompetitive Type

3. Interregional I-O Tables

Table C-1: 20-sector (Mukdahan–Savannakhet) Interregional IO TableTable C-2: 20-sector (Mukdahan–Savannakhet) Interregional Input CoefficientsTable C-3: 20-sector (Mukdahan–Savannakhet) Interregional Leontief InverseTable C-4: 10-sector (Mukdahan–Savannakhet) Interregional IO TableTable C-5: 10-sector (Mukdahan–Savannakhet) Interregional Input CoefficientsTable C-6:10-sector (Mukdahan–Savannakhet) Interregional Leontief Inverse

appendIx1:LIStoFInput–outputtabLeS

July 2007 ��


Major Sector Major industry industryi Agriculture and forestry 1 Agriculture and forestry 01 Crops

02 Livestock and poultry , fishery

0� Forestry and logging

ii Industry 2 Mining and quarrying 0� Mining and quarrying

0� Food, beverage, and tobacco

0� Textiles, garments, and leather products

� Manufacturing 07 Wood and paper products; printing/publishing

0� Chemical products; petroleum

0� Nonmetallic mineral products

10 Metal products, machinery, equipment, and spare parts

11 Other manufactured goods

� Electricity and water supply 12 Electricity and water supply

� Construction 1� Construction

iii Services � Transportation and communications 1� Transportation

1� Post and telecommunications

7 Wholesale and retail trade 1� Wholesale and retail trade

� Finance, real estate, and business services

17 Banking, insurance, business services

1� Real estate and ownership of dwellings

� Public administration 1� Public administration

10 Personal, social, and community services

20 Personal, social, and community services

appendIx2:correSpondencebetween20InduStrIeS,10MajorInduStrIeS,and3MajorSectorS



SeLectedreFerenceS

Asra, A., F. T. Secretario, and E. B. Suan. 2006. Development of an Input-Output Framework: An Application to Savannakhet, Lao PDR. Economics and Research Department, Asian Development Bank. Unpublished report.

Benvenuti, S. C., and R. Paniccià. 2003. "A Multi-regional Input–Output Model for Italy." Istituto Regionale Programmazione EconomicaToscana. Available: http://www.irpet.it/storage/pubblicazioneallegato/34_Interventin.22.pdf.

Chenery, H. B. 1956. “Interregional and International Input-Output Analysis.” In T. Barna, ed., The Structural Interdependence of the Economy. New York: John Wiley and Sons, Inc.

Chenery, H. B., and Paul G. Clark. 1959. Interindustry Economics. New York: John Wiley & Sons, Inc.

Fritz O., E. Kolleritsch, and G. Streicher. 2006. "Building a Multiregional Input-Output Table for Austria: Compilation Methods and Results." Paper presented at the Intermediate Input–Output Conference on Sustainability, Trade and Productivity, 26–28 July, Sendai, Japan. Available: http://www.iioa.org/pdf/Intermediate-2006/Full%20paper_Fritz.pdf.

Ichihashi, M. 2000. “Measuring of Interregional Trade Relations Over the Border: An Example of Hiroshima and Heilongjiang.” Regional Economic Studies 20:31–43. Available: http://www-cres.senda.hiroshima-u.ac.jp/publications/bulletin/kiyo/vol11/11-03.pdf.

Institute of Developing Economies–Japan External Trade Organization. 2006a. Asian International Input-Output Table Volume 1: Explanatory Notes. IDE Statistical Data Series No. 89, Tokyo.

Institute of Developing Economies–Japan External Trade Organization. 2006b. Asian International Input-Output Table Volume 2: Data. IDE Statistical Data Series No. 90, Tokyo.

Isard, W. 1951. “Interregional and Regional Input-Output Analysis: A Model of a Space-Economy.” Review of Economics and Statistics 33(4):318–28.

Isard, W., I. J. Azis, M. P. Drennan, R. E. Miller, S. Saltzman, and E. Thorbecke. 1998. Methods of Interregional and Regional Analysis. Aldershot: Ashgate Publishing Limited.

Ishikawa, Y., and T. Miyagi. 2004. “The Construction of a 47-Region Inter-regional Input–Output Table and Inter-regional Interdependence Analysis at Prefecture Level in Japan.” Paper presented at the 44th European Congress of the European Regional Science Association, Porto, Portugal. Available: http://www.ersa.org/ersaconfs/ersa04/PDF/432.pdf.

Hartwick, J. M. 1971. “Notes on the Isard and Chenery-Moses Interregional Input-Output Models.” Journal of Regional Science 11(1):73–86.

Leontief, W. 1936. “Quantitative Input and Output Relations in the Economic Systems of the United States.” Review of Economic Statistics 18(3):105–25.

Miller, R. E., and P. D. Blair. 1985. Input-Output Analysis: Foundations and Extensions. New Jersey: Prentice-Hall, Inc.

Moses, L. N. 1955. “The Stability of Interregional Trading Patterns and Input-Output Analysis.” American Economic Review 45(5):803–26.

Okamoto, N., Y. X. Zhang, S. Hioki, T. Kanazawa, and K. Zhao. 2005. “A Method for Constructing an Interregional Input-Output Model of China for 2000.” Journal of Econometric Study of Northeast Asia 5(2):23–6. Available: http://www.erina.or.jp/en/Publications/jesna/pdf/jesna5-2.pdf.

Okuda, T., T. Hatano, and S. C. Qi. 2004. “An Estimation of a Multi-Regional Input/Output Table in China and the Analysis.” Paper presented at the Conference on Input-Output and General Equilibrium: Data, Modeling, and Policy Analysis, 3 September, Brussels. Available: http://www.ecomod.net/conferences/iioa2004/iioa2004_papers/399.pdf.

