Testing for the Directodn of ExportsIndia's Exports of Manufactures in the IW -
Ashok Khanna SWP538
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WORLD BANK STAFF WORKING PAPERSNumber 538
Testing for the Direction of ExportsIndia's Exports of Manufactures in the 1970s
Ashok Khanna
The World BankWashington, D.C., U.S.A.
Copyright (© 1982The International Bank for Reconstructionand Development / THE WORLD BANK1818 H Street, N.W.Washington, D.C. 20433, U.S.A.
All rights reservedManufactured in the United States of America
This is a working document published informally by The World Bank. To
present the results of research with the least possible delay, the typescript has
not been prepared in accordance with the procedures appropriate to formal
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should not be attributed to The World Bank, to its affiliated organizations, or to
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The full range of The World Bank publications is described in the Catalog of
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in World Bank Research Program: Abstracts of Current Studies. Both booklets are
updated annually; the most recent edition of each is available without charge
from the Publications Distribution Unit of the Bank in Washington or from the
European Office of the Bank, 66, avenue d'Iena, 75116 Paris, France.
Ashok Khanna is assistant professor of international business at New York
University and a consultant to the Economic Analysis and Projections
Department of The World Bank.
ABSTRACT
The main hypothesis tested here is that the exports of a developingcountry, with an advanced manufacturing sector, will differ amongdestinations: the capital intensity of exports will be greater to the morelabor abundant destinations, and the labor intensity of exports will begreater to the more capital abundant destinations. India's exports ofmanufactures for 1973 and 1978 were used for the analysis. The resultsgenerally corroborate the above hypothesis and also indicate that thedirection of exports is sustained over time.
The economies of many developing countries, including India, deviatefrom efficiency conditions. Protection and a higher-than-efficient wage forunskilled labor would tend to bias the structure of production in an economytowards capital intensity and adversely affect the comparative advantage ofcommodities produced under these distorted conditions. Indian data were usedto analyze the impact of protection and labor-market distortions on thestructure of production and relative comparative advantage of commodities.The results indicate that protection and higher-than-efficient wages do biasthe structure of production toward capital intensity and have a negativeimpact on the comparative advantage of commodities. However, although thestructure of production is affected, the direction of exports is not; thevalidity of the main hypothesis is unaffected by the existence of thesedistortions in the economy.
ACKNOWLEDGMENTS
I wish to thank Larry White, Tom Pugel, my colleagues at New YorkUniversity, and Oli Havrylyshyn of the World Bank for their helpfulcomments.
I am grateful for the data supplied by the International Trade andCapital Flows Division and for the support of the Division's project on TradeAmong Developing Countries [RPO 672-321.
TABLE OF CONTENTS
Page
CHAPTER I Introduction 1
CHAPTER II Empirical Evidence 3
CHAPTER III Theory 5
CHAPTER IV Export Patterns 8
CHAPTER V Protection and Labor Market Distortions 19
CHAPTER VI Comparative Advantage, Protection, and Labor Market
Distortions 24
CHAPTER VII Policy Implications 27
CHAPTER VIII Conclusions 29
Appendix I Data Sources 31
Appendix II Glossary of Symbols and Variables 34
Appendix III Destination countries 36
Bibliography 37
LIST OF TABLES
Page
Table 1 Direct factor content 11
Table 2 Direct plus indirect factor content 12
Table 3 Relative comparative advantage 17
Table 4 Protection 20
Table 5 Labor market distortions 23
Table 6 Comparative advantage, protection, and labormarket distortions 25
CHAPTER I: INTRODUCTION
This study was motivated by conversations with Indian businessmen who
had noticed a pattern in their export of manufactures - they were shipping
"sophisticated" products to other developing countries and the Middle East,
and "simple" products to the developed countries. The Indian press
corroborated the businessmen's observation by emphasizing the sale of turnkey
factories to the Middle East and Africa, and garments to developed
countries. Clearly, if there is a systematic relationship between the
commodity characteristics of exports of manufactures and destination
countries, it would be of considerable importance for export promotion policy;
these policies would be enhanced by becoming commodity and market specific
instead of just focusing on commodities. Also, presently, there is no
recognition given to the factor intensity of commodities when export promotion
policies are designed; this has implications for economywide efficiency of
resource allocation. However, the Tandon Committee Report on India's Export
Strategy in the 1980's, India's latest effort at devising a national export
plan, made no note of either the directionality of India's exports of
manufactures, or the factor characteristics of commodities, in its policy
recommendations.
Other researchers have also observed a directionality in exports.
The exports of developing countries followed a pattern - they exported their
capital intensive products to other developing countries and their labor
intensive products to developed countries. However, these researchers merely
described the phenomenon, they provided no theoretical framework within which
their observation could be interpreted. It was not possible to answer
questions about the cause of the observed pattern of exports, their future
trend, or whether, in a normative sense, the pattern was desirable. Also, the
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research did not posit a statistical relationship between commodity
characteristics and destination markets. For both these reasons it was not
possible to draw any policy implications from their work.
It turned out that A. Krueger (1977) and A. Deardorff (1979) had
recently extended the Heckscher-Ohlin-Samuelson factor endowment explanation
for trade, to a multicommodity, multicountry framework which is appropriate
for this analysis. A relationship between the factor intensity of an exported
commodity and destination market factor endowments can be derived from this
framework; this relationship is amenable to a statistical test thereby
allowing answers to the policy questions posed above to flow from the
analysis. Further, A. Krueger's (1977) work on the impact of protection, and
labor and capital market distortions on the structure of production and trade
generated interesting policy questions as by-products - in what direction do
protection and labor market distortions make an impact on the structure of
production; how does this affect the pattern of exports posited above; how is
the export performance of commodities affected; is it possible to design
policies to compensate for these distortions; is it possible to figure out
what the structure of production would be under efficient allocation, and
therefore what should be the structure of production 5 or 10 years hence.
