metadata: authors: 0: author: Yeats,Alexander James
docna: 0: docna: What do alternative measures of comparative
            advantage reveal about the composition of developing
            countries' exports?
docty: Policy Research Working Paper
subtopic: Construction Industry,Oil Refining & Gas Industry,Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Plastics & Rubber Industry,International Trade and Trade Rules,Trade and Services,Energy and Mining,Business Cycles and Stabilization Policies
teratopic: Water Resources
abstracts: cdata!: Despite their extensive applications in
            research and policy studies, no product level comparisons
            had been made between Bela Balassa's
            "revealed" comparative advantage (RCA) index and
            indices associated with the National Bureau of Economic
            Research (NBER) that reflect the standard Hecksher-Ohlin
            theory of comparative advantage. The author conducted
            several empirical tests for developing countries'
            exports of manufactured products, partly to identify factors
            that often lead to differences between the two indices. The
            results show that products in which developing countries
            have achieved a revealed comparative advantage are highly
            concentrated in a broad group of labor-intensive products;
            for other items, their RCAs are generally below unity.
            Within the labor-intensive group, however, developing
            countries failed to develop a revealed comparative advantage
            for about half of the items. A regression model suggests
            that in the labor-intensive group, revealed comparative
            advantage falls as the requirements increase for natural
            resources, for physical capital, and for human capital -
            including higher per capita wages, and more professional or
            technical personnel.
repnme: repnme: What do alternative measures of comparative
            advantage reveal about the composition of developing
            countries' exports?
display_title: What do alternative measures of
            comparative advantage reveal about the composition of
            developing countries' exports
listing_relative_url: /research/1990/08/700213/alternative-measures-comparative-advantage-reveal-composition-developing-countries-exports
topicv3: Manufacturing Sectors m1326521 1281,Trade m1326924 698,Trade in Services m1326928 780,Iron m1503514 2931,Petroleum Industry m1583790 4710
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Water Resources
origu: Policy, Research & Ect Affairs
no_of_pages: 34
author_keys: 0: author_key: 93582
model_extractions: **Plc,Research, and Exte'rna f International Trade**

WPS 470 This paper-a product of the International Trade Division, Intemational Economics Departrnent -is part of a larger effort in PRE to provide basic infornaiion for analyzing the presert level and composition of developing countries' exports and projecting future changes in them. Copies are available frec from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Jean Epps, room S8-037, extension 33710 (29 pages, including tables).

Despite their extensive applications in research and policy studics, no product-level comparisons had been made between Bela Balassa's "revealed" comparative advantage (RCA) index and indices associated with the National Bureau of Economic Research (NBER) that reflect the standard Hecksher-Ohlin theory of comparative advantage.

in a broad group of labor-intensive products; for other items, their RCAs are generally below unity.

Within the labor-intensive group, however, developing countries failed to develop a revealed comparative advantage for about half of the items.

Yeats conducted several empirical tests for developing countries' exports of manufactured products, partly to identify factors that often lead to differences between the two indices.

The results show that products in which developing countries have achieved a revealed comparative advantage are highly concentrated A regression model suggests that in the labor-intensive group, revealed comparative advantage falls as the requirements increase for natural resources, for physical capital, and for - human capital including higher per capita wages, and more professional or technical personnel.

The PRE Working Paper Series disseminates thc findings of work under way in the Bank's Policy, Research, and Extemal Affairs Complex. An objective of thc scries is to get these ftndings outquickly, even ifpresentations are less than fullypolished. The findings, interpretations, and conclusions in these papers do not necessarily represent official Bank policy.

IProduced by the PRE Dissemination Centcr
What Do Alternative Measures of Comparative Advantage Reveal About the Composition of Developing Countries' Exports?

by Alexander J. Yeats* Table of Contents

|I.|Introduction|1|
|---|---|---|
|II.|The Comparative Advantage Indices|3|
|III.|Industry Analysis of RCAs and Heckscher-Ohlin<br>Indices|6|
|IV.|Source of Variation<br>iRevealed Comparative Advantage|14|
|V.|Summary and Conclusions|21|
|Refer|ences|23|
|Appen|dix Tables|25|

* Principal Economist, International Economics Department, The World Bank, Washington, D.C. 20433. I would like to thank Bela Balassa and Paul Meo for many helpful comments and suggestions.
# I. Introduction

In economic policy debates at the national and international level, issues relating to comparative advantage have often been a key concern. World Bank structural adjustment loans, for example, have frequently had the objective of stimulating production and the flow of resources into sectors (industries) where developing countries have, or are acquiring, a comparative advantage. Similarly, much of the debate on structural adjLstment policies that has occurred in the World Bank (1986) (1988), OECD (1979), or UNCTAD (1983) has been on ways to facilitate the flow of resources out of developed countries sectors where a comparative advantage has been lost into areas where it has been gained or maintained. Issues relating to comparative advantage have also played an increasingly prominent role in aspects of location theory that deal with the optimal geographic position for establishing firms or subsidlaries of multinational enterprises.