Piispala, J. 2000. “On Regionalising Input/Output Tables—Experiences from Compiling Regional Supply and Use Tables in Finland.” Paper presented at the 13th International Conference on Input-Output Techniques, University of Macerata, Italy. Available: http://www.iioa.org/pdf/13th%20conf/Piispala_RegionalMakeUse.pdf.

Quesnay, F. 1759. Tableau Économique. Reprinted 1894. British Economic Association (now Royal Economic Society), United Kingdom.

July 2007 �1


Rasmussen, P. N. 1957. Studies in Inter-Sectoral Relations. Amsterdam: North Holland Publishing Company.

Richardson, H. W. 1972. Input-Output and Regional Economics. London: Weidenfeld and Nicolson.

Riefler, R., and C. M. Tiebout. 1970. “Interregional Input-Output: An Empirical California-Washington Model.” Journal of Regional Science 10(2):135–51.

Robinson, S., A. Cattaneo, and M. El-Said. 2001. “Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods.” Economic Systems Research 13(1):47–64.

Secretario, F. T. 1994. Construction of a 5-Region Inter-Regional Input-Output Table of The Philippines. Final Technical Report prepared for the JSPS Project — Manila Regional Input-Output Research Project. Japan Society for the Promotion of Science.

Secretario, F., K. Kim, and C. Goce-Dakila. 2002. “The Metro-Manila Inter-Regional Input-Output Table: Its Attempt of Compilation by the Hybrid Approach.” Paper presented at the 14th International Conference on Input-Output Techniques, 10–15 October, Montreal, Canada. Available: http://www.iioa.org/pdf/14th%20conf/kimkwangmoon.pdf.

Secretario, F. T., B. Trinh, D. M. Hung, and K. M. Kim, 2003a. “Construction of An Inter-Regional Input-Output Table for Viet Nam by the Hybrid Approach.” Paper presented at the Symposium on Study on Regional Economic-Natural Environment in Viet Nam’s Transition Economy, 1 July, Nissan Research Foundation, Hanoi.

. 2003b. “Inter-Regional Input-Output Analysis: The Case of Ho Chi Minh City and the Rest of Vietnam Economies.” Paper presented at the Symposium on Study on Regional Economic-Natural Environment in Viet Nam’s Transition Economy, 1 July, Nissan Research Foundation, Hanoi.

Verduras, C. L. 2000. “The Estimation of the Interregional Trade in the Context of an Interregional Input-Output Model for the Spanish Economy.” Paper presented at the 13th International Conference on Input-Output Techniques, 21–25 August, University of Macerata, Italy. Available: http://www.iioa.org/pdf/13th%20conf/Llano_EstimatingSpanishInterregionalTrade.pdf.

Walras, L. 1874. Elements of Pure Economics. Translated by W. Jaffe, 1954. Homewood, IL: Richard Irwin, Inc.

42

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44

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No. 60 Measuring Competitiveness in the World’s SmallestEconomies: Introducing the SSMECI—Ganeshan Wignaraja and David Joiner, November2004

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45

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No. 72 Can the Poor Benefit from the Doha Agenda? TheCase of Indonesia—Douglas H. Brooks and Guntur Sugiyarto,October 2005

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No. 74 Growth and Trade Horizons for Asia: Long-termForecasts for Regional Integration—David Roland-Holst, Jean-Pierre Verbiest, andFan Zhai, November 2005

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No. 76 Policy Reform in Indonesia and the AsianDevelopment Bank’s Financial Sector GovernanceReforms Program Loan—George Abonyi, December 2005

No. 77 Dynamics of Manufacturing Competitiveness inSouth Asia: ANalysis through Export Data—Hans-Peter Brunner and Massimiliano Calì,December 2005

No. 78 Trade Facilitation—Teruo Ujiie, January 2006

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No. 80 Central Asia: Mapping Future Prospects to 2015—Malcolm Dowling and Ganeshan Wignaraja,April 2006

No. 81 A Small Macroeconometric Model of the People’sRepublic of China—Duo Qin, Marie Anne Cagas, Geoffrey Ducanes,Nedelyn Magtibay-Ramos, Pilipinas Quising, Xin-Hua He, Rui Liu, and Shi-Guo Liu, June 2006

No. 82 Institutions and Policies for Growth and PovertyReduction: The Role of Private Sector Development—Rana Hasan, Devashish Mitra, and MehmetUlubasoglu, July 2006

No. 83 Preferential Trade Agreements in Asia:Alternative Scenarios of “Hub and Spoke”—Fan Zhai, October 2006

No. 84 Income Disparity and Economic Growth: Evidencefrom People’s Republic of China— Duo Qin, Marie Anne Cagas, Geoffrey Ducanes,Xinhua He, Rui Liu, and Shiguo Liu, October 2006

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No. 86 Economic Growth, Technological Change, andPatterns of Food and Agricultural Trade in Asia— Thomas W. Hertel, Carlos E. Ludena, and AllaGolub, November 2006

No. 87 Expanding Access to Basic Services in Asia and thePacific Region: Public–Private Partnerships forPoverty Reduction— Adrian T. P. Panggabean, November 2006

No. 88 Income Volatility and Social Protection inDeveloping Asia—Vandana Sipahimalani-Rao, November 2006

No. 89 Rules of Origin: Conceptual Explorations andLessons from the Generalized System ofPreferences—Teruo Ujiie, December 2006

No. 90 Asia’s Imprint on Global Commodity Markets—Cyn-Young Park and Fan Zhai, December 2006

No. 91 Infrastructure as a Catalyst for RegionalIntegration, Growth, and Economic Convergence:Scenario Analysis for Asia—David Roland-Holst, December 2006

No. 92 Measuring Underemployment: Establishing theCut-off Point—Guntur Sugiyarto, March 2007

No. 93 An Analysis of the Philippine Business ProcessOutsourcing Industry—Nedelyn Magtibay-Ramos, Gemma Estrada, andJesus Felipe, March 2007