The pertinent previous research is briefly reviewed in Chapter II and
Krueger and Deardorff s theory summarized in Chapter III. Chapters IV to VI
contain the results of the analysis for India: export patterns, impact of
goods and factor market distortions on production, and impact of goods and
factor market distortions on comparative advantage. Some policy implications
are derived in Chapter VII and conclusions presented in Chapter VIII.
-3-
CHAPTER II: EMPIRICAL EVIDENCE
Several researchers have noticed that the commodity characteristics
of a developing country's exports of manufactures differ by destination;
exports are labor intensive "upstream" to more developed countries, and
capital and skill intensive "downstream" to less developed countries. Heller
(1976) calculated the capital and skill intensity of Japan's exports to
developed and developing countries for the period 1956-1968. He concluded
that Japan's exports to other developing countries were more capital and skill
intensive than Japan's exports to developed countries.
Heller's conclusions are generally corroborated by other studies
conducted in recent years. Diaz-Alejandro (1974), in analyzing the export
expansion of some Latin American countries, notes "that a significant
difference appears to exist between manufactured exports going to other Latin
American countries and those going to the rest of the world. The former tend
to be more *'sophisticated" but also, alas, more capital and import
intensive." Krueger (1978) compared the labor content of some developing
countries exports to developed countries, and other developing countries, with
the conclusion that "with the exception of Thailand, all the countries ...
were found to have remarkably different products, and therefore factor
proportions, in their trade with developed countries than with other
developing countries. Uruguay, for example, exports products to developing
countries that are less labor using than even the production competing with
imports from developed countries. Likewise, Chile's exports to developed
countries require almost 40 more labor per DVA (domestic value added) than
her total exports." In other words, exports to developing countries are more
capital intensive than exports to developed countries.
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Tyler's (1972) analysis of the skill content of Brazil's exports,
found them to be more skill intensive to developing countries than to
developed countries. And Amsden (1980), in her study of ten developing
countries exports finds that "skill intensity ... is both positive and highly
significant for most exporters" in explaining the share of commodities
exported to developing countries. Lately, the results of Wolf and
Havrylyshyn's (1981) analysis of the direct factor content of manufactured
exports of advanced developing countries "clearly confirm the expectation that
trade among developing countries is more capital and skill intensive than
exports of developing countries to industrialized countries."
These studies, although of considerable descriptive value, lack an
explicit theoretical framework, and are not designed in a manner that allows
statistical inferences to be made. These shortcomings make it difficult to
draw reliable policy conclusions from their results. These inadequacies will
be addressed in this analysis.
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CHAPTER III: THEORY
A. Krueger (1977) and A. Deardorff-s (1979) extention of the standard
two country, two commodity, two factor Heckscher-Ohlin-Samuelson [HOS] model
to a multicountry, multicommodity, two factor framework is particularly
pertinent for this analysis. After stating its assumptions, the model will be
outlined and a pattern of production and trade derived. Then, the impact of
distortions in the goods and factor markets on that pattern of production and
trade will be discussed.
(a) Assumptions
All the standard HOS assumptions and no factor price equalization
between countries, apply. What this means is that perfectly competitive
conditions prevail, there are universal prices, no transport costs, and all
the countries have access to the same technology menu. The important
difference between countries, that determines their pattern of production and
trade, is in their factor endowments.
(b) Pattern of Production
Given the assumptions above, it is possible to rank countries on the
basis of their factor endowments, and commodities on the basis of factor
intensity; countries will specialize in the production of commodities
according to their relative factor endowments. Production in the most labor
abundant country will be concentrated on the most labor intensive commodities,
and production in the most capital abundant country will include production of
the most capital intensive goods, with countries in between specializing in
the production of commodities with factor intensities appropriate to their
factor endowments. 1/ Countries will rely on trade to provide commodities
that they do not produce.
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(c) Pattern of Trade
The pattern of trade will differ between countries on two sides of a
country's factor endowment. Any country, not at the extremes of the factor
endowment ranking, will import commodities that are more capital intensive
than its own production choice from countries with larger capital/labor
endowments. The same country will also import commodities that are more labor
intensive than its own production choice from other countries with smaller
capital/labor endowments.
A country s exports will differ among destinations; the capital
intensity of exports will be greater to the more labor abundant destinations,
and the labor intensity of exports will be greater to the more capital
abundant destinations. 2/ This directionality of exports has obvious
implications for export promotion policies and is the basis of hypotheses
tested in this paper.