Given the importance attached to comparative advantage issues in these debates, it is not surprising that considerable efforts have been made to empirically assess national comparative advantage. One extensively applied line of analysis is the so called "revealed" comparative advantage (RCA) model which is based on pioneering studies by Balassa (1965) (1968) and tested by UNCTAD
2 (1983) or LNIDO (1982). A second related line of analyses, often associated with Lary's (1968) work for the U.S. National Bureau of Economic Research (NBER), is based directly on a standard Heckscher-Ohlin model and has been applied by Tuong and Yeats (1981), Eizan and Yeats (1989) or Yeats (1989) for tests of trade theories and country export performance.' This approach attempts to determine the relative labor and capital inputs of specific goods, normally defined at the three or four-digit SITC level, and then assumes that d3veloping countries would have a comparative advantage in the production and trade of relatively labor intensive items (Yeats, 1989 provides an empirical verification of this point). However, in view of the number of empirical studies that have been undertaken on comparative advantage, it is surprising that no previous efforts were made to examine the direct link between the Balassa RCA and NBER (Heckscher-Ohlin) measures of developing countries' comparative advantage at the product and industry level.<sup>2</sup> This study conducts several empirical tests relating to this I For example, Yeats (1989) examined the export performance of developing countries for a group of three, four and five-digit SITC products that Lary (1968) determined were manufactured by labor-intensive production processes in the mid-1960s. The results showed that developing countries achieved a major increase in their market shares (from 8.7 to 21.2 per cent) for labor-intensive goods exported to developed market economy countries while the shares for all other nonfuel goods declined from 21.7 to 14.1 per cent. In the United States, developing countries increased their share of labor-intensive good imports from 17.9 to 40.5 per cent while their share of other nonfuel goods fell from 33.0 to 19.3 percent. See Appendix Table 2 for a comparision of developing countries' export performance for labor intensive and other goods in major OECD markets. These, and various other empirical tests lead to the conclusion that the NBER labor intensity indices provide a useful and accurate guide to the future composition of developing country exports.

> 2 Balassa (1979) calculated RCA and capital intensity indices for some 184 four-digit SIC products and analyzed this information after it had been aggregated to the national level for some 36 developed and developing countries. This lead to a "stages" theory of national comparative advantage. Tyers and Phillips (1S89) examined RCA indices and measures of labor intensity, technology, and human capital for very broad categories of goods (agriculture, minerals, etc.) at the national level for selected Asian countries.
3 point and also attempts to identify factors that often lead to differences between the NBER and Balassa RCA indices.

II. The Comparative Advantage Indices Heckscher-Ohlin measures of comparative advantage are generally similar to labor intensity indices derived by Lary (1968) for the NBER. Lary's analysis employed the criteria of value added per employee, both in the U. S. and other countries, for identification of products which were capital or labor intensive. The general rule followed was to classify labor-intensive products as those which met two conditions, the first being that value added per employee did not exceed the national average for all United States manufacturing by more than 10 per cent.<sup>3</sup> The specific factor .ntensity index calculated for industry j (L.) was defined as, where V and Vt represent value added in industry j and all United States manufacturing respectively, while Nj and Nt represent the number of workers in 3 The use of United States data is appropriate for identifying labcr intensive products if these items are genrally produced by labor intensive - processes in other countries. Lary (1968, Appendix D) analyzed U.S. U.K., U.S. - - Japan, and U.S. India production data and determined this was generally the case. However, based on these comparisons several additional products were added to the list derived from U.S. statistics.
4 the industry and in all manufacturing activity.4 In addition, the NBER imposed a second criteria that imports by developed from developing countries totalled at least $100,000 at the three-digit level of the Standard International Trade Classifications (SITC) system in 1965. According to the NBER reasoning, this approach excluded clearly capital-intensive products while applying the test of the market (as reflected in imports) to iterils at or near the overall national average. The import value criteria was therefore added in recognition that -alue added per employee was not an infallible guide to South-North comparative advantage.

In contrast to the Heckscher-Ohlin (NBER) approach, Balassa (1965) developed the concept of "revealed" comparative advantage which is measured by the share of a given product in a countr-y's total exports relative to the good's 4 The reader should note that there is an inverse relation between the numeric value of the index defined in equation (1) and the labor intensity of a given product. That is, the lower the numeric value of the index the higher the labor intensity. It also follows that products with very high index values are capital intensive in production. The selection of items based on value added per employee in the U.S. was supplemented by detailed examination of manufactures itported by developed from less developed countries to see if additional products needed to be taken into account. On this basis, several items such as batteries, lamps and miscellaneous manufactures were added to the NBER list since relative valuf. added in other countries appeared below the United States average. However, a major conclusion of this analysis was that products manufactured by labor-intensive processes in the United States were also manufactured by re'latively Labor-intensive processes in other countries. Lary used these findings to justify extensive use of United States production statistics as a guide to factor proportion.
5 share in total world exports of ma-nu`ctures.s Specifically, if xij is the value of country i's exports of j and Xit is the country's total exports of manufactures, its revealed comparative advantage index is, where the w subscripts refer to world trade totals. The RCA index may take values from zero to infinity with those above unity indicating the country has a comparative advantage in the product. A point of considerable interest would be to determine how the above "revealed" comparative advantage index, for (say) all, or groups of, developing countries c3mpares with the NBER labor-intensity index for a common group of products. A high correlation (i.e., high developing country RCAs for industries with high labor-intensity ratios) would be an important verification of the Heckscher-Ohlin theory.

