How Important Are Dual Economy Effects for Aggregate Productivity?

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How Important Are Dual Economy Effects for Aggregate Productivity? How Important are Dual Economy Effects for Aggregate Productivity? Dietrich Vollratha University of Houston Abstract: This paper brings together development accounting techniques and the dual economy model to address the role that factor markets have in creating variation in aggregate total factor productivity (TFP).Developmentaccountingresearchhasshownthatmuchofthevariationinincomeacrosscountries can be attributed to differences in TFP. The dual economy model suggests that aggregate productivity is depressed by having too many factors to low productivity work in agriculture. Data show large differences in marginal products of similar factors within many developing countries, offering prima facie evidence of this misallocation. Using a simple two-sector decomposition of the economy, this article estimates the role of these misallocations in accounting for the cross-country income distribution. A key contribution is the ability to bring sector specific data on human and physical capital stocks to the analysis. Variation across countries in the degree of misallocation is shown to account for 30 — 40% of the variation in income per capita, and up to 80% of the variation in aggregate TFP. JEL Codes: O1, O4, Q1 Keywords: Resource allocation; Labor allocation; Dual economy; Income distribution; Factor markets; TFP a) I’d like to thank Francesco Caselli, Areendam Chanda, Carl-Johan Dalgaard, Jim Feyrer, Oded Galor, Doug Gollin, Vernon Henderson, Peter Howitt, Mike Jerzmanowksi, Omer Moav, Malhar Nabar, Jonathan Temple, David Weil, and an anonymous referee for helpful comments and advice. In addition, the participants at the Brown Macroeconomics Seminar, Northeast Universities Development Conference and Brown Macro Lunches were very helpful. All errors are, of course, my own. Department of Economics, 201C McElhinney Hall, Houston, TX 77204 [email protected] 1 1Introduction One of the most persistent relationships in economic development is the inverse one between income and agriculture, seen here in figure 1. In the cross-section as well as over time, increases in income are associated with decreases in the relative size of the agricultural sector. The strength of this relationship is such that the decline of agriculture is often seen as a major hallmark of economic development. 12 JPN DNKNOR USANLDSWEFRAAUTFIN 10 GBRCANAUSITA NZL GRCPRT KOR ARG URY TTO ZAF VEN CHL CRI 8 MUS POL TUR JAMCOL TUN PER DOM IRN SLV MAR GTM PHL EGY IDN SYR HND ZWE Log of GDP per capita per Log of GDP LKA PAK 6 IND KEN TZA MWI 4 0 .2 .4 .6 .8 Percent of Labor in Agriculture Figure 1: Income per capita and Percent of Labor Force in Agriculture Note: GDP Data is from PWT 5.0 and agricultural labor share is from FAO. The development accounting literature, typified by Hall & Jones (1999) and Klenow & Rodriguez- Clare (1997), has focused on the cross-country variation in income observed in figure 1. It is generally found that differences in total factor productivity (TFP) are the primary source of in- come variation. This literature, though, has not concentrated on the role of agriculture until very recently. In contrast, the field of development economics since the contributions of Lewis (1954), Jorgenson (1961), and Ranis & Fei (1961) has been intimately concerned with agriculture and its connection 2 y Rich R* yR ()lA | AA,R , AI ,R Log Income per Capita P* y Poor yP ()lA | AA,P , AI ,P 0 l Rich l Poor 1 A Percent of Labor in Agriculture A Figure 2: Explanations for the Inverse Relationship of Income and Agric. to income levels. The dual economy theory suggests that, prima facie, factor market inefficiencies exist within the economy. This lowers overall productivity and income by allocating too many factors of production to the low productivity sector, typically agriculture. This paper brings the dual economy model into the development accounting framework and quantifies the effect that factor market inefficiency has on income levels and TFP variation across countries. Simply put, how important are dual economy effects for aggregate productivity? The answer to this question is intimately related to the inverse relationship of agriculture and income in figure 1. This can be seen more clearly in figure 2. In this diagram, points R∗ and P ∗ represent the observations of a rich, low-agriculture country (R) and a poor, high-agriculture country (P ).Each country is characterized by a two-sector economy (agriculture and industry) and their production functions are of the same form. For simplicity ignore any differences in capital endowments. One possible answer is characterized by the neoclassical growth model, in which the operation 3 of factor markets is bypassed completely by assuming there is only one sector.1 Accordingtothis model, countries differ in the relative productivity of agriculture and industry. Thus R∗ is the maximum point on yR (lA AA,R,AI,R) and P ∗ is the maximum point on yP (lA AA,P ,AI,P ).In | | country R, AI,R must be large relative AA,R and in P theoppositemustbetrue:AI,P is small