(d) Distortions in the Goods and Factor Markets
In most developed countries markets function fairly efficiently so
the Krueger-Deardorff version of the HOS model outlined above can be tested by
analyzing the production and trade of those countries. However, in many
developing countries there are significant deviations from efficiency
conditions that could alter their structure of production and trade such that
it may not conform to the specialization patterns set forth above. The
deviations fall into two categories: first, distortions in the goods markets
because of protection, subsidies, and taxes resulting in a divergence of
domestic from international prices and second, distortions in the factor
markets resulting in wage and interest rates that do not reflect the
opportunity costs of employing labor and capital respectively. It turns out
-7-
that the analysis of trade patterns is unaffected by the existence of
distortions in the goods and factor markets with the notable exceptions of
(a) taxes and subsidies to production and trade and (b) inter-industry factor
price differentials. Where these two distortive situations exist, anything
can happen, and production and trade may bear no relationship to that which
would have occurred under an efficient allocation regime. 3/
-8-
CHAPTER IV: EXPORT PATTERNS
The empirical evidence and theory presented above suggest hypotheses
about a country's pattern of exports. These hypotheses are specified and
tested in this Chapter. India's exports of manufactures for 1973 and 1978 are
used as the data for the tests (1978 was the most recent year for which trade
data were available).
The general hypothesis is that India's exports of manufactures will
have different commodity characteristics according to their destination:
countries that have a relatively greater capital/labor endowment will receive
relatively higher labor content and relatively more of the labor intensive
goods; countries that have a relatively smaller capital/labor endowment will
receive relatively higher capital content and relatively more of the capital
intensive commodities.
There are two alternative interpretations of the HOS theory. The
factor content version holds that a country will be a net exporter of its
abundant factors embodied in traded goods; the factor content - labor and
capital - of trade has to be analyzed. The commodity version states that a
country exports those commodities that intensively use the country's
relatively abundant factors. Theoretically, the factor content version is
considered to be the more robust, 4/ however, both versions are tested here.
(a) Factor Content
Factor content can be measured as just the direct factor content of
exports or, direct plus indirect factor content of exports. The models for
these two measures will be stated separately and the statistical tests
specified later because they are the same for both measures.
-9-
Direct factor content
[D] [X = [F whered3x7 6 d7 6x50 d3x5O
Dd = A direct coefficient matrix that measures the physicalcapital, human capital, and labor content of value added,expressed as a proportion of total output for 76 commoditygroups.
Xd = India's ex orts of 76 commodities to 50 destinations for1973 and 178.
Fd = The direct physical capital, human capital, and laborcontent of India's exports of manufactures to 55destinations.
Direct plus indirect factor content
-1[Dt] (I-A] [X = [Ft] where
3x60 60x60 60x50 3x50
Dt A direct coefficient matrix that measures the physicalcapital, human capital, and labor content of value added,expressed as a proportion of total output for 60 commoditygroups.
I = Is a 60x60 identity matrix.
A = Is a 60x60 input-output transactions matrix for the Indianeconomy for 1973.
xt = India's exports of 60 commodity groups to 50 destinationsfor 1973 and 1978.
Ft The direct plus indirect physical capital, human capitaland labor content of India's exports of manufactures to todestinations.
Statistical Tests
The following relationships will be tested for significance:
dCi =j il il ij i =1 3
j = 1...50
Cij i2 +i 2Eij where
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Cd Are the direct factor content ratios defined J=1...3. 3respectively, as physical capital/labor (k/1), humancapital/labor (h/i), physical plus human capital/labor(k+h/i), of India's exports to destination "j".
Cti Are the direct plus indirect factor content ratios defined
as in cd above.ij
Ei = Are the factor endowment ratios defined i=i,...3respectively, as physical capital/labor (K/L), humancapital (H), physical capital/labor and human capital(K/L, H), of destination country j".
Results
A series of regressions were run using ratios of factor content of
India's exports of manufactures, in 1973 and 1978, to 50 destinations as the
dependent variables and the destination country endowments as the explanatory
variables. The factor content ratios were defined as physical capital/labor,
human capital/labor, and physical plus human capital/labor; these definitions
of capital/labor cover the two possibilities of human capital being a
complement to physical capital and of human capital being a substitute.
Explanatory variables were defined in concordance with the factor content
ratio definition - where the physical capital/labor factor content ratio was
used as the dependent variable, physical capital/labor endowment was used as
the explanatory variable, etc. The data for 1973 and 1978 were also pooled
and the same regressions run to see whether there had been a structural change
in the estimated relationships between the two periods.
The results are presented in Tables 1 and 2. As can be seen the
signs of all the estimated coefficients are, as expected, consistently
negative for both years, individually and pooled, for direct and direct plus
indirect factor content, and whether one explanatory variable was used or
two. Of the twelve equations where only one explanatory variable was used, in
Table 1: DIRECT FACTOR CONTENT
Country Endowments
PhysicalDependent Variable Constant Capital/Labor- Human Capital R2 F
PhysicalExport-Capital/Labor 1973 4.110 -.146 .267 17.48+
(.035)
Export " " 1978 4.215 -.157 .317 22.23+(.033)
Export " " Pooled 4.158 --.151 .293 40.60+(.024)
HumanExport-Capital/Labor 1973 3.337 -.009 .083 4.359k
(.004)
Export " 1978 3.726 -.014 .198 11.87+(.004)
Export " Pooled 3.531 -.012 .135 15.24+(.003)
Physical PlusExport-Human Capital/Labor 1973 7.333 -.234 -.004 .246 7.68+
(.079) (.011)
Export " 1978 8.033 :-.223 -.012 .327 11.42+(.073) (.011)
.Export Pooled 7.689 -.226 -.008 .285 19.30+(.052) (.007)
* = Significant at the 5% level
+ Significant at the 1% level
Table 2: DIRECT PLUS INDIRECT FACTOR CONTENT
Country EndowmentsPhysical
Dependent Variable Constant Capital/Labor Human Capital R2 F
PhysicalExport-Capital/Labor 1973 4.023 -. 059 .123 6.7 e
(.023)
Export 1978 4.393 -. 071 .210 12.73+(.020)
Export " Pooled 4.187 -. 060 .134 15.13+(.015)
HumanExport-Capital/Labor 1973 3.145 -. 004 .100 5.33t
(.002)
Export 1978 3.378 -. 006 .161 9.19+(.002)
Export Pooled 3.262 -. 005 .124 13.93+(.001)
Physical PlusExport-Human Capital/Labor 1973 7.230 -. 079 -. 004 .154 4.29*
(.042) (.006)
Export " 1978 7.932 -. 087 -. 007 .254 8.00+(.038) (.006)
Export Pooled 7.610 -. 072 -. 007 .175 10.31+(.029) (.004)
* 5 Significant at the 5% level
+ = Significant at the 1% level
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all cases the coefficient is significantly different from zero at either the
5% or 1% level of significance. In the six equations using two explanatory
variables the significance level of the individual estimated coefficients
drops, even though the F statistic indicates that the total estimation is
significant at the 5% or 1% level. This relatively worse performance is
probably due to some collinearity among the two explanatory variables; the
standard errors of the estimated coefficients do increase in the two
explanatory variables cases over the one explanatory variable cases, and the
correlation coefficient between the two explanatory variables is significant
at the 1% level.
