Economic History and Cliometrics Lab

Working Paper # 9

Skill Premium in Chile: Studying Skill Upgrading in the

South

FRANCISCO A. GALLEGO

This Version: May, 2010

www.ehcliolab.cl

Economic History and Cliometrics Laboratory Working Paper Series The EH Clio Lab WP series disseminates research developed by lab researchers and students quickly in order to generate comments and suggestions for revision or improvement before publication. They may have been presented at conferences or workshops already, but will not yet have been published in journals. The EH Clio Lab is a research group that applies economic tools –theory as well as quantitative tools applied in economics- to the study of economic history. The current two main research topics: (i) “The Republic in Numbers” and (ii) papers on more specific historical issues and problems, using data both from the República and other sources. The latter consists in the collection and construction of a large number of statistical series about Chile`s development process during the past two centuries. The EH Clio Lab receives funding from the Millenium Nuclei Research in Social Sciences, Planning Ministry (MIDEPLAN), Republic of Chile, (icm@mideplan.cl).

Skill Premium in Chile: Studying Skill Upgrading in the South Francisco A. Gallego Economic History and Cliometrics Lab Working Paper #9 May 2010 Abstract The evolution of the skill premium (i.e., the wage differential between skilled and unskilled workers) has interest from at least two perspectives: it is a rough measure of inequality among workers of different qualifications and provides information on the characteristics of the development process of the economy. In this paper, I investigate empirically the evolution of the skill premium in Chile over the last 40 years. After some fluctuations in the 1960s and 1970s, the skill premium increased in the 1980s and has remained roughly constant since then. The data suggest that this evolution is an outcome of a significant increase in relative demand for skilled workers in the 1980s and 1990s and a sizeable increase in the relative supply in the 1990s. Sectoral evidence shows that, after controlling for sector and time effects, (i) the relative demand increased faster in the same industries in Chile than in the US and (ii) the correlation is stronger for tradable industries and non-tradable industries that are intensive in imported capital, as expected. This result is consistent with a number of theories that link skill up- grading in developed and developing countries. To try to disentangle among these theories, I present time series evidence suggesting that, after controlling for other determinants of skill premium, not only there is a positive correlation between skill premium in Chile and in the US but also the size of the correlation is consistent with the Acemoglu (2003a) model of endogenous technological choice in which new technologies are produced in developed countries (like the US) and adopted in developing economies (like Chile). JEL Classification Number: O3, J31

Table

1:College/H

ighSchoo

lWag

ePremium

(inlogpoints)

Middle

East

EastAsia

DevelopingEurope

Latin

America

High

Income

and

North

Africa

and

Pacific

and

CentralAsia

and

theCaribbean

Mean

0.48

Mean

0.53

Mean

0.29

Mean

0.62

Mean

0.37

Median

0.48

Median

0.52

Median

0.27

Median

0.59

Median

0.36

Kuw

ait

0.23

Vietnam

0.24

Hunga

ry0.22

Peru

0.41

Italy

0.14

Egy

pt

0.39

Hon

gKon

g0.31

Yugo

slavia

0.24

Costa

Rica

0.43

Norway

0.20

Tunisia

0.40

Indon

esia

0.35

Eston

ia0.27

Hon

duras

0.47

Netherlands

0.26

Iran

0.58

Sri

Lan

ka0.35

Polan

d0.35

Dom

inican

R.

0.47

Australia

0.27

Morocco

0.79

Malaysia

0.47

RussianFed

.0.36

Ven

ezuela

0.47

Israel

0.28

Sub-Saharan

Africa

Nep

al0.49

Urugu

ay0.49

UK

0.30

Mean

0.49

Thailand

0.58

Argentina

0.52

German

y0.30

Median

0.48

China

0.61

Bolivia

0.54

Den

mark

0.30

Ethiopia

0.16

Philippines

0.63

Parag

uay

0.58

Can

ada

0.32

Zim

bab

we

0.28

Singa

pore

0.66

Ecu

ador

0.59

Belgium

0.33

Uga

nda

0.30

Korea

0.68

Nicarag

ua

0.61

Austria

0.36

Cam

eroo

n0.30

Taiwan

0.95

Brazil

0.61

Spain

0.36

Ghan

a0.44

South

Asia

Pan

ama

0.69

Finland

0.37

Sudan

0.47

Mean

0.53

Chile

0.69

Switzerlan

d0.38

BurkinaFaso

0.48

Median

0.51

Colom

bia

0.70

Greece

0.38

Sou

thAfrica

0.51

Sri

Lan

ka0.35

ElSalvador

0.70

Portuga

l0.43

Zam

bia

0.53

Nep

al0.49

Mexico

0.70

Swed

en0.46

Kenya

0.57

India

0.53

Guatem

ala

0.75

France

0.50

Coted’Ivo

ire

0.66

Pak

istan

0.77

Jamaica

1.44

USA

0.50

Tan

zania

0.69

Cyp

rus

0.61

Botsw

ana

0.96

Japan

0.66

Sou

rce:

Author’s

calculationsusingdatafrom

Contreras(2002)forChile;Autoretal.

(2005)fortheUS;andAcemoglu

(2003b),

BanerjeeandDuflo(2005),andCaselliandColeman(2006)forothercounties.

Table 2: Skill Upgrading in Chile, Sectoral Evidence

Total Between Within Within Share

(1) (2) (3) (3)/(1)

Panel A: All Sectors

1970 – 1961 0.58% 0.15% 0.44% 75.90%

1980 – 1970 0.65% 0.07% 0.58% 89.30%

1990 – 1980 1.34% 0.18% 1.17% 87.61%

2000 – 1990 0.84% 0.07% 0.77% 92.04%

Panel B: Tradable Sectors

1970 – 1961 0.13% -0.01% 0.14% 108.85%

1980 – 1970 0.64% 0.06% 0.59% 91.81%

1990 – 1980 1.98% 0.11% 1.89% 95.50%

2000 – 1990 0.36% 0.00% 0.35% 99.56%

Panel C: Non-Tradable Sectors

1970 – 1961 0.75% 0.21% 0.56% 73.85%

1980 – 1970 0.56% -0.02% 0.58% 103.68%

1990 – 1980 1.15% 0.24% 0.93% 81.00%

2000 – 1990 0.88% -0.01% 0.89% 100.91%

Table 3: Share of Developed Economies in Imports of Non-Transportation Machinery and Equip-

ment

US OECD

1962

Machinery and Equipment 50.01% 98.50%

Data Processing Machines 31.23% 99.26%

1970

Machinery and Equipment 44.68% 94.33%

Data Processing Machines 24.12% 80.21%

1980

Machinery and Equipment 38.23% 86.29%

Data Processing Machines 45.23% 91.58%

1990

Machinery and Equipment 25.23% 83.27%

Data Processing Machines 46.97% 77.64%

2000

Machinery and Equipment 38.79% 74.28%

Data Processing Machines 55.91% 67.56%

Sources: Author’s calculations using Feenstra et al. (2005)

Table 4: Sectoral Evidence, including the Wage Bill in the US

Panel A

Sample: Full Full Full Non-tradable

Sample Sample Sample Sectors

(1) (2) (3) (4)

Skilled Labor Share in the US 1.584** 0.643 1.272* 0.643

(0.738) (0.833) (0.714) (0.912)

Skilled Labor Share in the US 1.740 3.012***

× Dummy for AMIC (1.533) (0.946)

Skilled Labor Share in the US 0.828

× Dummy for tradable sector (2.001)

Year Dummies Yes Yes Yes Yes

Sector Dummies Yes Yes Yes Yes

Observations 100 97 100 52

R2 0.780 0.783 0.788 0.854

Panel B

Sample: Full Full Full Tradable

Sample Sample Sample Sectors

(1) (2) (3) (4)

Skilled Labor Share in the US 1.508* 0.066 0.965 1.807

(0.835) (0.653) (0.789) (2.419)

Skilled Labor Share in the US 2.084

× Dummy for AMIC (1.912)

Skilled Labor Share in the US 0.793

× Dummy for tradable sector (2.461)

FDI stock 0.003 0.009 0.005 -0.005

(0.004) (0.005) (0.004) (0.010)

FDI stock -0.012

× Dummy for AMIC (0.009)

FDI stock -0.011

× Dummy for tradable sector (0.010)

Tariffs -0.103

(0.370)

Year Dummies Yes Yes Yes Yes

Sector Dummies Yes Yes Yes Yes

Observations 94 92 94 45

R2 0.770 0.793 0.789 0.591

Notes: Standard errors clustered at the sector level in parenthesis. Significance level:

*** p<0.01, ** p<0.05, * p<0.1. Dummy for AMIC is a dummy variable equals to

1 when a country is above median of imported capital (AMIC). Tariffs is equal to

Tariff ×1,000.