No. 94 Theory and Practice in the Choice of SocialDiscount Rate for Cost–Benefit Analysis: A Survey—Juzhong Zhuang, Zhihong Liang, Tun Lin, andFranklin De Guzman, May 2007

No. 95 Can East Asia Weather a US Slowdown?—Cyn-Young Park, June 2007

No. 96 Interrelationship between Growth, Inequality, andPoverty: the Asian Experience—Hyun H. Son, June 2007

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No. 1 Is Growth Good Enough for the Poor?—Ernesto M. Pernia, October 2001

No. 2 India’s Economic ReformsWhat Has Been Accomplished?What Remains to Be Done?—Arvind Panagariya, November 2001

No. 3 Unequal Benefits of Growth in Viet Nam—Indu Bhushan, Erik Bloom, and Nguyen MinhThang, January 2002

No. 4 Is Volatility Built into Today’s World Economy?—J. Malcolm Dowling and J.P. Verbiest,February 2002

No. 5 What Else Besides Growth Matters to PovertyReduction? Philippines—Arsenio M. Balisacan and Ernesto M. Pernia,February 2002

No. 6 Achieving the Twin Objectives of Efficiency andEquity: Contracting Health Services in Cambodia—Indu Bhushan, Sheryl Keller, and Brad Schwartz,March 2002

No. 7 Causes of the 1997 Asian Financial Crisis: WhatCan an Early Warning System Model Tell Us?—Juzhong Zhuang and Malcolm Dowling,June 2002

No. 8 The Role of Preferential Trading Arrangementsin Asia—Christopher Edmonds and Jean-Pierre Verbiest,July 2002

No. 9 The Doha Round: A Development Perspective—Jean-Pierre Verbiest, Jeffrey Liang, and LeaSumulong, July 2002

No. 10 Is Economic Openness Good for RegionalDevelopment and Poverty Reduction? ThePhilippines—E. M. Pernia and Pilipinas Quising, October2002

No. 11 Implications of a US Dollar Depreciation for AsianDeveloping Countries—Emma Fan, July 2002

No. 12 Dangers of Deflation—D. Brooks and Pilipinas Quising, December 2002

No. 13 Infrastructure and Poverty Reduction—What is the Connection?—Ifzal Ali and Ernesto Pernia, January 2003

No. 14 Infrastructure and Poverty Reduction—Making Markets Work for the Poor—Xianbin Yao, May 2003

No. 15 SARS: Economic Impacts and Implications—Emma Xiaoqin Fan, May 2003

No. 16 Emerging Tax Issues: Implications of Globalizationand Technology—Kanokpan Lao Araya, May 2003

No. 17 Pro-Poor Growth: What is It and Why is ItImportant?—Ernesto M. Pernia, May 2003

No. 18 Public–Private Partnership for Competitiveness—Jesus Felipe, June 2003

No. 19 Reviving Asian Economic Growth Requires FurtherReforms—Ifzal Ali, June 2003

No. 20 The Millennium Development Goals and Poverty:Are We Counting the World’s Poor Right?—M. G. Quibria, July 2003

No. 21 Trade and Poverty: What are the Connections?—Douglas H. Brooks, July 2003

No. 22 Adapting Education to the Global Economy—Olivier Dupriez, September 2003

No. 23 Avian Flu: An Economic Assessment for SelectedDeveloping Countries in Asia—Jean-Pierre Verbiest and Charissa Castillo,March 2004

No. 25 Purchasing Power Parities and the InternationalComparison Program in a Globalized World—Bishnu Pant, March 2004

No. 26 A Note on Dual/Multiple Exchange Rates—Emma Xiaoqin Fan, May 2004

No. 27 Inclusive Growth for Sustainable Poverty Reductionin Developing Asia: The Enabling Role ofInfrastructure Development—Ifzal Ali and Xianbin Yao, May 2004

No. 28 Higher Oil Prices: Asian Perspectives andImplications for 2004-2005—Cyn-Young Park, June 2004

No. 29 Accelerating Agriculture and Rural Development forInclusive Growth: Policy Implications forDeveloping Asia—Richard Bolt, July 2004

No. 30 Living with Higher Interest Rates: Is Asia Ready?—Cyn-Young Park, August 2004

No. 31 Reserve Accumulation, Sterilization, and PolicyDilemma—Akiko Terada-Hagiwara, October 2004

No. 32 The Primacy of Reforms in the Emergence ofPeople’s Republic of China and India—Ifzal Ali and Emma Xiaoqin Fan, November2004

No. 33 Population Health and Foreign Direct Investment:Does Poor Health Signal Poor GovernmentEffectiveness?—Ajay Tandon, January 2005

No. 34 Financing Infrastructure Development: AsianDeveloping Countries Need to Tap Bond MarketsMore Rigorously—Yun-Hwan Kim, February 2005

No. 35 Attaining Millennium Development Goals inHealth: Isn’t Economic Growth Enough?—Ajay Tandon, March 2005

No. 36 Instilling Credit Culture in State-owned Banks—Experience from Lao PDR—Robert Boumphrey, Paul Dickie, and SamiuelaTukuafu, April 2005

No. 37 Coping with Global Imbalances and AsianCurrencies—Cyn-Young Park, May 2005

No. 38 Asia’s Long-term Growth and Integration:Reaching beyond Trade Policy Barriers—Douglas H. Brooks, David Roland-Holst, and FanZhai, September 2005

No. 39 Competition Policy and Development—Douglas H. Brooks, October 2005

No. 40 Highlighting Poverty as Vulnerability: The 2005Earthquake in Pakistan—Rana Hasan and Ajay Tandon, October 2005

No. 41 Conceptualizing and Measuring Poverty asVulnerability: Does It Make a Difference?—Ajay Tandon and Rana Hasan, October 2005