relative to AA,P . This would account for the difference in labor shares in agriculture. To account for theincomedifference, though, it must also bethecasethatAI,R is large relative to AI,P . Variation in income and the inverse relationship with agriculture is driven primarily by differences in sectoral productivity levels. The dual economy, if it exists, exerts a negligible effect on productivity and income differences, as the poor economy does equate marginal products between sectors. The other possibility is that the inefficient factor markets in the dual economy have real, mea- surable effects.2 In figure 2 this is would be the case if both countries R and P are operating on yR (lA AA,R,AI,R), and again AI,R is large relative to AA,R. What separates countries R and P , | now, is that the rich country is maximizing income by equating marginal products between sectors, while P is poor because most of its people are in the low productivity agricultural sector. The differences in aggregate productivity and income between R and P are the result of factor market inefficiency, not differences in sector level productivity. This dual economy effect drives the inverse relationship of income and agriculture in this case. In this paper I use development accounting techniques to demonstrate that the macroeconomic evidence overwhelmingly supports the second possibility, that factor market inefficiency is a source of variation in aggregate TFP.3 Using data covering the period 1970 — 1990 that includes sector- 1 Included here as well are multi-sector growth models which explicitly incorporate factor markets, but generally do so under the assumption that these markets operate perfectly to equate marginal products across sectors. Reviewing only relatively recent work, papers by Matsuyama (1992), Laitner (2000), and Kongasmut, Rebelo & Xie (2001) all explore economic ramifications of the movement of labor between sectors, but do so assuming that wage rates are equalized across sectors. Unified growth models in Goodfriend & McDermott (1995) and Hansen & Prescott (2002) make use of the same assumptions, and Echevarria (1997) bypasses the issue by assuming a single optimizing agent in the economy. Kogel & Prskawetz (2001) construct a growth model in which agricultural workers are paid their average product, not their marginal, but do not explore the ramifications of this assumption. 2 There is a variety of evidence suggesting real inefficiencies in factor markets within countries. Banerjee & Duflo (2005) review a host of studies indicating that rates of return to the same factor vary widely within countries. From a macroeconomic perspective, the structural transformation research exemplified by Chenery & Syrquin (1975) and Chenery, Robinson & Syrquin (1986) as well as recent work by Caselli & Coleman (2001) and Temple & Woessmann (2004) examines how the reallocation of factors within an economy contributes to income growth. None of these studies, though, show how important these effects are in creating variation in income between countries. 3 There are, of course, other sources of inefficiency within economies. This paper does not deal with those sources explicity, and their effect will be captured within the residual TFP measures calculated by sector. 4 specific measures of physical capital and human capital I find that 30 — 40% of the variation in income per capita across countries is due to variation in the efficiency of their factor markets. These dual economy effects also explain up to 80% of the variation in aggregate TFP in my sample. Differences in sector level TFP are negligible in creating income differences between countries. This holds despite the fact that agricultural TFP levels vary greatly by country. The relatively small size of agriculture in total output, though, keeps this variation from being very meaningful. This paper is part of a growing literature examining the role of agriculture in the cross-country income distribution.4 Work by Gollin, Parente & Rogerson (2002) and Restuccia, Yang & Zhu (2003) explores the possibility that the combination of subsistence constraints and differences in agricultural TFP drive the income distribution. Restuccia (2004) and Graham & Temple (2003) create models in which the allocation of resources between sectors influences total factor productivity (TFP), and hence income. Their simulations show that these allocations can determine up to 50% of the variation in TFP between countries. Chanda & Dalgaard (2003) address the question more directly by doing a decomposition of aggregate TFP across countries. Their evidence suggests that up to 85% of the variation in aggregate TFP can be attributed to differences in the allocation of resources across sectors. These papers, though, do not deal explicitly with the question of the efficiency of factor markets within countries. The work of Cordoba & Ripoll (2004) does examine the wage gap between sectors specifically as a determinant of aggregate TFP differences. They find, as does this paper, that conventional measures of human capital by sector cannot account for the wide gaps in marginal product between sectors.
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