Estimating Returns to Scale with Large, Imperfect Panels: An Application to Chilean Manufacturing Industries

Abstract

This study exploits plant-level panel data from Chile to provide new evidence on the empirical significance of scale economies in manufacturing sectors. Particular emphasis is given to econometric problems induced by the presence of unobservable plant heterogeneity, measurement error, and selectivity. An analysis of the results suggests that estimates based on generalized method of moments (GMM) estimators that pool long differences (which eliminate heterogeneity effects) are robust to measurement error in the capital stock, heteroscedasticity, and selectivity. Returns to scale for three-digit industries are fairly evenly distributed over the plausible range of 0.8 to 1.2, and none is statistically significantly different from constant returns. Similar results hold for the four-digit industries for which sufficient data are available. Although general expansion of the manufacturing sector cannot be expected to yield strong plant-level scale economies, our results do not rule out scale economies from other sources, such as the spreading of start-up costs and external returns to scale. Finally, the analysis has generated severalfindings of methodological interest, including the notion that Stigler's survival test may indeed be useful as a quick first pass on the empirical importance of returns to scale. Domestic markets for industrial products are often small in developing countries. Accordingly, scale economies in manufacturing sectors can critically influence market structures, growth prospects, and trading patterns. Although the potential importance of these effects has long been recognized by students of development, there has been very little convincing research on their empirical significance. Berry (1992) and Bhagwati (1988) share the concern of Rodrik (1988), who notes that "there is practically no direct evidence on the importance of scale economies in specific industrial sectors of the developing countries." In M. Daniel Westbrook and James R. Tybout are in the Department of Economics at Georgetown University. This article was prepared for the World Bank research project "Industrial Competition, Productive Efficiency, and Their Relation to Trade Regimes" RPO 674-46. The authors are grateful to John Cuddington, Zvi Griliches, three anonymous referees, and participants in workshops at the National Bureau of Economic Research and at Georgetown for their comments.

Crowding-out and crowding-in effects of the components of government expenditure

“…vi Another method of excluding unobserved country-specific variables estimates the first-differenced regression (see Hsiao, 1986, andWestbrook andTybout, 1993 We further note that the expenditure data from the Government Financial Statistics include both current and capital spending. We divide the variables by GDP to calculate GDP shares.…”

The Effects of Overseas Operations on Home Employment of Japanese Multinational Enterprises

“…The first-difference estimator provides the better treatment for the endogenity problem, which is common to the firm-level data, as compared to the withintransformation estimator (Westbrook and Tybout 1993). However, the first-difference 15 7 Complied from the online database at http://www.boj.or.jp/type/stat/dlong/price/cgpi/index.htm 8 They are available for the following industries, textile products, iron and steel, non-ferrous metals, metal products, general machinery, electrical machinery, transport equipment, precision instruments, and other manufacturing industry products.…”

“…Failing to take them into account might lead to permanent observable differences in output, employment and wages (Westbrook and Tybout 1993). Additionally, industryspecific effects take into account for industry-wide technological shocks.…”

Economies of Scale: A Survey of the Empirical Literature

“…With the exception of machine tool manufacturing no InEOS could be found once technical efficiency was controlled for by the average experience of the labor force, the age of the capital stock, the experience of the entrepreneur and the level of capacity utilization. Scherer (1980, p. 92 Panel data analyses that have been used by Westbrook and Tybout (1993) and Tybout and Westbrook (1992) to analyze scale effects in Chilean and Mexican manufacturing firms of different three digit industries. Westbrook and Tybout (1993) find returns to scale to vary between 0.8 and 1.2 between different industries.…”

“…Scherer (1980, p. 92 Panel data analyses that have been used by Westbrook and Tybout (1993) and Tybout and Westbrook (1992) to analyze scale effects in Chilean and Mexican manufacturing firms of different three digit industries. Westbrook and Tybout (1993) find returns to scale to vary between 0.8 and 1.2 between different industries.…”