The magnitude of the estimated coefficients change between 1973 and
1978 in a consistent direction in every regression. A Chow test was used to
determine if there had been a structural change in the estimated coefficients
between the two years. The test indicated that there was no structural change
in the estimated relationship between the 1973 and 1978; the models are robust
for that period.
Other minor aspects of the results worth noting are first, that the
results for 1978 are consistently better than for 1973, and the results of the
pooled estimation are even better than those for 1978. The pooled estimates
are the best because of the increased degrees of freedom but there is no
obvious reason for the improvement of the 1978 results over 1973. Second, for
both analyses, direct and direct plus indirect, physical capital endowment is
the better explanatory variable. This is probably because physical capital
endowments were calculated for all countries using the same methodology and
for the same time periods, whereas the human capital endowments were obtained
from surveys taken at various times, and the same human capital endowments were
assumed for the 1973 and 1978 analyses; the physical capital endowment data
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are probably more reliable than the human capital endowments. Third, all of
the regressions in Tables 1 and 2 were tried in log-linear form to test for
one kind of heteroscedasticity. The results were not markedly different from
those presented in Tables 1 and 2 indicating that heteroscedasticity, at least
due to scale differences, is not a significant problem.
Conclusion
The results strongly suggest that the hypothesis as stated cannot be
rejected even though the explanatory variables do not explain much of the
variation in the dependent variable. It is very likely that there is a inverse
relationship between the capital/labor ratio of factor content of India's
exports of manufactures, and the destination country's capital/labor factor
endowment; this relationship was robust during the 1970's.
The direct factor content results are more reliable for two
reasons. First, for a developing country such as India, direct factor content
is a more appropriate measure than direct plus indirect factor content because
the latter does not incorporate non-competing imported inputs that are
included in exports; the direct factor content measure treats all inputs as
being internationally traded and therefore not relevant for consideration in
estimating trade in factor services of any particular country. 5/ Second,
direct coefficients for agriculture, mining, and service sectors were not
available, thus the direct plus indirect coefficients potentially suffer from
a bias in measurement. -
(b) Commodity
The commodity version will be tested by estimating the following
relationships and examining them for significance. The first stage of the
test equations estimates the relationship between capital intensity of a
commodity and its relative comparative advantage in each destination country;
the estimated coefficients are dependent variables in the second stage with
destination country endowments as the explanatory variables. The linking of
factor intensity of commodities and factor endowment of countries via the
relative comparative advantage ratio posits a test of the general hypothesis
stated above.
Statistical Tests
l(a) log Rij = log ac+ B log (k/l)i for each 'J'
(b) ;= a+b(K/L)
2(a) log Rij = log a; + B log (h/l)i for each 'J'
(b) B = a+b(H)-
3(a) log Rij = log a + B log (k+h/l)i for each 'j'
(b) S = a+b (K/L, H) where
ij w~ j
iR =i / Nj where
Xij India's exports of product 'i' to country ',
Wi;= World's exports of product 'i' to country j.
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(k/l)i, (h/l)i, (k+h/l)i Physical capital/labor, human capital/labor, physical plus human capital/labor ratios for product i".
(K/L)j, (H)j, (K/L, Hj) = Physical capital/labor, human capital,physical capital/labor and human capitalendowment ratios for country ;j.
RCA = Rij, the Relative Comparative Advantage ratio
Results
The results are presented in Table 3. Of the eight possible
estimated coefficients, seven have the expected negative sign and one has a
positive sign; in most of the cases the coefficients were different from zero
at the 1% level of significance. Among the explanatory variables, physical
capital performed better, probably for the reasons stated earlier. As with
the factor content analysis the proportion of variation in the dependent
variable explained by the explanatory variables is not very great but physical
capital explained more of the variation than did human capital. There is no
obvious pattern in the estimates for 1973 as compared with 1978.
Conclusion
These results are supportive of the hypothesis but not quite as
supportive as the factor content analysis. This may partly be explained by
problems with the RCA ratio, 7/ and in the coefficients used as dependent
variables in the second stage. 8 It is worth remembering that the commodity
interpretation of HOS is not theoretically as strong as the factor content
interpretation; these results should be weighted accordingly.