No. 42 Potential Economic Impact of an Avian FluPandemic on Asia—Erik Bloom, Vincent de Wit, and Mary JaneCarangal-San Jose, November 2005

ERD POLICY BRIEF SERIES (PBS)(Published in-house; Available through ADB Department of External Relations; Free of charge)

47

1. Improving Domestic Resource Mobilization ThroughFinancial Development: Overview September 1985

2. Improving Domestic Resource Mobilization ThroughFinancial Development: Bangladesh July 1986

3. Improving Domestic Resource Mobilization ThroughFinancial Development: Sri Lanka April 1987

4. Improving Domestic Resource Mobilization ThroughFinancial Development: India December 1987

5. Financing Public Sector Development Expenditurein Selected Countries: Overview January 1988

6. Study of Selected Industries: A Brief ReportApril 1988

7. Financing Public Sector Development Expenditurein Selected Countries: Bangladesh June 1988

8. Financing Public Sector Development Expenditurein Selected Countries: India June 1988

9. Financing Public Sector Development Expenditurein Selected Countries: Indonesia June 1988

10. Financing Public Sector Development Expenditurein Selected Countries: Nepal June 1988

11. Financing Public Sector Development Expenditurein Selected Countries: Pakistan June 1988

12. Financing Public Sector Development Expenditurein Selected Countries: Philippines June 1988

13. Financing Public Sector Development Expenditurein Selected Countries: Thailand June 1988

14. Towards Regional Cooperation in South Asia:ADB/EWC Symposium on Regional Cooperationin South Asia February 1988

15. Evaluating Rice Market Intervention Policies:Some Asian Examples April 1988

16. Improving Domestic Resource Mobilization ThroughFinancial Development: Nepal November 1988

17. Foreign Trade Barriers and Export Growth September1988

18. The Role of Small and Medium-Scale Industries in theIndustrial Development of the Philippines April 1989

19. The Role of Small and Medium-Scale ManufacturingIndustries in Industrial Development: The Experience ofSelected Asian Countries January 1990

20. National Accounts of Vanuatu, 1983-1987 January1990

21. National Accounts of Western Samoa, 1984-1986February 1990

22. Human Resource Policy and Economic Development:Selected Country Studies July 1990

23. Export Finance: Some Asian Examples September 199024. National Accounts of the Cook Islands, 1982-1986

September 199025. Framework for the Economic and Financial Appraisal of

Urban Development Sector Projects January 199426. Framework and Criteria for the Appraisal and

Socioeconomic Justification of Education ProjectsJanuary 1994

27. Investing in Asia 1997 (Co-published with OECD)28. The Future of Asia in the World Economy 1998 (Co-

published with OECD)29. Financial Liberalisation in Asia: Analysis and Prospects

1999 (Co-published with OECD)30. Sustainable Recovery in Asia: Mobilizing Resources for

Development 2000 (Co-published with OECD)31. Technology and Poverty Reduction in Asia and the Pacific

2001 (Co-published with OECD)32. Asia and Europe 2002 (Co-published with OECD)33. Economic Analysis: Retrospective 200334. Economic Analysis: Retrospective: 2003 Update 200435. Development Indicators Reference Manual: Concepts and

Definitions 200436. Investment Climate and Productivity Studies

Philippines: Moving Toward a Better Investment Climate2005The Road to Recovery: Improving the Investment Climatein Indonesia 2005Sri Lanka: Improving the Rural and Urban InvestmentClimate 2005Lao PDR Private Sector and Investment ClimateAssessment: Reducing Investment Climate Constraintsto Higher Growth 2006

SPECIAL STUDIES, COMPLIMENTARY(Available through ADB Department of External Relations)

No. 43 Creating Better and More Jobs in Indonesia: ABlueprint for Policy Action—Guntur Sugiyarto, December 2005

No. 44 The Challenge of Job Creation in Asia—Jesus Felipe and Rana Hasan, April 2006

No. 45 International Payments Imbalances—Jesus Felipe, Frank Harrigan, and AashishMehta, April 2006

No. 46 Improving Primary Enrollment Rates among thePoor—Ajay Tandon, August 2006

No. 47 Inclusiveness of Economic Growth in the People’sRepublic of China: What Do Population HealthOutcomes Tell Us?—Ajay Tandon and Juzhong Zhuang, January 2007

No. 48 Pro-Poor to Inclusive Growth: Asian Prescriptions—Ifzal Ali, May 2007

No. 49 Technology and Development in Asia—Frank Harrigan, June 2007

48

OLD MONOGRAPH SERIES(Available through ADB Department of External Relations; Free of charge)

EDRC REPORT SERIES (ER)

No. 1 ASEAN and the Asian Development Bank—Seiji Naya, April 1982

No. 2 Development Issues for the Developing Eastand Southeast Asian Countriesand International Cooperation—Seiji Naya and Graham Abbott, April 1982

No. 3 Aid, Savings, and Growth in the Asian Region—J. Malcolm Dowling and Ulrich Hiemenz,

April 1982No. 4 Development-oriented Foreign Investment

and the Role of ADB—Kiyoshi Kojima, April 1982

No. 5 The Multilateral Development Banksand the International Economy’s MissingPublic Sector—John Lewis, June 1982

No. 6 Notes on External Debt of DMCs—Evelyn Go, July 1982

No. 7 Grant Element in Bank Loans—Dal Hyun Kim, July 1982

No. 8 Shadow Exchange Rates and StandardConversion Factors in Project Evaluation—Peter Warr, September 1982

No. 9 Small and Medium-Scale ManufacturingEstablishments in ASEAN Countries:Perspectives and Policy Issues—Mathias Bruch and Ulrich Hiemenz, January1983

No. 10 A Note on the Third Ministerial Meeting of GATT—Jungsoo Lee, January 1983

No. 11 Macroeconomic Forecasts for the Republicof China, Hong Kong, and Republic of Korea—J.M. Dowling, January 1983

