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Brookings Trade Forum 2006 (2006) 97-127

Wage Dynamics and Economic Development
Andrew M. Warner
Millennium Challenge Corporation
[Comments and Discussion]

The primary purpose of this paper is to introduce new data on wages by occupations across fifty-eight countries. The main distinguishing feature of the data is that they were collected with exactly the same methodology at the same time in many countries, thus permitting a high degree of comparability across countries. The data are from surveys of firms, which ask what the firm pays for broad occupational categories, such as office cleaners, secretaries, and managers.

The second purpose of the paper is to show empirical evidence from a number of sources on how wage levels correlate with GDP and to interpret this evidence. Various sources of wage data are compared through this lens, both across countries and across time within countries. The paper discusses conditions under which wage growth should keep pace with GDP growth and shows econometric evidence on the determinants of wage levels across countries.

This paper begins by showing figures of wages plotted against GDP per worker or GDP per person using a variety of wage data. GDP is used as a common denominator against which wages can be displayed for a variety of occupations across time and across countries. Such plots, however, inevitably provoke criticism: "Of course wages correlate with GDP, since wages are by definition part of GDP." The answer is yes, but not so fast. Among the variables that can break the link between wage levels and GDP are changing participation rates of the labor force, shifting employment between sectors with different wage levels, and changes in the share of labor income in GDP.

The paper shows that after these forces play themselves out, simple elasticities between log wage levels and log GDP per worker or log GDP per capita tend to lie in the range 0.6 to 1.0. Some of the wage data presented in this paper show a 1-for-1 elasticity, and some of the regression results show a partial 1-for-1 association after holding constant other variables. [End Page 97]

The paper presents econometric evidence to shed light on the forces that drive wage levels around the world. These regressions deal with two methodological issues that need to be confronted by any empirical study of wages and GDP across countries: the bias toward 1 from the fact that wages are part of GDP and the simultaneous determination of wage levels and GDP levels. The paper deals with both issues by using the capital-labor ratio as the driving force behind the determination of wages and GDP. This variable is used both as an instrument for GDP and directly in the estimated wage equations.

Some of the important factors found to mediate the wage-GDP relationship are the extent of skill accumulation during growth; the degree of structural change during growth; and, when the wage data are for specific occupations or industries, special factors associated with those occupations or industries. The paper also shows evidence about the role of labor market policies, market competition, and global forces. The paper is organized as follows. The first section discusses the existing wage data. The second section describes the new fifty-eight-country occupational wage data. The third section reviews related studies on wages. The fourth section discusses the evidence on the association between wages and GDP using a variety of data. And the final two sections present and discuss regression evidence in a more formal setting.

Data on Wages

Until very recently, wage data from different countries were characterized by a low degree of comparability due to differences in the way occupations were classified and wages were measured (sources varied in terms of inclusion of bonuses, in-kind benefits, and pension and insurance contributions). Also data on wages outside of the manufacturing sector were lacking, which is a significant issue because manufacturing can make up a small share of GDP. Data from the 2006 edition of World Development Indicators show that for 1998 the median share...


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pp. 97-127
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Archived 2012
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