Before *ndertaking such an empirical test, howaver, it is useful to consider factors that might cause the Balassa and NationaL Bureau indices to differ. First, protectionism in major markets could limit developing countries' exports of a labor-intensive product to a sufficient extent that the RCA index is constrained below levels (above unity) that it would reach in the absence of trade barriers. Such a situation might, for example, occur for (say) textile 5 Foods and agricultural raw materials have generally been excluded from revealed comparative advantage computations since it is felt that protectionism and subsidization in these sectors distorts trade to an extent that comparative advantage cannot be measured using the Balassa approach. Following standard practice, this study employs a definition of manufactures that includes all items classified in SITC 5 through 8 less 68 (nonferrous metals) Dlus a few processed food and raw material products items classified in other groups. The latter were added to achieve consistency with the definition used and results presented in the NBER study.
6 and clothing products when exports from developing countries face discrimin-itory trade barriers under the Multifibre Arrangement. Second, international transport costs could also be a factor. If freight costs are particularly high for an industry, this may have a locational influence that would override the effects of labor intensity.6 Third, there are certain products that must normally be located close to centers of raw material production or in areas where relatively cheap energy sources exist (aluminum smelting is an example). For products where these considerations are important, labor intensity may not be the major factor determining the location of production. Fourth, government policies in the exporting countries themselves can have a major influence on revealed comparative advantage. Such would be the case if specific exports were subsidized, if trade barriers (i.e., effective protection) produced major distortions in production incentives, or if other government policies had a substantial anti-export bias. Finally, some labor intensive processes require high skill labor inputs (jewel cutting, lens grinding, fabrication of some high tech instruments, etc.) or special management skills that are in short supply in developing countries.

# III. Industry Analysis of RCAs and Heckscher-Ohlin Indices

For a test of the relation between Balassa's RCA index and the National Bureau's index of labor intensity, both measures were computed for 6 Transport costs can have two different types of locational effects depending on the nature of the product(s) in question. For items that undergo considerable reduction in weight or bulk with fabrication (which should reduce nominal freight charges) there would be an incentive to locate manufacturing activity close to the raw material inputs. Second, some products (like beverages which require the mixture of syrups with water) greatly expand their bulk and freight costs upon processing. Transport costs for such items could dictate that their production be located close to centers of consumption, a factor that would offset the influence of factor proportions.
7 labor intensive products previously identified by the NBER as well as all other (capital. intensive) manufactured goods. For the initial tests the revealed comparative aevantage indices were computed for all developing countries as a group with all developed countries being the destination of exports. This procedure generated 119 distinct three, four and five-digit SITC labor intensive products and 88 similar capital intensive products which had matched RCA and labor intensity indices. Since there was an interest in determining how the relation between the two comparative advantage indices might vary between developing countries at different levels of industrialization, revealed comparative advantage indices were also computed for the 207 labor and capital intensive goods exported from two selected groups of developing countries: Asian semi-industrialized exporters of manufactures (Hong Kong, Republic of Korea, Singapore and Taiwan, China) and a group of "other" South Asian developing countries (Indonesia, Malaysia, Thailand and the Philippines).

Table 1 provides summary statistics on comparisons between the Heckscher-Ohlin indices and matched developing countries' revealed comparative advantage indices for both the NBER labor intensive and other capital intensive products. To determine how the relationship may have changed these comparisons are made for different years; 1965, 1975 and 1985. In addition, the value of imports from developing countries is shown for these three years.' To assist 7 Erzan and Yeats (1989) examined broad two-digit U.S. Standard Industrial Classification (SIC) changes in factor intensities over this interval and generally f(und that sectors using relatively labor-intensive techniques in the earlier period employed similar techniques in 1982. Petroleum and coal products (SIC 29) and tobacco products (SIC 21) were exceptions as both sectors experienced a major increase in capital intensity while primary metals (SIC 33) became more labor intensive. Erzan-Yeats also found that textiles and clothing became slightly more labor intensive in spite of high levels of protection under the MFA which was intended to provide the industry with opportunities to implement structural adjustment measures.
on the Correspondence Between Developing Countries' RCA and Heckscher-Ohlin Indices Bureau of Economic Research Labor Intensive Product Group and Other Manufactures Table I