Table 3: RELATIVE COMPARATIVE ADVANTAGE
Dependent Variable PhysicalConstant Capital/Labor Human Capital R2 F
1) Physical Capital Intensity:RCA Coefficient 1973 -.269 -.071 .226 14.04+
(.019)
1978 -.247 -.058 .210 12.78+(.016)
2) Human Capital Intensity:RCA Coefficient 1973 .797 -.012 .179 10.50+
(.004)
1978 .703 -.010 .192 11.40+(.003)
3) Physical plus Human CapitalIntensity:RCA coefficient 1973 -.230 -.109 .001 .283 9.26+
(.030) (.004)1978 -.025 -.074 -.002 .275 8.92+
(.024) (.004)
* = Significant at the 5% level
+ = Significant at the 1% level
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(c) Conclusions
The overall conclusion for the test of the hypothesis about trade
patterns is that, although the explanatory variables did not explain much of
the variation in.the,dependent variable,..virtually all the signs of the
estimated coefficients were negative as expected and in almost all cases were
significantly different from zero at the 5% or 1% levels. The results
strongly suggest that the hypothesis cannot be rejected and the probability is
high that the relationship specified in the hypothesis is valid. The results
for the factor content analysis were more robust than those for the commodity
analysis; this is probably because of the greater disaggregation of RCA ratios
and also perhaps due to an inadequate estimation technique. The policy
implications of these results will be discussed in the last chapter.
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CHAPTER V: PROTECTION AND LABOR MARKET DISTORTIONS
(a) Protection
The Indian economy is quite heavily protected so some impact on the
structure of production is to be expected. The theory outlined above suggests
that India, being a relatively labor abundant country, would tend to protect
its capital intensive industries; the structure of production in India will be
more capital intensive than under an efficient allocation. However, if the
relationship between protection and capital intensity of industries is
systematic, then the pattern of trade outlined above should not be affected;
tests of the directionality of exports will be credible in spite of
protection. 2/ Indeed, if the protected commodities are given subsidies thatenable them to be exported, then our theory predicts that these subsidies will
reinforce the trade pattern yielded under an efficient allocation; India will
have a yet greater tendency to export capital intensive goods to countries
that are relatively labor abundant.
Statistical Test
yj = a + ixi i = 1...3j = 1...35 where
Yi = Effective protection rate for commodity j .
Xij = Capital intensity of commodity j , defined k/l, h/i,k+h/l as above for i = 1.. .3 respectively.
Results
The results are presented in Table 4. The sign of the coefficients
of all the capital intensity definitions used as explanatory variables are
positive as expected, but only one of these coefficients is significantly
different from zero at the 5% level of significance; also, the explanatory
variables do not explain much of the variation in the dependent variable.
Table 4: PROTECTION
Indian Industry CoefficientsPhysical Human Physical Plus
Dependent Variable Constant Capital/Labor Capital Labor Human Capital/Labor R2 F
Effective Protection Rate 121.770 9.381 .118 4.159(4.600)
136.189 14.435 .026 .819
(15.954)115.517 6.906 .099 3.421#
(3.733)
= Significant at the 10% level r
* = Significant at the 5% level
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Conclusions
Although these results do not indicate rejection of a systematic
relationship between protection and capital intensity of industries in India,
they do not give strong support to it either.
(b) Labor Market Distortion
Because of a series of government regulations and trade union
activities, the wage structure in India is distorted in the direction of being
higher than under efficient allocation. This distortion will make the
production and trade bundle of India more capital intensive than under
efficient allocation and again, the theory used in this study predicts that
the trade pattern yielded by an efficient allocation of resources will be
reinforced. 11/
Statistical Test
Yij = a + ad i = 1...3 wherej = 1.. .76
Yij = Capital intensity of industry 'J, defined k/l, h/l, k+h/l as abovefor i=1...3 respectively
dj = Labor market distortion in industry 'j', defined as
d- where
Ni = Number of workers in industry 'j'.
Wj = Average wage of a worker in industry 'j;.
W* = Minimum average wage of a worker among all industries.
Vj = Wage value added in industry 'j .
-22-
Results
The results are presented on Table 5. There is, as expected, a
strong positive relationship between the capital intensity of an industry and
the labor market distortion in that industry; all the coefficients are
different from zero at the 1% level of significance.
Conclusions
There is strong evidence that labor market distortions are positively
related to the capital intensity of Indian industries; these industries are
clearly more capital intensive than they would be under an efficient
allocation.
(c) Conclusions
There is some evidence that protection, and strong evidence that
labor market distortions, result in Indian industries being more capital
intensive than under an efficient allocation. However, although the structure
of production is affected, the pattern of exports is not. Indeed, if export
subsidies are given to these distorted industries, it is possible that the
trade pattern yielded under efficient allocation will be reinforced. The
policy implications of these results will be discussed in the last chapter.
Table 5: LABOR MARKET DISTORTIONS
Dependent Variable Constant Labor Market 2Indian Industry Factor Distortions R FIntensities Defined As
Physical Capital/Labor -1.843 3.608 .452 64.314+(.450)
Human Capital/Labor .175 1.370 .932 1066.250+(.042)
Physical plus Human Capital/Labor -1.668 4.978 .589 111.818+(.471)
+ = Significant at the 1% level
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CHAPTER VI: COMPARATIVE ADVANTAGE, PROTECTION, AND LABOR MARKET DISTORTIONS
Theoretically, there is a relationship between comparative advantage
of an exported commodity, relative to total exports of manufactures, and
protection and labor market distortions. Protected commodities can only be
exported if they are subsidized; they will not enjoy a relative comparative
advantage among India's exports. A higher wage than is efficient will result
in the production of commodities that are more capital intensive than is
appropriate for India's relative position in the factor endowment ranking,
these commodities will also not enjoy a relative comparative advantage among
India's exports.