Table 5: Time-Series Evidence: Estimation in Levels

Dependent variable: Relative Demand

Variable (1) (2) (3)

Wage Premium in the US 2.081 1.874

(0.828) (0.750)

Openness in the US 1.331 1.353

(0.421) (0.570)

Output Gap 0.674 0.454 0.563

(0.458) (0.553) (0.465)

Real Minimum Wage -0.294 -0.346 -0.499

(0.199) (0.198) (0.220)

Structural Reforms 0.371 0.243 0.941

(0.465) (0.330) (0.401)

Price of unskilled goods -0.275 -0.254 -0.329

(0.186) (0.146) (0.178)

Trend 0.001 0.019 -0.051

(0.012) (0.876) (0.023)

N 38 40 38

R2 0.853 0.876 0.883

ADF-test -4.629 -4.604 -5.677

Notes: Newey-West HAC standard errors in parenthesis.

Table 6: Time-Series Evidence: Estimation in First Differences

Dependent variable: Relative Demand

Variable (1) (2) (3)

Wage Premium in the US 2.397 2.142

(0.877) (0.062)

Openness in the US 1.597 1.381

(0.447) (0.590)

Output Gap 0.721 0.438 0.538

(0.560) (0.550) (0.443)

Real Minimum Wage -0.345 -0.388 -0.531

(0.250) (0.213) (0.233)

Structural Reforms 0.478 0.390 1.036

(0.370) (0.338) (0.405)

Price of unskilled goods -0.317 -0.245 -0.365

(0.207) (0.219) (0.179)

Trend -0.006 -0.034 -0.058

(0.013) (0.017) (0.024)

N 38 40 37

R2 0.252 0.293 0.482

Notes: Newey-West HAC standard errors in parenthesis.

Figure 1: The Wage Premium in Chile

0.4

0.6

0.8

1.0

1.2

1.4

1.6

60 65 70 75 80 85 90 95 00

Figure 2: Relative Supply in Chile

0.1

0.2

0.3

0.4

0.5

60 65 70 75 80 85 90 95 00

Figure 3: Relative Demand in Chile

0.0

0.5

1.0

1.5

2.0

60 65 70 75 80 85 90 95 00

Figure 4: Equipment Capital per Skilled Labor

2

4

6

8

10

12

14

65 70 75 80 85 90 95 00

Ass. 1: Quality of K approx. Ah Ass 2: Quality of K in the US

Figure 5: Decomposing Wage Premium Growth, by Decade Panel A: Assumption 1: Quality of Capital equal to Ah

-30%

-20%

-10%

0%

10%

20%

30%

40%

1970s 1980s 1990s

capital supply demand wage premium

Panel B: Assumption 2: Quality of Capital in the US

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

1970s 1980s 1990s

capital supply demand wage premium

Figure 6: Skill Premium in Chile and the US

0.6

0.8

1.0

1.2

1.4

1.6

0.35

0.40

0.45

0.50

0.55

0.60

0.65

65 70 75 80 85 90 95 00

Skill Premium in Chile Skill Premium in the US

0.6

0.8

1.0

1.2

1.4

1.6

2.2

2.4

2.6

2.8

3.0

3.2

3.4

65 70 75 80 85 90 95 00

Skill Premium in Chile Openness in the US

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.0

0.4

0.8

1.2

1.6

2.0

65 70 75 80 85 90 95 00

Skill Premium in the US Relative Demand in Chile

2.2

2.4

2.6

2.8

3.0

3.2

3.4

0.0

0.4

0.8

1.2

1.6

2.0

65 70 75 80 85 90 95 00

Openness in the US Relative Demand in Chile

Table A.1: Two-Digit Industries

Manufacture of food products, beverages, and tobacco products

Manufacture of textiles, dressing, and leather products

Manufacture of wood and wood products

Manufacture of paper and paper products, publishing and printing

Manufacture of chemicals and chemical products, plastics and rubber products, petroleum products

Manufacture of other non-metallic mineral products

Manufacture of basic metals

Manufacture of fabricated metal products, machinery and equipment

Other manufacturing industries

Construction

Wholesale and retail trade

Hotels and restaurants

Financial intermediation and real estate

Personal service activities

Education and health services

Sanitation services

Other community and social services

Transportation

Communications

Electricity, gas, steam and hot water supply

Collection, purification and distribution of water

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