No. 12 ASEAN: Economic Situation and Prospects—Seiji Naya, March 1983

No. 13 The Future Prospects for the DevelopingCountries of Asia—Seiji Naya, March 1983

No. 14 Energy and Structural Change in the Asia-Pacific Region, Summary of the ThirteenthPacific Trade and Development Conference—Seiji Naya, March 1983

No. 15 A Survey of Empirical Studies on Demandfor Electricity with Special Emphasis on PriceElasticity of Demand—Wisarn Pupphavesa, June 1983

No. 16 Determinants of Paddy Production in Indonesia:1972-1981–A Simultaneous Equation ModelApproach—T.K. Jayaraman, June 1983

No. 17 The Philippine Economy: EconomicForecasts for 1983 and 1984—J.M. Dowling, E. Go, and C.N. Castillo, June1983

No. 18 Economic Forecast for Indonesia—J.M. Dowling, H.Y. Kim, Y.K. Wang,

and C.N. Castillo, June 1983No. 19 Relative External Debt Situation of Asian

Developing Countries: An Applicationof Ranking Method—Jungsoo Lee, June 1983

No. 20 New Evidence on Yields, Fertilizer Application,and Prices in Asian Rice Production—William James and Teresita Ramirez, July 1983

No. 21 Inflationary Effects of Exchange RateChanges in Nine Asian LDCs

—Pradumna B. Rana and J. Malcolm Dowling, Jr.,December 1983

No. 22 Effects of External Shocks on the Balanceof Payments, Policy Responses, and DebtProblems of Asian Developing Countries—Seiji Naya, December 1983

No. 23 Changing Trade Patterns and Policy Issues:The Prospects for East and Southeast AsianDeveloping Countries—Seiji Naya and Ulrich Hiemenz, February 1984

No. 24 Small-Scale Industries in Asian EconomicDevelopment: Problems and Prospects—Seiji Naya, February 1984

No. 25 A Study on the External Debt IndicatorsApplying Logit Analysis—Jungsoo Lee and Clarita Barretto, February 1984

No. 26 Alternatives to Institutional Credit Programsin the Agricultural Sector of Low-IncomeCountries—Jennifer Sour, March 1984

No. 27 Economic Scene in Asia and Its Special Features—Kedar N. Kohli, November 1984

No. 28 The Effect of Terms of Trade Changes on theBalance of Payments and Real NationalIncome of Asian Developing Countries—Jungsoo Lee and Lutgarda Labios, January 1985

No. 29 Cause and Effect in the World Sugar Market:Some Empirical Findings 1951-1982—Yoshihiro Iwasaki, February 1985

No. 30 Sources of Balance of Payments Problemin the 1970s: The Asian Experience—Pradumna Rana, February 1985

No. 31 India’s Manufactured Exports: An Analysisof Supply Sectors—Ifzal Ali, February 1985

No. 32 Meeting Basic Human Needs in AsianDeveloping Countries—Jungsoo Lee and Emma Banaria, March 1985

No. 33 The Impact of Foreign Capital Inflowon Investment and Economic Growthin Developing Asia—Evelyn Go, May 1985

No. 34 The Climate for Energy Developmentin the Pacific and Asian Region:Priorities and Perspectives—V.V. Desai, April 1986

No. 35 Impact of Appreciation of the Yen onDeveloping Member Countries of the Bank—Jungsoo Lee, Pradumna Rana, and Ifzal Ali,May 1986

No. 36 Smuggling and Domestic Economic Policiesin Developing Countries—A.H.M.N. Chowdhury, October 1986

No. 37 Public Investment Criteria: Economic InternalRate of Return and Equalizing Discount Rate—Ifzal Ali, November 1986

No. 38 Review of the Theory of Neoclassical PoliticalEconomy: An Application to Trade Policies—M.G. Quibria, December 1986

No. 39 Factors Influencing the Choice of Location:Local and Foreign Firms in the Philippines—E.M. Pernia and A.N. Herrin, February 1987

No. 40 A Demographic Perspective on DevelopingAsia and Its Relevance to the Bank—E.M. Pernia, May 1987

49

No. 1 International Reserves:Factors Determining Needs and Adequacy—Evelyn Go, May 1981

No. 2 Domestic Savings in Selected DevelopingAsian Countries—Basil Moore, assisted by A.H.M. NuruddinChowdhury, September 1981

No. 3 Changes in Consumption, Imports and Exportsof Oil Since 1973: A Preliminary Survey ofthe Developing Member Countriesof the Asian Development Bank—Dal Hyun Kim and Graham Abbott, September1981

No. 4 By-Passed Areas, Regional Inequalities,and Development Policies in SelectedSoutheast Asian Countries—William James, October 1981

No. 5 Asian Agriculture and Economic Development—William James, March 1982

No. 6 Inflation in Developing Member Countries:An Analysis of Recent Trends—A.H.M. Nuruddin Chowdhury and J. MalcolmDowling, March 1982

No. 7 Industrial Growth and Employment inDeveloping Asian Countries: Issues and

ECONOMIC STAFF PAPERS (ES)

Perspectives for the Coming Decade—Ulrich Hiemenz, March 1982

No. 8 Petrodollar Recycling 1973-1980.Part 1: Regional Adjustments andthe World Economy—Burnham Campbell, April 1982

No. 9 Developing Asia: The Importanceof Domestic Policies—Economics Office Staff under the direction of SeijiNaya, May 1982

No. 10 Financial Development and HouseholdSavings: Issues in Domestic ResourceMobilization in Asian Developing Countries—Wan-Soon Kim, July 1982

No. 11 Industrial Development: Role of SpecializedFinancial Institutions—Kedar N. Kohli, August 1982