Statistical Test
RI = ai + blPi + b2Li where
_* ijxij
i ij
Xij India's exports of commodity 'i' to country 'j'.
Wij = World's exports of commodity 'i' to country 'j'.
Pi = India's effective protection rate for commodity 'i'.
Li = Labor market distortion, as defined above, in industry 'i'.
Results
The results are presented in Table 6. The signs of the coefficients
are consistently negative as expected but none of them is different from zero
at the 5% significance level. There is some evidence that protection and
labor market distortions have a negative impact on the relative comparative
advantage of a commodity, but this evidence is not particularly strong.
Table 6: COMPARATIVE ADVANTAGE, PROTECTION, AND LABOR MARKET DISTORTIONS
DistortionsDependent Variable Constant Effective Protection Rate Labor Market Distortion R2 F
Relative ComparativeAdvantage Ratio 1973 1.872 -. 002 .006 .196
(.004)
1978 1.527 -. 001 .005 .142(.003)
Relative ComparativeAdvantage Ratio 1973 2.844 -. 606 .042 1.313
(.529)
1978 2.168 -. 385 .039 1.211(.350)
Relative ComparativeAdvantage Ratio 1973 2.987 -. 001 -. 582 .044 .668
(.004) (.545)
1978 2.241 -. 001 -. 373 .040 .605(.003) (.361)
-26-
Conclusions
Effective protection and labor market distortions do have a weak
negative impact on the relative comparative advantage of a commodity. It is
possible that the negative impact of these distortions is weakened by the
existence of subsidies. However, a glance at the cash subsidies schedule for
exports for 1980 suggests that they vary from 5% to 15%, but are mostly around
10%; this level of subsidy is unlikely to weaken the impact of effective
protection rates that are frequently over 100%, and labor market distortions
that are quite severe. The Indian government's contention that cash subsidies
are essentially to compensate for internal taxes appears to be true.
Since India is often quoted as the example of an inefficient economy
riddled with distortions, the relatively weak negative impact of distortions
on relative comparative advantage is surprising. A possible explanation is
that Indian exporters are selling at internationally competitive prices that
are below their full cost; as long as the export price plus any subsidy is
above the variable cost of a commodity, the exporter earns a contribution to
overheads. This business practice is quite normal when there is idle
capacity, and there has certainly been idle capacity in many industries in
India during the 1973-78 period.
-27-
CHAPTER VII: POLICY IMPLICATIONS
There are policy implications that can be drawn from this study
immediately, and there are others that will require further work. The
immediate policy implications are first, this study provides a focus for the
work of India's export promotion agencies (Export Promotion Councils, Trade
Development Authority, Institute of Foreign Trade, etc.); India should be
promoting the export of its capital intensive manufactured goods in developing
countries and its labor intensive manufactures in developed countries. For
instance, if engineering goods are capital intensive, then Chicago is not an
efficient location for India's Engineering Export Promotion Council; rather
the same. monies would be better spent at a Middle East or North African
location. The-Tandon Committee on India's Export Strategy in the 1980's
suggested a new export overseer organization under a Secretary, Exports
Department, that will design and help implement, a National Export Plan. The
Committee suggested that the work of the Exports Department be divided into
about io industry divisions. This study indicates that the Exports Department
should consider a matrix type of organization where there is responsibility
for markets on the one hand, and industries on the other. Exports policies
can no longer be just commodity specific, they have to address the
directionality of exports.
Second, the Tandon Committee felt the "need to develop market-wise
data to develop a market-based approach....each market should be analyzed for
the range of products that India can supply competitively." The type of
information needed for such an anlaysis is similar to that used in this study.
Historical data on market share by commodity, by destination, and data for
relative comparative advantage of each of 76 commodities across destinations
are available; all of these data can be related to the industry
-28-
characteristics of the 76 cqmmodities. This information can be immediately
used to focus the element of the Cash Compensatory Support given on the
"infant export industry" argument. Markets where India should enjoy a
comparative advantage can be identified and subsidized; the subsidy should be
commodity and market specific rather than just commodity specific.
Although this study has broken ground for other areas of policy more
work is needed before any implications can be drawn. The first such area is
the relationship between protection and factor market distortions, structure
of production, and export performance. Effective protection data are needed
for all the 76 ISIC 4 digit commodity groups, and measures for labor and
capital market distortions have to be refined and related to policy
instruments that cause them. If this work were done, it would be possible to
estimate the impact of distortions on the structure of production and export
performance, and then devise policies to either remove the cause of the
distortions, or to compensate for them; these policies could be economywide or
industry specific depending on the nature of the distortion.
Second, if the work on distortions suggested above were available,
then it would be possible to make an informed statement about the industries
which it would be economically efficient for India to develop 5 years, or 10
years hence; these would also be industries in which India would enjoy a
comparative advantage in exports. This information would be invaluable for
industrial and commerical policies.
CHAPTER VIII: CONCLUSIONS
The major hypothesis of this study appears to be valid; India's
exports of manufactures have a different factor content and different
commodity characteristics according to their destination--countries that are
more developed receive relatively more of the labor intensive goods, and
countries that are less developed receive relatively more of the capital
intensive goods. There is also evidence that this pattern of exports was
maintained through the decade of the 1970's. This result is especially
striking because the protection systems in the world are biased against such
an outcome. In general, developed countries have relatively high trade
barriers against labor intensive imports, and developing countries have
relatively high trade barriers against capital intensive imports.
