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Understanding Solow Residuals in Latin America
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Despite some improvements in recent years, long-term economic growth in Latin America and the Caribbean (LAC) has been rather disappointing over the past decades. Since 1960, gaps in the GDP per capita of LAC countries with respect to not only the United States but also their peers (“twin economies”) have widened steadily (see table 1). While the typical Latin American country1 was around 4.4 times poorer than the United States in 1960, as of 2008 it was 5.5 times poorer. The comparison with twin economies—countries that in 1960 had a GDP per capita comparable to that in Latin America2—is even more remarkable. The average LAC economy was just 20 percent poorer than its typical twin economy in 1960. In 2008, GDP per capita in Latin America was less than half that in the twin economies.


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Table 1. 

GDP per Capita in Latin America Relative to Benchmarksa

This persistent decline in relative GDP per capita has been common to all countries in the region, with some exceptions. Of the nineteen LAC economies in my sample, five managed to grow faster than the United States during the 1960–2008 period: Brazil, Chile, Colombia, the Dominican Republic, and Panama. However, progress has been quantitatively modest. For example, if benchmarked to twin economies, only the Dominican Republic and Panama managed to grow faster over the same period. Furthermore, in several cases (for example, Brazil) progress was made mainly during the 1960s and 1970s, with growth being subpar from the debt crisis in the early 1980s onward. While the 2000s have been good years in terms of relative growth performance for the region, it will still take around 27 years to cut by 50 percent the GDP per capita gap with respect to the United States if the growth differential during 2000–08 of around 1.5 percent per year is to be maintained; with respect to the twin economies, it will take around 108 years. Therefore, low potential growth continues to be a significant challenge for the region.

This paper contributes to the understanding of what drives this poor performance by using new databases and analytical tools to explore the relative importance of productivity and factor accumulation across LAC countries. With regard to analytical tools, the paper provides new evidence from three viewpoints. First, I perform a careful analysis of different ways of decomposing GDP per capita levels into physical capital, human capital, and a residual—the “Solow residual,” often interpreted as a measure of total factor productivity (TFP), representing aggregate economic efficiency, but also often viewed as “a measure of our ignorance”—under different assumptions regarding the production function and measurement. Second, I present non-parametric estimations of efficiency based on a data envelope analysis that does not rely on the traditionally used Cobb-Douglas production function; instead, it recognizes that the relevant production possibilities frontier may be a function of factor endowments and thus differ across countries. With regard to new data sets, this paper uses three newly available sources. First, in contrast to previous studies focusing on Latin America, it uses the new version of the Barro and Lee (2010) data set on educational attainment, which addresses several concerns on data quality that arose over the previous version (see Cohen and Soto 2007 as well as De la Fuente and Domenech 2006). Second, I also use the latest version of the Penn World Tables (version 7.0), extending the analysis until 2008; doing so allows me to cover the 2000s, a decade that has been quite successful for the region in terms of economic growth compared with its past. Third, I use the PISA 2009 test scores from the Organization for Economic Cooperation and Development (OECD) to analyze the importance of cognitive skills and adjust human capital indicators for differences in quality.

The paper focuses on the decomposition of GDP per worker into physical capital, human capital, and the Solow residual through the use of alternative methods, as policy recommendations might differ substantially according to the source of income disparities, in particular if policymakers have to establish priorities and have limited political capital to implement reforms. While recent work...



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