No. 12 Petrodollar Recycling 1973-1980.Part II: Debt Problems and an Evaluationof Suggested Remedies—Burnham Campbell, September 1982

No. 13 Credit Rationing, Rural Savings, and FinancialPolicy in Developing Countries—William James, September 1982

No. 41 Emerging Issues in Asia and Social CostBenefit Analysis—I. Ali, September 1988

No. 42 Shifting Revealed Comparative Advantage:Experiences of Asian and Pacific DevelopingCountries—P.B. Rana, November 1988

No. 43 Agricultural Price Policy in Asia:Issues and Areas of Reforms—I. Ali, November 1988

No. 44 Service Trade and Asian Developing Economies—M.G. Quibria, October 1989

No. 45 A Review of the Economic Analysis of PowerProjects in Asia and Identification of Areasof Improvement—I. Ali, November 1989

No. 46 Growth Perspective and Challenges for Asia:Areas for Policy Review and Research—I. Ali, November 1989

No. 47 An Approach to Estimating the PovertyAlleviation Impact of an Agricultural Project—I. Ali, January 1990

No. 48 Economic Growth Performance of Indonesia,the Philippines, and Thailand:The Human Resource Dimension—E.M. Pernia, January 1990

No. 49 Foreign Exchange and Fiscal Impact of a Project:A Methodological Framework for Estimation—I. Ali, February 1990

No. 50 Public Investment Criteria: Financialand Economic Internal Rates of Return—I. Ali, April 1990

No. 51 Evaluation of Water Supply Projects:An Economic Framework—Arlene M. Tadle, June 1990

No. 52 Interrelationship Between Shadow Prices, ProjectInvestment, and Policy Reforms:An Analytical Framework—I. Ali, November 1990

No. 53 Issues in Assessing the Impact of Projectand Sector Adjustment Lending—I. Ali, December 1990

No. 54 Some Aspects of Urbanizationand the Environment in Southeast Asia—Ernesto M. Pernia, January 1991

No. 55 Financial Sector and EconomicDevelopment: A Survey—Jungsoo Lee, September 1991

No. 56 A Framework for Justifying Bank-AssistedEducation Projects in Asia: A Reviewof the Socioeconomic Analysisand Identification of Areas of Improvement—Etienne Van De Walle, February 1992

No. 57 Medium-term Growth-StabilizationRelationship in Asian Developing Countriesand Some Policy Considerations—Yun-Hwan Kim, February 1993

No. 58 Urbanization, Population Distribution,and Economic Development in Asia—Ernesto M. Pernia, February 1993

No. 59 The Need for Fiscal Consolidation in Nepal:The Results of a Simulation—Filippo di Mauro and Ronald Antonio Butiong,July 1993

No. 60 A Computable General Equilibrium Modelof Nepal—Timothy Buehrer and Filippo di Mauro, October1993

No. 61 The Role of Government in Export Expansionin the Republic of Korea: A Revisit—Yun-Hwan Kim, February 1994

No. 62 Rural Reforms, Structural Change,and Agricultural Growth inthe People’s Republic of China—Bo Lin, August 1994

No. 63 Incentives and Regulation for Pollution Abatementwith an Application to Waste Water Treatment—Sudipto Mundle, U. Shankar, and ShekharMehta, October 1995

No. 64 Saving Transitions in Southeast Asia—Frank Harrigan, February 1996

No. 65 Total Factor Productivity Growth in East Asia:A Critical Survey—Jesus Felipe, September 1997

No. 66 Foreign Direct Investment in Pakistan:Policy Issues and Operational Implications—Ashfaque H. Khan and Yun-Hwan Kim, July1999

No. 67 Fiscal Policy, Income Distribution and Growth—Sailesh K. Jha, November 1999

50

No. 14 Small and Medium-Scale ManufacturingEstablishments in ASEAN Countries:Perspectives and Policy Issues—Mathias Bruch and Ulrich Hiemenz, March 1983

No. 15 Income Distribution and EconomicGrowth in Developing Asian Countries—J. Malcolm Dowling and David Soo, March 1983

No. 16 Long-Run Debt-Servicing Capacity ofAsian Developing Countries: An Applicationof Critical Interest Rate Approach—Jungsoo Lee, June 1983

No. 17 External Shocks, Energy Policy,and Macroeconomic Performance of AsianDeveloping Countries: A Policy Analysis—William James, July 1983

No. 18 The Impact of the Current Exchange RateSystem on Trade and Inflation of SelectedDeveloping Member Countries—Pradumna Rana, September 1983

No. 19 Asian Agriculture in Transition: Key Policy Issues—William James, September 1983

No. 20 The Transition to an Industrial Economyin Monsoon Asia—Harry T. Oshima, October 1983

No. 21 The Significance of Off-Farm Employmentand Incomes in Post-War East Asian Growth—Harry T. Oshima, January 1984

No. 22 Income Distribution and Poverty in SelectedAsian Countries—John Malcolm Dowling, Jr., November 1984

No. 23 ASEAN Economies and ASEAN EconomicCooperation—Narongchai Akrasanee, November 1984

No. 24 Economic Analysis of Power Projects—Nitin Desai, January 1985

No. 25 Exports and Economic Growth in the Asian Region—Pradumna Rana, February 1985

No. 26 Patterns of External Financing of DMCs—E. Go, May 1985

No. 27 Industrial Technology Developmentthe Republic of Korea—S.Y. Lo, July 1985

No. 28 Risk Analysis and Project Selection:A Review of Practical Issues—J.K. Johnson, August 1985

No. 29 Rice in Indonesia: Price Policy and ComparativeAdvantage—I. Ali, January 1986

No. 30 Effects of Foreign Capital Inflowson Developing Countries of Asia—Jungsoo Lee, Pradumna B. Rana, and YoshihiroIwasaki, April 1986