There is evidence that protection, and a higher wage than is
efficient for unskilled labor, have resulted in India's industrial structure
being more capital intensive than would be true under efficient allocation;
these distortions also had a negative impact on the relative export
performance of commodities. However, although the structure of production is
affected, the directionality of exports is not. Indeed, it is possible that
protection and high wages reinforce the pattern of exports posited in this
study.
These results can be used to design market and commodity specific
export promotion policies which are presently only commodity specific. With
further work it will be possible to devise policies that counter the effect of
protection and labor market distortions on the structure of production, and to
predict an efficient investment pattern for the future; this information could
have a significant impact on industrial and commercial policy.
-30-
NOTES
1/ A detailed derivation of the pattern of production is available in A.Krueger (1977), A. Deardorff (1979), and A. Khanna (1982).
2/ The pattern of exports is derived in A. Khanna (1982).
3/ A. Krueger (1977) has a detailed discussion of distortions and theirimpact on production and trade.
4/ R. Baldwin (1979), A. Deardorff (1980), W. Travis (1972) discuss the twointerpretations of the HOS model.
5/ For a full discussion of this issue see A. Khanna (1982).
6/ The direct plus indirect factor content analysis includes only thedirect plus indirect factor content of manufacturing; coefficients foragriculture, mining, and service sectors were not available. Thisanalysis suffers from a potential bias in measurement. However in noprevious study have the results for direct, and direct plus indirect,factor content differed.
7/ There are 76 RCA's per destination ranging in value from zero to onethousand. The great variation in the value of RCA's suggests that,because of the level of disaggregation, this measure is susceptible to alot of noise, and therefore less reliable.
8/ There are weaknesses in this technique, first, that each of theestimated coefficients has a different variance and therefore adifferent level of reliability which has not been considered. Second,that relatively few of the coefficients were significantly differentfrom zero at the 5% level. However, the coefficients are the maximumlikelihood estimates and therefore the most reliable for use in thesecond stage.
9/ See A. Krueger (1977).
10/ The weak results are probably due to the level of aggregationrequired. Effective protection rates for India were obtained fromBhagwati and Srinivasan's NBER study on India. A concordance betweenthe NBER and Indian industry classifications was developed for only 35commodity groups.
11/ See A. Khanna (1982).
-31-
APPENDIX I
DATA SOURCES
I. TRADE
India's exports of manufactures for 1973 and 1978 by destination, and
India's relative comparative advantage ratios for 1973 and 1978 by commodity
and by destination were obtained from the World Bank's copy of the United
Nations trade data tapes. The World Bank's concordance program was used to
convert the United Nations data classified in Standard International Trade
Classifications (SITC) to the International Standard Industrial
Classifications (ISIC) used in this analysis.
II. INDUSTRY
a. INDIAN
i. Indian industry direct coefficients, labor market distortions,
and excess profits estimates were calculated from data obtained from the
"Annual Survey of Industries 1973-74: Summary Results for the Factory Sector"
published by the Central Statistical Organization, Ministry of Planning,
India.
ii. An input-output table for India was developed from the "National
Accounts Statistics Transaction Table for 1973-74" also published by the
Central Statistical Organization, Ministry of-Planning, India.
b. UNITED STATES
U.S. industry direct coefficients were calculated from data obtained
from the "Census of Manufactures 1972" published by the Department of
Commerce, United States.
III. COUNTRY ENDOWMENTS
a. LABOR
-32-
Labor force data for countries was obtained from "Labor Force
Estimates and Projections 1950-2000" published by the International Labor
Office. The estimated number was used for the 1970 labor endowment and the
low projection was used for the 1975 endowment.
b. HUMAN CAPITAL
Two types of human capital endowment data were gathered:
i. Literacy rates (male and total) for countries were obtained from
the "Statistical Yearbook 1980" published by UNESCO. For the few countries
that these rates were not available, the rates for similar countries were
used. For instance, the U.S. literacy rates used for other developed
countries. '
ii. Data for percentages of countries labor force that falls into
both (a) professional, technical, and related workers and (b) administrative,
executive, and managerial categories were obtained from various issues of the
"Yearbook of Labor Statistics" published by the International Labor Office.
c. PHYSICAL CAPITAL
a. BASIC DATA
The data for Gross Domestic Investment (GDI) in domestic currency
were obtained from he "World Tables 1976, 1980" published by the World Bank
for all non-socialist block countries and from various issues of the United
Nations National Account Statistics for all the socialist block countries.
GDI data were missing for the period 1955-60 for a few countries; in these
cases the annual average growth rate of GDI for the period 1960-65 was used to
approximate GDI for the earlier period.
The data for exchange rates to convert the domestic currency physical
capital endowments into dollars was obtained from the "World Tables 1975,
1980" for all non-socialist block countries and from "Pick's Currency Annual,
1976" for socialist block countries.
-33-
b. CALCULATION METHODOLOGY
All GDI data were converted to constant 1970 prices (except
Czechoslovakia and the USSR) using implicit GDI price deflators. The physical
capital endowments for 1970 and 1975 were calculated uisng the following
formula
TKT = X (l-r)T- where
t=t0
KT = Physical capital endowment in year T in domestic currency.
Xt= GDI in year t.
r = Double declining depreciation rate of 13.3% based on the assumption of
an average 15 years asset life.