# Summary Statistics for the National

|||%of individual<br>pro-||Individual<br>pro|mucts with|
|---|---|---|---|---|---|
|||duct manufactures with|Total valueofexports to|RCAsexceedin|g unity|
|Product/Country<br>Group|Year|RCAs exceedingunity1/|developed countries<br>(Smill)|<br>Value (Sill)|<br>**S**oftotal|
|NBERlabor Intensive Manufactures||||||
|Alldeveloping countries|1965|30.2|2,945.7|2,499.0|64.8|
||1975|45.3|20,864.7|17,592.3|84.3|
||1985|51.3|98,785.0|83,186.0|84.2|
|Asian exporters<br>of manufactures|1965|29.4|956.9|869.6|90.9|
||1975|39.5|11,043.1|9,250.6|83.S|
||1985|49.5|55,968.4|49,777.4|88.9|
|Other South-Asian counlries|1965|19.7|202.4|191.8|94.8|
||1975|33.6|1,33t.0|1,179.7|a8.7|
||1985|29.4|9,267.6|7,734.8|83.5|
|All Other ManufacturedGoods||||||
|Alldeveloping countries<br>2/|1965|6.8|906.5|482.0|53.2|
||1975|9.1|4,641.8|1,930.1|41.6|
||1985|14.8|26,311.5|d,212.2|31.2|
|Asian Exporters<br>of mnuf,<br>*ures 3/|1965|1.1|41.2|1.0|2.4|
||1975|2.3|860.7|241.9|28.1|
||1985|6.8|7,033.2|1,919.4|27.2|
|Other South-Asian countries<br>4/|1965|3.4|19.1|3.4|17.8|
||1975|2.3|97.1|8.6|8.9|
||1985|0.0|848.6|0.0|0.0|

- I/ The NBER labor intensive group is composed of 119 distinct three, four and five-digit SITC products. See Appendix Table I for a lisTing of these Items with their corresponding labor intensity and revealed comparative advantage indices. The "all other" (capital intensive) group Is composed of 88 three, four and five-digit SITC products.

- 2/ Outside the NBER labor intensive product group these developing countries had a 1985 RCA above one in the fol lowing SITC groups (SITC no. in parenthesis): inorganic chemicals (513); coal and petroleum based chemicals (521); dyes anC tanning products (532); explosives (571); unhardened rubber products (69292); cement (6612); nonindustrial diamonds (6672); pig iron (671); iron and steel tubes (6783); iron and steei anchors W6NW4; television receivers (7241); ships and boats (735); and base metal office supplies (8951).

- 3/ Outside the NBER labor intensive product group these developing countries had a 1985 RCA above one in the fol lowing SiTC groups (SITC no. in parentheses): rubber tyres and tubes (6291); iron and steel anchors (6984*; nonelectric domestic appliances (7194ki television receivers (7241); ships and boats (735); and base metal office supplies (8951).

- 4/ Coal and petroleum products (SITC 521); medicinal products (541); unhardened rubber products (6293); cameras and projectors (8615); and developed cinema f its (863) were the non-NBER products in which these countries developed RCAs greater than one.
9 in evaluating this information, the percentage of NBER and capital intensive goods (measured both in terms of the number of products and value of exports) for which the developing countries recorded a revealed comparative advantage exceeding unity is given.8 Appendix Table 1 provides detailed information on the matched RCA and labor intensity indices for each of the 119 products included in the original National Bureau selection.

It is evident from Table 1 that the Balassa RCA and labor intensity indices generally perform as expected for the NBER group of products (where RCAs tend to be above unity) as well as the capital intensive manufactures group (where RCAs are normally below one). This reflects a clear confirmation of the Hecksher-Ohlin theory of comparative advantage.9 vrom 1965 to 1985 the percentage of NBER labor intensive products in which developing countries had a revealed Gomparative advantage increased by more than 20 percentage points and reac'.ed 51 per cent. In value terms the association is stronger as developing countries had revaaled comparative advantage indices over unity in products that accounted for 84 per cent of total labor intensive shipmencs in each of the three years while this ratio approaches 90 per cent for the Asian exporters of manufactures. The table also indicates that the "othur South-Asian Countries' I In assessing the results reported in Table 1 more importance should be given to export values than to the number of products since some items are of relatively little importance in trade. Table 1 shows that developing countries have generally achieved high RCAs in the most important labor intensive products.

9 While the aggregate results reported in Table 1 are fully consistent with, and provide an empirical verification of, factor proportions theory it may be viewed as surprising that developing countries were not able to establish a revealed comparative advantage in approximately one-half of the products which were identified by the NBER as being labor intensive. There are exceptions, but subsequent analyses will show (see Section IV of this paper) that, within the NBER group, developing countries had their highest RCAs in the most labor intensive products.
10 were far more specialized within the labor intensive group as they only had a revealed comparative advantage in 29 per cent of the NBER products (by number), yet these items accounted for almost 84 per cent of their total 1985 value of shipments of labor intensive manufactures.

In contrast to labor intensive products, Table 1 shows that, for the majority of items with moderate to high capital intensities, developing countries mostly failed to establish a revealed comparative advantage. In 1985 these countries ach.'eved a revealed comparative advantage in only 14.8 per cent of these items. Furthermore, the underlying data indicate two types of products were largely responsible for these results. The first were capital intensive items whose production location may be influenced by the existence of a natural resource base (i.e., cement, coal and petroleum based chemical products, dyes and tanning products, etc.,) or whose production characteristics changed from capital to labor intensive over the 1965 to 1985 interval.

