human capital, industrial growth and resource curse gdn_valchakova

8/8/2019 Human Capital, Industrial Growth and Resource Curse GDN_Valchakova

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10th GDN Conference Natural Resources And Development

Human Capital, Industrial Growth

and Resource Curse

by Elena Suslova and Natalya Volchkova

New Economic School

February 3, 2009

Kuwait


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Motivation: empirical study of the

black box of resource curse

Resource curse well documented slower

growth of resource rich economies

Literature provide us with a number ofspeculations on the origin and propagation of

the curse

Little of empirical backup.


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Literature: are natural resources a

blessing or a curse? Channels of negative effects transmission

Dutch Disease Corden&Neary82: theoretical model of deindustrialization Sachs&Warner95, 97, 99: cross country studies revealed negative

relation between natural resource abundance and growth rates

Spatafora&Warner95, Hutchison94: time series analysis does notconfirm diagnosis

Excessive volatility of income Spatafora&Warner95: terms of trade shocks have positive effect; Ramey&Ramey95: volatility of government expenditures matter;

Political Economy

Auty01, Paldam&Svendse00: huge rents provoke rent-seeking,corruption, postponement of reforms, competitive industrialization;

Egorov, Guriev&Sonin07: less free media in oil-rich countries;

Human Capital Underdevelopment Gylfason01, Leamer et al.99: resource intense sectors absorb

national savings while creating only a few eminently qualified jobs,

thus preventing the development of innovative industries.


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Our paper :

Provides empirical study of a human capitalunderdevelopment channel of resource curse

Our result:

We find empirical support for the hypothesis that the

human capital transmission mechanisms is via thedistorting effect of resources on the distribution of countrys

human capital, namely under accumulation of country's

high skilled human capital.


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Some facts about human capital

development and natural resources

from Gylfason 2001


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Some facts about human capital

developments and natural resources

from Gylfason 2001


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How to deal with the black box?

Cross-country growth studies: omitted variables problem

endogeneity issues

failure to distinguish among possible mechanisms of

transmission Difference in differences - cross-country and cross-

industry growth - study a la Rajan&Zingales98:

fixed country and industry effects

mostly exogenous explanatory variables model the transmission mechanism


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Model: Leamer et al (1999)

Assumptions Open economy: production pattern is

determined by comparative advantage a la

Hecksher-Ohlin model Growth mechanism: capital accumulation

both physical and human

Compare the implied dynamics of human

capital accumulation between twocountries: rich in natural resources vs.poor in natural resources


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Model: Leamer et al (1999)

Capital (physical, human)

Natural

Resources

Labor

Capitalaccumula

tion

A BC

D

E

F

G

H L

M

Primitive Extraction

Capital-

intensiveExtraction

Petrochemicals

Craft

Apparel

Machinery

Capita

laccum

ula

tion

PeasantFarming

makeslabor

expensivem

akes

lab

orch

eaper


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Model results: The resource rich economy faces a trap of skilled

labor underdevelopment: physical capitalaccumulation provokes the decline in the return tolabor and subsequently to human capital whichhas depressing effect on the upper tail of humancapital distribution and prevents the developmentof new more sophisticated industries as there is noenough skilled labor

Resource rich economy needs to overcomecoordination problem with respect to development

of marginally skilled human capital in order toswitch to next product mix Warning: the story is not about the lower volume

of human capital but about the deficit of marginallyskilled human capital in resource rich economies


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Testable hypotheses:

Industries with higher skilled labor

intensity grow slowly relative to industries

less skilled labor intensive in resource rich

economies compared to resource pooreconomies

low-skilled labor intensity does not

differentiate industrial growth betweenresource rich and resource poor countries


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Hypotheses: illustration

resource richness of economy

High-Ski

lledlaborinten

sity

ofind

ustry

indA

indB

CountryH Country F

>

Low-sk

illedl

aborin

tensityofind

ustry

~difference in

growth rates (A-B)H

difference in

growth rates (A-B)F


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Estimated equation

- average annual real growth rates of sectoriin country k

- share of industry iin Value Added of manufacturing incountry kat the beginning of period