These physical capital endowment numbers for 1970 and 1975 were then
converted to dollars using the average exchange rate for 1970.
In the case of Czechoslovakia and the USSR, base years of 1967 and
1969, respectively, had to be used, and these physical capital endowments were
converted into dollars using the exchange rates for 1967 and 1969. The dollar
endowments were then adjusted for U.S. inflation to the base year 1970 to be
consistent with the endowment data for other countries.
IV. EFFECTIVE PROTECTION
Rates of effective protection applied to industries in India were
obtained from the National Burea of Economic Research study by J. Bhagwati and
T.N. Srinivasan Foreign Trade Regimes and Economic Development.
-34-
APPENDIX II
GLOSSARY OF SYMBOLS AND VARIABLES:
A - Is a 60x60 transactions table for the Indian economy for 1973-74that as converted into an input-output table by dividing each itemby its column total.
cd = Are the direct factor content ratios defined i=1_3 respectivelyas physical capital/labor (k/1), human capital/labor (h/1),physical plus human capital/labor (k+h/1), of India's totalexports of manufactures to each of 50 destination countries j.
tcij - Are the direct plus indirect factor content ratios defined as in
Ci; above.
Dd Is a matrix of direct coefficients that are the physical capital,human capital, and labor content of value added, expressed as aproportion of total output for 76 commodity groups.
Dt = Is a matrix of direct coefficients, conceptually identical to Ddabove, for 60 commodity groups in concordance with A, the input-output table.
d = Is the labor market distortion in industry 'J' defined as thenumber of workers (N) multiplied by the average wage of industry'j (W ) , less the minimum average wage among all industries(6F), Is a proportion of wage value added (Vj) in industry j.
Eij Are the factor endowment ratios defined i = 1...3 respectively, asphysical capital/labor (K/L), human capital (H), physicalcapital/labor and human capital (K/L, H) of each of the 50destination countries j.
Fd = Is the direct factor content matrix (physical capital, humancapital, and labor) of India's exports of manufactures to 50destinations. This matrix is the result of post multiplying theDd matrix by India's export matrix Xd, defined below.
Ft Is the direct plus indirect factor content matrix (physicalcapital, human capital, and labor) of India's exports ofmanufactures to 50 destinations. This matrix is the result ofpost multiplying the Dt matrix by the technology matrix [I-A]1defined below, and post multiplying that product by India's exportmatrix Xt, defined below.
I = I a 60x60 Identity Matrix[I-A] 1 = Is the technology matrix derived by inverting the [I-A] matrix
where I and A are defined as above.
-35-
(K/L)j = Capital/labor endowment of 50 countries 'j'; these are the capitalendowment numbers calculated for 1970 and 1975 divided by workingpopulation numbers for those years.
H = Are the human capital endowments of 50 countries 'j', defined asthe male literacy rate for those countries.
(k/l)i = Are the physical capital/labor ratios of industries 'i',calculated as the physical capital proportion of value addeddivided by the labor proportion of value added.
(h/l)i = Are the human capital/labor ratios of industries 'i', calculatedas the human capital proportion of value added divided by thelabor proportion of value added.
(k+h/l)i = Are the physical plus human capital/labor ratios of industries'i', calculated as the physical plus human capital proportions ofvalue added divided by the labor proportion of value added.
Li = Is the labor market distortion defined as in dj above inconcordance with the industry definitions for which effectiveprotection data were available.
Pi = Effective protection rates for 35 industries 'i', obtained fromBhagwati and Srinivasan's NBER study on India.
Rij = The relative comparative advantage ratios of India's exports of 76commodities 'i' to 50 countries 'J' defined as India's marketshare of commodity 'i' in country 'j' divided by India's marketshare of commodity 'i' in the world.
Ri = The relative comparative advantage ratios of India's exports of 35commodities 'i' defined as India's market share of commodity 'i'in world exports of commodity 'i' divided by India's market sharein world exports of all manufactures.
Xd = A matrix of India's exports of 76 commodity groups to 50destinations for 1973 and 1978.
Xt = India's exports of the 76 commodity groups to 50 destinations for1973 and 1978 aggregated to conform to the commodity definitionsof the input-output table.
Y and X have also been used as dependent and independent variables in severalregression equations; their definition stated with the equations, is specificto those equations.
-36-
APPENDIX IIIDESTINATION COUNTRIES
1. Libya 26. Hong Kong
2. Sudan 27. Indonesia
3. Egypt 28. South Korea
4. Ethiopia 29. Malaysia
5. Kenya 30. Philippines
6. Mauritius 31. Singapore
7. Nigeria 32. Thailand
8. Uganda 33. Taiwan
9. Tanzania 34. Belgium-Luxembourg
10. Canada 35. France
11. United States 36. Federal Republic of Germany
12. Israel 37. Italy
13. Japan 38. Netherlands
14. Bahrain 39. United Kingdom
15. Iran 40. Sweden
16. Iraq 41. Switzerland
17. Kuwait 42. Greece
18. Lebanon 43. Spain
19. Oman 44. Yugoslavia
20. Qatar 45. Czechoslovakia
21. Saudi Arabia 46. Hungary
22. United Arab Emirates 47. Poland
23. Bangladesh 48. U.S.S.R.
24. Burma 49. Australia
25. Sri Lanka 50. New Zealand
-37-
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World B5ank Energy, International Trade, World Bank Reprint Series: NumberWorld Bank ~~~~~~and Economic Growth 180. Reprinted from World Develop-
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