A question of considerable interest is why, within the labor intensive product group, developing countries failed to develop a revealed comparative advantage in approximately one-half of the NBER items. One possibility is that high RCAs generally prevail among the most labor intensive of these products with revealed comparative advantage indices below unity clustered in those items that require higher capital inputs. Figure 1 tests this hypothesis. Here, all prodiicts are ranked in terms of increasing labor intensity (i.e., decreasing capital intensity) as one moves from left to right on the horizontal axis while the vertical axis records the revealed comparative advantage indices developing countries achieved for each product. While there is a significant relationship between the RCAs and labor intensity, the large variations from product-to-product clearly show that other factors have a major of these products with revealed comparative advantage indices below unity
the 119 SITC<sup>Products</sup> Figure 1.<sup>Comparison</sup> of Matched Developing<sup>Country RCAand LaborIntensity Indicesfor</sup> in the _NBER1_<sup>Labor</sup> Intensive Product Croup <!-- Start of picture text --> Balassa's Revealed g<br>Comparatlve Advantage 1 .<br>tndex<br>i | X<br>6.Q0<br>ji~ ~ ~ ~ ~~ ~~~~~~~~~~~~~~~~~~~~I<br>45<br>U I5<br>3.5 14<br>- Cii S J<br>4.0<br>1.5<br>.0.<br>s<br>110 100 9080060<br>Increasing Capital Intensity Increasing Labor Intensitygo<br>NATION~AL BUREAUJ OF ECONOMIC RESEARCH LABOR INTENSITY INIWX<br><!-- End of picture text -->
Tabulation of Products with High Labor Intensities and Developing Countries' RCAs Below Unity Table 2

||v<br>|NBER ind<br>alue added/empl<br>|ex a/<br>oyee(mig1OO)|Value<br>developed|of imports by<br>countries (Smill)|Developi|ng countrie|s RCA Index|
|---|---|---|---|---|---|---|---|---|
|SITC|Description|1965|1982|1965|1985|1965|1975|1985|
|631.8<br>|Wood simply worked<br>|54|55|41.4|973.0|4.11|0.83|0.98|
|661.3<br>|Building stone worked<br>|57|65|58.5|944.4|0.53|0.94|0.84|
|633<br>|Cork manufactures|64|65|51.3|234.1|0.95|0.42|0.21|
|631.4<br>|Reconstituted wood|64|62|55.7|858.5|0.13|0.05|0.14|
|653.6<br>|Woven regenerated fabrics<br>|71|62|377.2|961.7|0.27|0.75|0.82|
|655 b/<br>|Special Textile products|71|60|364.9|3,274.5|1.49|1.23|0.63|
|653.2<br>|Woven wool fabrics<br>|71|62|550.6|1,390.7|0.24|0.30|0.39|
|662<br>|Clay refractory products|73|76|282.1|2,264.7|0.36|0.33|0.34|
|732.9<br>|Motorcycles and parts<br>|76|72|230.2|1,706.0|0.07|0.07|0.00|
|717.1<br>|Textile machinery|76|76|726.4|3,352.4|0.02|0.05|0.85|
|895.2<br>|Pens and pencils<br>|77|93|78.6|782.5|0.25|0.35|0.47|
|892 c/<br>|Printed matter|78|77|182.7|1,517.9|0.39|0.43|0.40|
|657<br>|Floor covers<br>|79|50|487.7|3,226.6|5.34|3.77|0.41|
|642 d/<br>|Articles of paper|81|103|249.5|4,446.6|0.15|0.46|0.63|
|693<br>|Wire products<br>|82|73|152.8|1,359.2|0.11|0.53|0.85|
|663<br>|Mineral manufactures, nes|82|85|285.8|2,714.3|0.37|0.27|0.24|
|653.9<br>|Woven fabrics, nes<br>|84|62|54.2|131.9|0.75|1.06|0.92|
|062<br>|Sugar preparations<br>|84<br>|140|76.9|740.2|0.04|0.65|0.52|
|653.3<br>|Linen and hemp woven fabrics<br>|<br>84<br>|62|18.8|145.4|0.21|0.20|0.34|
|653.7<br>|Knitted or crocheted fabrics<br>|<br>84|62|187.1|1,081.0|0.32|0.24|0.24|
|661.8<br>|Mineral building products<br>|85|85|53.5|329.9|0.79|0.25|0.91|
|718.1|Paper mill machinery|87|99|224.7|1,844.1|0.01|0.05|0.16|
|Memo Ite|m (high labor Intensive high RCA|products)|||||||
|841.1<br>|Textile clothing not knit<br>|49|50|835.5|21,758.0|4.74|5.26|4.03|
|841.4|Clothing accessories knit|49|50|872.1|14,856.8|3.49|5.12|3.62|
|851|Footwear|55|50|538.2|12,702.8|1.53|2.89|3.14|
|841.3|Leather clothing|53|52|80.2|2,135.4|2.96|6.71|4.68|

- a/ For some products it was necessary to estimate labor Intensities as a range due to the fact that a direct concordance between the SIC and SITC does not exist (See Appendix Table 1 for details). In these cases, the above figure show the average o thge ihgh and low labor intensity ratios.

- b/ Excludes 655.1 felt and articles n.e.s. and elastic fabric not knit.