- industry iintensity with respect to low-skilled labor

- industry iintensity with respect to high-skilled labor

- resource richness of country k

Hypotheses:

10 GDN C f N l R A d D l


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Data: industrial sectors demand for

human capital Abowd et al. ( 2003) estimate the human capital index

for each of 68 millions of U.S. workers (which covers45% of U.S. labor force) that were surveyed in 1992within Longitudinal Employer - Household Dynamics

(LEHD Programs individual, employer, and employmenthistory databases).

Then each individual human capital index was placedinto the industry where the firm she employed in belongsto.

This allows constructing the comparable distribution ofthe level of human capital within U.S. industries.

Why US data?

10th GDN C f N t l R A d D l t


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Distribution of human capital within

U.S. industriesMetallurgy

10.6 10.611.2 11.4 11.1

10.39.2

8.47.9

0

2

4

6

8

10

12

1 2 3 4 5 6 7 8 9

Machinery (excl. electrical)

9.5

7.9 8.28.8

9.510.1 10.4

10.8 11.3

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8 9



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Constructing industry intensities

with respect to high skilled labor

with respect to low-skilled labor

= share of labor force in jth decile of human capital

distribution in industry i



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Measures of high- and low-skilled

intensities

M anufacturing sector

Petroleum and coal productsMachinery, except electrical

MetallurgyTransport equipment

Pa er and roducts

Manufact

PetroleumMachinery,

TextilesPrinting an

E lectric m a 10th GDN Conference Natural Resources And Development


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Data: other industrial

characteristics

Average annual real growth rates ofmanufacturing sector in 1980-2000 Nominal value added data from UNIDO

(United Nation Industrial DevelopmentOrganization) database for 3-digit ISIC codes(Rev.2)

GDP deflator obtained from WDI (World

Development Indicators) database. Share of sector in total manufacturing

value added in 1980-2000 from UNIDOdatabase.



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Data: country level raw hydrocarbon production of the economy as a

share of countrys GDP, 1980-2000

1 Japan 0

2 Singapore 03 Korea 0

4 Spain 0

5 Turkey 0

6 Austria 0

7 France 0 10th GDN Conference Natural Resources And Development


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Example

In 1980-1990

Norway: Machinery grew at a 4 percent

lower annual real rate than Metallurgy

Belgium: Machinery grew at 2 percent

higher rate than Metallurgy



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Estimation results: 1980-1990

Dependent variable: IndustVariable

Share of industry in totalmanufacturing value added, 19

Low skilled intensity * ResourResource richness

High-skilledint

en

sity

25% 75%

75

25

%

> by 0.8%

average annual real

growth in the sample is

2.2%Observations with positive growth



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Resource measure primary

export

De

Vari

SharObservations with positive growth



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10 GDN Conference Natural Resources And Development

Robustness check

Other measures of resource abundance-

oil, gas at the beginning of the period,

average over the period results hold

Period 1990-2000, oil, gas production

results hold and becomes stronger:

75%-25% growth losses =4.7% and average

annual growth =5.4%



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Conclusions

There are significant systematical losses in growthrates of industries with higher skilled-laborintensities relative to those with lower skilled-laborintensities in countries rich in natural resources

compared to resource poor countries. Low-skilled labor intensity does not differentiate

industrial growth across poor- and rich-resourcecountries.

It is consistent with the story of underaccumulation of skilled labor in resource richcountries: upper tails of human capital distributionare thinner in resource rich economies



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Policy application

One of the possible charms against theresource curse: investment in education

Leamer at al: If the model is somehow backed

up with hard evidence, the policy advice is veryclear: Governments in countries that are in astage of old product mix but close to the stageof new product mix should be making majorimprovements in their educational systems, inparticular eliminating the dumbbell educationalsystems that were economically efficient in oldproduct mix but inappropriate in new one.

human capital, industrial growth and resource curse gdn_valchakova

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