No. 31 Economic Analysis of the EnvironmentalImpacts of Development Projects—John A. Dixon et al., EAPI, East-West Center,August 1986

No. 32 Science and Technology for Development:Role of the Bank—Kedar N. Kohli and Ifzal Ali, November 1986

No. 33 Satellite Remote Sensing in the Asianand Pacific Region—Mohan Sundara Rajan, December 1986

No. 34 Changes in the Export Patterns of Asian andPacific Developing Countries: An EmpiricalOverview—Pradumna B. Rana, January 1987

No. 35 Agricultural Price Policy in Nepal—Gerald C. Nelson, March 1987

No. 36 Implications of Falling Primary CommodityPrices for Agricultural Strategy in the Philippines—Ifzal Ali, September 1987

No. 37 Determining Irrigation Charges: A Framework—Prabhakar B. Ghate, October 1987

No. 38 The Role of Fertilizer Subsidies in AgriculturalProduction: A Review of Select Issues

—M.G. Quibria, October 1987No. 39 Domestic Adjustment to External Shocks

in Developing Asia—Jungsoo Lee, October 1987

No. 40 Improving Domestic Resource Mobilizationthrough Financial Development: Indonesia—Philip Erquiaga, November 1987

No. 41 Recent Trends and Issues on Foreign DirectInvestment in Asian and Pacific DevelopingCountries—P.B. Rana, March 1988

No. 42 Manufactured Exports from the Philippines:A Sector Profile and an Agenda for Reform—I. Ali, September 1988

No. 43 A Framework for Evaluating the EconomicBenefits of Power Projects—I. Ali, August 1989

No. 44 Promotion of Manufactured Exports in Pakistan—Jungsoo Lee and Yoshihiro Iwasaki, September1989

No. 45 Education and Labor Markets in Indonesia:A Sector Survey—Ernesto M. Pernia and David N. Wilson,September 1989

No. 46 Industrial Technology Capabilitiesand Policies in Selected ADCs—Hiroshi Kakazu, June 1990

No. 47 Designing Strategies and Policiesfor Managing Structural Change in Asia—Ifzal Ali, June 1990

No. 48 The Completion of the Single European CommunityMarket in 1992: A Tentative Assessment of itsImpact on Asian Developing Countries—J.P. Verbiest and Min Tang, June 1991

No. 49 Economic Analysis of Investment in Power Systems—Ifzal Ali, June 1991

No. 50 External Finance and the Role of MultilateralFinancial Institutions in South Asia:Changing Patterns, Prospects, and Challenges—Jungsoo Lee, November 1991

No. 51 The Gender and Poverty Nexus: Issues andPolicies—M.G. Quibria, November 1993

No. 52 The Role of the State in Economic Development:Theory, the East Asian Experience,and the Malaysian Case—Jason Brown, December 1993

No. 53 The Economic Benefits of Potable Water SupplyProjects to Households in Developing Countries—Dale Whittington and Venkateswarlu Swarna,January 1994

No. 54 Growth Triangles: Conceptual Issuesand Operational Problems—Min Tang and Myo Thant, February 1994

No. 55 The Emerging Global Trading Environmentand Developing Asia—Arvind Panagariya, M.G. Quibria, and NarhariRao, July 1996

No. 56 Aspects of Urban Water and Sanitation inthe Context of Rapid Urbanization inDeveloping Asia—Ernesto M. Pernia and Stella LF. Alabastro,September 1997

No. 57 Challenges for Asia’s Trade and Environment—Douglas H. Brooks, January 1998

No. 58 Economic Analysis of Health Sector Projects-A Review of Issues, Methods, and Approaches—Ramesh Adhikari, Paul Gertler, and AnneliLagman, March 1999

No. 59 The Asian Crisis: An Alternate View—Rajiv Kumar and Bibek Debroy, July 1999

No. 60 Social Consequences of the Financial Crisis inAsia—James C. Knowles, Ernesto M. Pernia, and MaryRacelis, November 1999

51

No. 1 Estimates of the Total External Debt ofthe Developing Member Countries of ADB:1981-1983—I.P. David, September 1984

No. 2 Multivariate Statistical and GraphicalClassification Techniques Appliedto the Problem of Grouping Countries—I.P. David and D.S. Maligalig, March 1985

No. 3 Gross National Product (GNP) MeasurementIssues in South Pacific Developing MemberCountries of ADB—S.G. Tiwari, September 1985

No. 4 Estimates of Comparable Savings in SelectedDMCs—Hananto Sigit, December 1985

No. 5 Keeping Sample Survey Designand Analysis Simple—I.P. David, December 1985

No. 6 External Debt Situation in AsianDeveloping Countries—I.P. David and Jungsoo Lee, March 1986

No. 7 Study of GNP Measurement Issues in theSouth Pacific Developing Member Countries.Part I: Existing National Accountsof SPDMCs–Analysis of Methodologyand Application of SNA Concepts—P. Hodgkinson, October 1986

STATISTICAL REPORT SERIES (SR)

No. 8 Study of GNP Measurement Issues in the SouthPacific Developing Member Countries.Part II: Factors Affecting IntercountryComparability of Per Capita GNP—P. Hodgkinson, October 1986

No. 9 Survey of the External Debt Situationin Asian Developing Countries, 1985—Jungsoo Lee and I.P. David, April 1987

No. 10 A Survey of the External Debt Situationin Asian Developing Countries, 1986—Jungsoo Lee and I.P. David, April 1988

No. 11 Changing Pattern of Financial Flows to Asianand Pacific Developing Countries—Jungsoo Lee and I.P. David, March 1989

No. 12 The State of Agricultural Statistics inSoutheast Asia—I.P. David, March 1989

No. 13 A Survey of the External Debt Situationin Asian and Pacific Developing Countries:1987-1988—Jungsoo Lee and I.P. David, July 1989