- c/ Excludes 892.2 newspaper and periodicdis.

d/ Includes 641.7 handmade papers.
13 influence on developing countries comparative advantage. **'O** For example, developing countries achieved RCAs ovr.c 3.0 for several of the most highly capital intensive products on the tiBER list (i.e., products with a factor intensity index of 95.0 or more) including radio broadcast receivers, meat or fish meal, and fur clothing while they failed to achieve a revealed comparative advantage in a number of highly labor intensive products (i.e., items with an NBER labor intensive index of 80.0 or lower). This indicates that other factors may often negate or override the competitive edge that high labor intensity provides for developing countries."1 A question of importance concerns the nature of the product characteristics that have these offsetting effects.

In an initial attempt to account for the RCA variations, Table 2 lists the most highly labor intensive products for which developing countries failed to achieve RCAs over unity. Several possible factors may explain the developing countries' relatively poor performance in these items.12 First, the '° A nonlinear (quadratic) regression fitted to the labor intensity and RCA indices in Figure 1 took the form: where L is the labor intensity for product j and t values are shown in parenthe0sis. Labor intensity, by itself, accounts for 28 per cent of the total variation in the revealed comparative advantage indices with 72 per cent of the total variation remaining unexplained.

11 Meat or fish meal and fur clothing are classified by UNIDO as natural resource intensive products. A required natural resource base -- such as the availability of anchovies in Peru and several other Latin American countries - - is no doubt a factor offsetting the influence of labor intensity.

12 See the notes to Table 1 for a list of capital intensive products in which developing countries had high revealed comparative advantage indices. These appear to be mainly composed of natural resource intensive products (i.e., coal and petroleum based chemicals, rubber manufactures, cement, etc.,) or certain types of iron and steel products which often received government subsidies.
14 value of trade in several products may be too low (under one-half billion) to stimulate development of required produciton capacity. Developing countries may have consciously focussed on higher value fast growing products. As the table indicates (see the memo item), developing countries have developed high RCA's in high value labor intensive products like footwear and clothing where trade approaches $50 billion in spite of quotas and other NTBs that are applied to these goods. Second, several products like paper articles, sugar preparations, pens and pencils, and paper mill machinery became less suitable for developing countries over 1965-1982 since they shifted to relatively more capital intensive production techniques. Tbird, a "natural resource" production orientation may affect some items as UNIDO (1982) classifies several products i.e., cork, clay products, worked building stone, etc.,) as having a strong pull toward raw material sources.13

# IV. Source of Variation in Revealed ComRarative Advantage

While the previous analysis showed that developing countries' revealed comparative advantage was concentrated within a group of products manufactured by labor intensive processes, a surprising point was that they failed to develop RCAs above unity for about one half of these items. This 13 While the RCA indices reported in Table 2 are relatively stable over 1965-85, there are three products for which they went from above to below unity. The results for simply worked wood (SITC 631.8) appear to be due to a major shift by developing countries out of this item into "upstream" products like plywood, veneers, and wood manufactures. Floor covers witnessed a major expansion of -- trade in linoleum and synthetic fiber floor covers (SITC 657.4 and 657.6) items that appear to be manufactured by relatively capital intensive processes. - The labor intensive component product (knotted carpets and rugs SITC 657.5) experienced a declining share in the total trade in floor covers. Cordage is the major component of special textile products (SITC 655). Here, trade in capital intensive synthetic fibre cordage has rapidly displaced exports of (labor intensive) natural fiber (jute, sisal, etc.) cordage.
15 suggests that other factors offset the advantages associated with lower<sup>labor</sup> costs in developing countries. In an attempt to identify these factors, production information was collected on the following variables<sup>which other</sup> studies (Baldwin (1971), Helleiner (1976) and Hufbauer (1970) indicate<sup>have</sup> influenced the level and structure of trade:

- (1) Two Human Capital Variables (a). The share of the labor force accounted for by professional or technical personnel, and (b). average<sup>per</sup> capita wages in the industry. Average per capita wages is part of the<sup>NBER</sup> measure; the rest is non-wage value added that represents physical capital. The assumption is that most developing countries would not have a comparative advantage in sectors requiring high human capital inputs.

- (2) A Market Size Variable Developed market economy imports measured in 1985 US dollars. The purpose is to determine whether developing countries "target" items with larger markets, ceteris paribus, when establishing a production base for exports.

- (3) Capital Requirements The value of fixed plant and equipment per capita immediately employed in making the commodity. Developing countries comparative advantage should be inversely related to this variable.

- (4) A Product Differentiation Variable Measured by the coefficient of variation in unit values of the industry's goods destined for different countries. To determine if developing countries are less likely to have a comparative advantage in more differentiated products.

- (5) Consumer Orientation (Goods) Ratio Percentage of industry output (and imports) directly purchased by final consumers. Has developing countries' comparative advantage differed in consumer as opposed to producer goods?

- (6) Resource Based Production Variable UNIDO (1982) identified goods whose production location is normally based near raw material supplies. A dummy variable takes a value of one for these items or zero otherwise. Do natural resource requirements significantly influence patterns of developing countries' revealed comparative advantage?

- (7) A Product Cycle Variable The approximate date that the item was first traded internationally according to Hufbauer (1970). Is developing countries comparative advantage weighted towards older more established products?
16 (8) An Industry Scale Variable - Identifies industries where economies of scale appear to be operative (see the notes to Table 3). Is developing countries comparative advantage adversely affected by larger scale production requirements.

