Working Papers

Firm-Size Distribution and Cross-Country Income Differences

Published:June 1, 2007
Paper Released:May 2007
Authors:Laura Alfaro, Andrew Charlton and Fabio Kanczuk

Executive Summary:

Country-to-country differences in per-worker income are known to be enormous. Per capita income in the richest countries exceeds that in the poorest countries by more than a factor of 50. The consensus view in scholarly literature on development accounting is that two-thirds of these variations can be attributed to differences in efficiency or total factor productivity (TFP). Emerging research, however, suggests other possibilities. Alfaro and coauthors, applied a monopolistic competitive firm model to a new dataset of more than 20 million firms in nearly 80 developing and industrialized countries. They then calculated the extent to which differences in the misallocation of resources (as well as differences in the amount of physical and human capital resources) explain dispersion in income per worker. Their results suggest that misallocation of resources is a crucial determinant of income dispersion. Key concepts include:

  • Particular sources of inefficiency, such as credit market imperfections, macroeconomic volatility, defective bankruptcy procedures, or a malfunctioning regulatory environment, drive country-to-country differences in firm size distribution.
  • Misallocation of resources is a crucial determinant of income dispersion.

About Faculty in this Article:

HBS Faculty Member Laura Alfaro

Laura Alfaro is a professor in the Business, Government and the International Economy unit at Harvard Business School.

Author Abstract

We investigate, using a unique firm level dataset of nearly 20 million firms in 80 countries, whether differences in the allocation of resources across heterogeneous plants are a significant determinant of cross-country differences in income per worker. Using a monopolistic competitive firm framework to derive our benchmark calibration, we find that the model over-explains income variance. We further explore whether the results are driven by sample biases, calibration assumptions, or modeling choice. We find the same results prevail even in sub-samples in which the data are more reliable, and when we vary the calibration assumptions. This suggests the need for more complex modeling structures. Despite these acknowledged shortcomings, our results suggest that misallocation of resources is a crucial determinant of income dispersion.

Paper Information