No. 14 A Survey of the External Debt Situation inAsian and Pacific Developing Countries: 1988-1989—Jungsoo Lee, May 1990

No. 15 A Survey of the External Debt Situationin Asian and Pacific Developing Countries: 1989-1992

No. 1 Poverty in the People’s Republic of China:Recent Developments and Scopefor Bank Assistance—K.H. Moinuddin, November 1992

No. 2 The Eastern Islands of Indonesia: An Overviewof Development Needs and Potential—Brien K. Parkinson, January 1993

No. 3 Rural Institutional Finance in Bangladeshand Nepal: Review and Agenda for Reforms—A.H.M.N. Chowdhury and Marcelia C. Garcia,November 1993

No. 4 Fiscal Deficits and Current Account Imbalancesof the South Pacific Countries:A Case Study of Vanuatu—T.K. Jayaraman, December 1993

No. 5 Reforms in the Transitional Economies of Asia—Pradumna B. Rana, December 1993

No. 6 Environmental Challenges in the People’s Republicof China and Scope for Bank Assistance—Elisabetta Capannelli and Omkar L. Shrestha,December 1993

No. 7 Sustainable Development Environmentand Poverty Nexus—K.F. Jalal, December 1993

No. 8 Intermediate Services and EconomicDevelopment: The Malaysian Example—Sutanu Behuria and Rahul Khullar, May 1994

No. 9 Interest Rate Deregulation: A Brief Surveyof the Policy Issues and the Asian Experience—Carlos J. Glower, July 1994

No. 10 Some Aspects of Land Administrationin Indonesia: Implications for Bank Operations—Sutanu Behuria, July 1994

No. 11 Demographic and Socioeconomic Determinantsof Contraceptive Use among Urban Women inthe Melanesian Countries in the South Pacific:A Case Study of Port Vila Town in Vanuatu—T.K. Jayaraman, February 1995

No. 12 Managing Development throughInstitution Building— Hilton L. Root, October 1995

No. 13 Growth, Structural Change, and OptimalPoverty Interventions—Shiladitya Chatterjee, November 1995

No. 14 Private Investment and MacroeconomicEnvironment in the South Pacific IslandCountries: A Cross-Country Analysis—T.K. Jayaraman, October 1996

No. 15 The Rural-Urban Transition in Viet Nam:Some Selected Issues—Sudipto Mundle and Brian Van Arkadie, October1997

No. 16 A New Approach to Setting the FutureTransport Agenda—Roger Allport, Geoff Key, and Charles Melhuish,June 1998

No. 17 Adjustment and Distribution:The Indian Experience—Sudipto Mundle and V.B. Tulasidhar, June 1998

No. 18 Tax Reforms in Viet Nam: A Selective Analysis—Sudipto Mundle, December 1998

No. 19 Surges and Volatility of Private Capital Flows toAsian Developing Countries: Implicationsfor Multilateral Development Banks—Pradumna B. Rana, December 1998

No. 20 The Millennium Round and the Asian Economies:An Introduction—Dilip K. Das, October 1999

No. 21 Occupational Segregation and the GenderEarnings Gap—Joseph E. Zveglich, Jr. and Yana van der MeulenRodgers, December 1999

No. 22 Information Technology: Next Locomotive ofGrowth?—Dilip K. Das, June 2000

OCCASIONAL PAPERS (OP)

52

—Min Tang, June 1991No. 16 Recent Trends and Prospects of External Debt

Situation and Financial Flows to Asianand Pacific Developing Countries—Min Tang and Aludia Pardo, June 1992

No. 17 Purchasing Power Parity in Asian DevelopingCountries: A Co-Integration Test

—Min Tang and Ronald Q. Butiong, April 1994No. 18 Capital Flows to Asian and Pacific Developing

Countries: Recent Trends and Future Prospects—Min Tang and James Villafuerte, October 1995

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2. Mongolia: A Centrally Planned Economyin TransitionAsian Development Bank, 1992$15.00 (paperback)

3. Rural Poverty in Asia, Priority Issues and PolicyOptionsEdited by M.G. Quibria, 1994$25.00 (paperback)

4. Growth Triangles in Asia: A New Approachto Regional Economic CooperationEdited by Myo Thant, Min Tang, and Hiroshi Kakazu1st ed., 1994 $36.00 (hardbound)Revised ed., 1998 $55.00 (hardbound)

5. Urban Poverty in Asia: A Survey of Critical IssuesEdited by Ernesto Pernia, 1994$18.00 (paperback)

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Developing an Interregional Input–OutputTable for Cross-border Economies:

An Application toLao People’s Democratic Republic

and Thailand


July 2007

About the Paper

Benson Sim, Francisco Secretario, and Eric Suan measure the extent of economic interdependency between Mukdahan province in Thailand and Savannakhet province in Lao People’s Democratic Republic by developing an interregional input–output table using the Chenery-Moses model in conjunction with popular data reduction methods such as the simple location quotient method in the input–output tables literature.

Asian Development Bank6 ADB Avenue, Mandaluyong City1550 Metro Manila, Philippineswww.adb.org/economicsPublication Stock No. 070507ISSN 1995-2996 Printed in the Philippines

About the Asian Development Bank

ADB aims to improve the welfare of the people in the Asia and Pacific region, particularly the nearly 1.9 billion who live on less than $2 a day. Despite many success stories, the region remains home to two thirds of the world’s poor. ADB is a multilateral development finance institution owned by 67 members, 48 from the region and 19 from other parts of the globe. ADB’s vision is a region free of poverty. Its mission is to help its developing member countries reduce poverty and improve their quality of life.

ADB’s main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance.ADB’s annual lending volume is typically about $6 billion, with technical assistanceusually totaling about $180 million a year.

ADB’s headquarters is in Manila. It has 26 offices around the world and morethan 2,000 employees from over 50 countries.

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