These variables were then matched with the labor intensity and revealed comparstive advantage indices at the level of product detail indicated in Appendix Table l.'4 Correlations were then run with these explanatory variables and the RCA indices.

Table 3 shows Spearman correlation coefficients for these explanatory variables and the industry RCA values for all developing countries as well as those for the two groups of Asian countries. In all three country groups the labor intensity variable is statistically significant at the 99 per cent level and takes the expected (negative) sign.15 The human capital (per capita wage) and physical capital variables are also highly correlated with the developing countries' revealed comparative advantage and the signs associated with these variables are as expected -- as physical and human capital requirements increase 14 The reader should note that the NBER measure (equation 1) represents capital intensity that combires physical and human capital. Variables (1) and (3) above attempt to independently measure the effects of human and physical capital. The human capital, physical capital and product differentiation variables are all based on U.S. Department of Commerce, Census of Manufactures data, while the market size variable was estimated using United Nations, Series D Commodity Trade Statistics. UNIDO (1982) was the source of resource based product information, while Hufbauer (1970) identified the first trade dates for the different products. In some cases, these dependent variables were derived for three-digit product groups and it was necessary to apply these values to underlying four and five-digit products listed in Appendix Table 1. See Balassa (1979, pp. 260-262) for suggestions of other variables that might be tested, as well as a discussion of the use of stock and flow variables for the capital measures.

's The negative sign was expected since an inverse indicator is involved - that is, the higher the value of the index the less labor intensive (i.e., more capital intensive) is the production process. As such, Table 3 shows that, as one moves to less labor intensive production processes developing countries' revealed comparative advantage indices decline.
17 Table 3

# Spearman Rank Correlation Coefficients Between Revealed Comparative Advantage Indices and Ton Explanatory Variables

|:xpl|anatory<br>Variable 1/|All Developing<br>Countries|Asian Exporters<br>of manufactures|Other South<br>Asian Countries|
|---|---|---|---|---|
|1)|Labor intensity<br>variable|-0.542*|-0.499*|-0.559'|
|(2)|Developed country imports (Smill.)|-0.119|-0.078|-0.021|
|(3)|Capital per worker|-0.547^|-0.494*|-0.492*|
|(4)|Skill variable|-0.338*|-0.254|-0.377*|
|5)|Average per capita wage|-0.617*|-0.5840|-0.615*|
|:)|Scale variable|-0.271*|-0.248|-0.259|
|7)|Consumer good ratio|0.476*|0.492'|0.427*|
|8)<br>|First trade date<br>|-0.2890|-0.276|-0.226|
|(9)|Product differentiation<br>variable|-0.326'|-0.259|-0.286'|
|(10)|Resource based product dummy2/|-0.183|-0.017|-0.159|

Statistically significant at the 99 per cent level.

- / The explanatory variables are defined as follows:

- (1) Labor intensity average per capita value added in the industry relative to that for all United States manufacturing activity.

(2) Developed country imports - a measure of the size of the market for the product. Measured in 1985 US dollars.

(3) Fixed plant and equipment immediately employed in making the commodity. Measured in US dollars on a per capita basis.

(4) Percentage of the industry's labor force xccounted for by professional, technical and scientific personnel.

(5) wage bill divided by total employees immediately occupiad in making the commodity. A measure of human capital.

(6) The exponent in the regression equation V = KNa, where V is the ratio between value added in plants employing N persons and the average value added for the industry.

(7) Percentage of industry output (and imports) directly purchased by final consumers.

(8) Hufbauer's (1970) estimate of the first date (year) that the product was traded internationally.

(9) Measured by the coefficient of variation in unit values of industry goods destined for different countries. Differentiated goods have higher coefficients of variation.

(10) Taken from UNIDO (1982). Products dependent on available natural resources take a value of one. Other greods take a value of zero.

Since more than 85 per cent of the NBER labor intensive products are not considered to be natural resource based, and hence take a value of zero for this dummy, the rank correlation coefficient is a very weak statistical test for causality. A dummy variable produces a very weak ranking as it merely separates the data into two alternative levels.
18 developing countries' :omparative advantage falls.

Tiible 3 indicates that several variables are not affecting developing countries' revealed _.omparative advantage, with the market size variable failing to achieve significance for each of the three groups of exporters.'6 Relatively weak results are also achieved for the scale variable and first trade data -- - these terms are not significant for either of the two Asian country subgroups - while the product differentiation variable does not appear to influence the RCA profiles of the Asian exporters of manufactures. These three variables are, however, significant for the runs for all developing countries.

To what extent can the variables listed in Table 3 jointly account for differences in developing countries' revealed comparative advantage? While a high degree of inter-correlation between some of the independent variables made estimation difficult, a series of linear multiple regressions were run to provide an approximate answer.'7 Representative results for these regressions are summarized in Table 4.

Table 4 shows that labor intensity, by itself, accounts for about 24 per cent of the total variation in developing countries revealed comparative advantage with the relationship improving when nonlinear regression forms were

> 16 While results for the resource based production variable are shown in Table 3 the basis for running rank correlations on this term are weak. This dummy variable establishes a dichotomy between industries, by taking value of zero or one, and therefore establishes only a very weak ranking. More appropriate regression tests are given in Table 4 and these show that natural resource requirements have an important influence on developing countries comparative advantage.

