Comments and Discussion

The past decade has seen an explosion of empirical research on economic growth and its determinants, yet many of the central issues of interest remain unresolved. For instance, no consensus has emerged about the relative contributions of capital accumulation and improvements in total factor productivity in accounting for differences in growth across countries and time. Nor is there agreement about the role of increased education or the importance of economic policy. Indeed, results from the many studies on a given issue frequently reach opposite conclusions. And two of the main empirical approaches—growth accounting and growth regressions—have themselves come under attack, with some researchers going so far as to label them as irrelevant to policymaking.

In this paper we argue that, properly implemented and interpreted, both growth accounts and growth regressions are valuable tools, which can improve—and have improved—our understanding of growth experiences across countries. We also show that careful attention to issues of measurement and consistency goes a long way in explaining the apparent contradictions among findings in the literature. Our analysis combines growth accounts and growth regressions with a focus on measurement and procedural consistency to address the issues raised. The growth accounts are constructed for eighty-four countries that together represent 95 percent of gross world product and 84 percent of world population, over a period of forty years from 1960 to 2000. Appendix A lists the countries in the sample by region.¹ This large data set also enables us to compare growth experiences across two twenty-year time periods: 1960–80 and 1980–2000.

Understanding the characteristics and determinants of economic growth requires an empirical framework that can be applied to large groups of countries over a relatively long period. Growth accounts and growth regressions provide such frameworks in a way that is particularly informative because the two approaches can be used in concert, enabling researchers to explore the channels (factor accumulation versus increased factor productivity) through which various determinants influence growth. Although the information thus provided is perhaps best considered descriptive, it can generate important insights that complement those gained from in-depth case studies of selected countries, or from estimation of carefully specified econometric models designed to test specific hypotheses.

Growth accounts provide a means of allocating observed output growth between the contributions of changes in factor inputs and a residual, total factor productivity (TFP), which measures a combination of changes in efficiency in the use of those inputs and changes in technology. These accounts are used extensively within the industrial countries to evaluate the sources of change in productivity growth, the role of information technology, and differences in the experience of individual countries.² In his recent, comprehensive assessment, Charles Hulten aptly describes the approach as “a simple and internally consistent intellectual framework for organizing data. . . . For all its flaws, real and imagined, many researchers have used it to gain valuable insights into the process of economic growth.”³

Despite its extensive use within the industrial countries, growth accounting has done surprisingly little to resolve some of the most fundamental issues under debate in the development literature. For example, the major objective of growth accounting is to distinguish the contribution of increased capital per worker from that of improvements in factor productivity. Yet one can observe widely divergent views on this issue, with some researchers claiming that capital accumulation is an unimportant part of the growth process and others that it is the fundamental determinant of growth.

Criticism of growth accounting has been concentrated in three areas. The first focuses on the fact that TFP is measured as a residual. As discussed in detail by Hulten, this residual provides a measure of gains in economic efficiency (the quantity of output that can be produced with a given quantity of inputs), which can be thought of as shifts in the production function. But such shifts reflect myriad determinants, in addition to technological innovation, that influence growth but that the measured increases in factor inputs do not account for. Examples include the implications of sustained political turmoil, external shocks, changes in...