The Linkage between Prices, Wages, and Labor Productivity: A Panel Study of Manufacturing Industries

1. IntroductionPolicy makers and financial analysts cite wage pressures and productivity gains as leading factors in explaining inflation. This cost-push explanation of inflation, however, is questioned by Mehra (1991, 1993, 2000), who shows that prices explain wages, but that wages are not a causal factor in determining inflation. Studies by Hu and Trehan (1995) and Gordon (1988, 1998) report evidence indicating that wage growth has no predictive content for inflation, rejecting the cost-push view. Emery and Chang (1996) and Hess (1999) demonstrate that these findings are sensitive to the sample period examined. Ghali (1999), using Granger-causality tests, finds that wage growth does help to predict inflation, supporting the cost-push view. A related but also relatively unexplored relationship is that between real wages and productivity. Although this link is the building block of many macroeconomic models and is frequently cited in intermediate macroeconomic textbooks, few empirical works have tested this relationship.1Recently, a large number of studies have begun testing long-standing macroeconomic hypotheses using panel unit-root and/or panel cointegration tests. However, few studies have employed industry-level panel data sets. The current article contributes to filling this void. It employs manufacturing industry data to evaluate the long-run dynamics between wages, prices, and productivity rather than the traditional approach of examining macroeconomic aggregates. More specifically, using annual four-digit industry-level data from the manufacturing sector over the period 1958-1996, this article examines the relationship between prices and wage-adjusted productivity as well as the linkage between productivity and real wages, using panel unit-root and cointegration estimation methods. The increased power and precision of the panel methods are particularly valuable in this context because they allow the researcher to more accurately test for the existence of a one-for-one cointegrating equilibrium between labor market variables and industry output prices. An additional objective of this article is to show the advantages and disadvantages of employing panel unit-root and cointegration tests. We demonstrate that the considerable heterogeneity of the data imply that the practitioner must be cautious in making inferences about the linkage between variables when using either pooling estimation methods or aggregate-level data. Our methodology accommodates for heterogeneity, by averaging coefficients, as well as examines outlier effects through quartile analysis. Heterogeneity of the cointegrating vector and cross-correlations are accommodated through analysis by industry of the extent of cointegration across the panel and Monte Carlo simulations that calculate correctly sized critical values.Our results suggest that a stable, long-run relationship exists between prices and wage-adjusted productivity as well as between real wages and productivity for many, but not all, industries. Both relationships, however, have considerably varied estimates and in most cases differ from the one-for-one linkage found by Mehra and others in aggregate-level data. Furthermore, Granger-causality tests support one-way causation from prices to per-unit labor costs (ULC) in both the short and the long run. Hence, the industry-level data reject the standard cost-push explanation of wage pressures contributing to inflation, supporting the aggregate-level findings of Mehra (1991, 1993, 2000) and others. Our findings suggest that prices may be driven more by demand-side factors than supply-side factors. Results further support bidirectional Granger causality in the long run between real wages and labor productivity. This implies that changes in real wages lead to productivity changes and is not inconsistent with the efficiency wage hypothesis. At the same time, productivity movements affect real wages, which is consistent with efficient labor markets. …