> 17 The author will provide interested readers with full Pearson and Spearman correlation coefficients between the RCA indices and explanatory variables listed in Table 3 upon request.
# Table 4

|||Regr|ession Result<br>Advantage In|s for All Deve<br>dices Against<br>(t values sho|loped Count<br>Selected Ex<br>wn in paren|ries Revealed C<br>planatory Vari<br>thesis)|omparative<br>ables|||
|---|---|---|---|---|---|---|---|---|---|
|||||_______<br>__In|dependent Va|riables||||
|Dependent<br>Variable|Constant|Labor<br>intensity|Consumer<br>good ratio|Average per<br>capita wage|Resource<br>dummy|Capital per<br>worker|Scale<br>variable|First trade<br>date|R2|
|RCA1/|2.045<br>(10.31)|-0.018<br>(6.06)*|--|--|--|--|--|--|0.236|
|RCA|1.659<br>(4.48)|-0.010<br>(3.47)'|0.002<br>(5.36)*|--|--|--|--|--|0.386|
|RCA|5.414<br>(12.17)|-0.002<br>(0.47)|--|-0.0007<br>(6.49)|--|--|--|--|0.437|
|RCA|4.659<br>(6.26)|-0.004<br>(2.41)'|0.0D08<br>(1.71)|-0.0005<br>(4.05)*|-1.577<br>(4.27)*|--|--|--|0.525|
|RCA|4.719<br>(6.26)|-0.005<br>(2.45)'|0.0008<br>(1,73)|-0.0006<br>(4.05)'|-1.593<br>(4.27)'|0.00003<br>(0.56)|--|--|0.527|
|RCA|4.612<br>(6.17)|-0.005<br>(2.36)*|0.0007<br>(1.55)|-0.0005<br>(3.85)'|-1.621<br>(4.34)'|--|-0.001|--|0.528|
|RCA|42.156|-0.004|0.0007|-0.0006|-1.622|--|-|0.019|0.530|
||(1.15)|(1.24)|(1.49)|(4.09)|(4.36)|||(1.02)||

1/ In a double log form this regression produces a somewhat better fit as the coefficient of determination Increases<sup>to 28 per</sup> cent.
20 tested.18 When other combinations of explanatory variables were added the relationship improves to the point that over 50 per cent of the variation in developing countries' RCA indices are accounted for. In these runs the natural resource, consumer good ratio, and human capital (per capita wage) variables appear to make the. strongest contribution toward improving the regressicn's explanatory power.

When the regressions shown in Table 4 were repeated for the two Asian developing country sub-groups rather different results (not shown) were achieved. The pattern for Indonesia, Malaysia, Thailand and the Philippines corresponded closely to that for all developing countries, but there were marked differences for the Asian exporters of manufactures (Rep. of Korea, Hong Kong, Singapore, and Taiwan, Province of China). Here, there was a deterioration in the explanatory power of the labor intensity and physical and human capital variables.19 The weaker results suggest that these countries have advanced to a stage where lower labor costs are no longer providing a major stimulus to 18 When a double log form was used the results improved slightly (R<sup>2</sup> 0.28) -- about the same level of explanatory power was achieved using a quadratic form (see equation 3). Given that several of the independent variables take negative values or are zero-one dummys, it was not possible to utilize a standard nonlinear form for the multiple regressions although several variables appeared not to take a linear form.

> 19 For example, the regression between the Asian NICs revealed comparative advantage indices and the labor intensity variable took the form:

which wa; much weaker than the corresponding equation for all developing countries shown in Table 4. Also, the explanatory variables shown in the table were only able to account for 33 per cent of the variation in the NTCs results while they "explained" over half of the variation in all developing countries RCA industries.
21 exports, nor does a shortage of capital serve as the constraint it is in other developitag countries.

# V. Summary and Conclusions

Economic theory postulates that developing countries should have a comparative advantage in labor intensive products in their trade with developed market economy countries. This study examined the validity and strergth of this proposition by comparing indices of labor intensity for three, four and fivedigit SITC products with matched indices of developing countries' revealed comparative advantage. The findings have important implications, ranging from a test of factor proportions theory to the establishment of a methodology for ide-.tifying potential "successful" developing country export. The results also provide quantitative evidence on the extent to which labor intensity, and several other production and market characteristic variables, influence the product composition of South-North trade.

The results show that products in which developing countries have a revealed comparative advantage are in fact highly concentrated . ithin the labor intensive group. This provides a strong verification of factor proportions theory. In particular, where relatively low RCAs occur in the labor intensive group human and physical capital requirements, as well as natural resource requirements appear to be explanatory factors. Regressions were tested which explained over 50 per cent of the variation in RCA indices. The explanatory variables in these tests largely related to differences in production functions and it appears the results could be improved by testing factors relating to demand -- particularly, measures that reflect trade barriers or the market power of domestic firms. Three (or five) firm concentration ratios for sales or production have been extensively employed as measures of market power in the
22 industrial organization literature and these indices could be tested in connection with variations in RCA indices.