Do Higher Wages Reflect Higher Productivity? Education, Gender and Experience Premiums in a Matched Plant-Worker Data Set

Abstract

Do wage differences between workers with high and low levels of education, between males and females and between workers with different levels of experience reflect differences in productivity? We address this set of questions on the basis of a data set with variables for individual workers matched with a comprehensive data set for manufacturing plants in Norway for the period 1986-93. The results suggest that workers with higher education tend to be more productive, roughly in accordance to their wage premium. Female workers are cet par. found to be less productive than male workers, and this is reflected in their wages. Experienced workers are on average found to be more productive. For workers with 8 to 15 years of experience, the productivity premium exceeds the wage premium, while the opposite is the case for workers with more than 15 years of experience.

Are Older Workers Worthy of Their Pay? An Empirical Investigation of Age-Productivity and Age-Wage Nexuses

“…Using firm level data from Israel, they estimate Cobb-Douglas production functions augmented with the inclusion of the shares of workers in the young, prime-age and older age brackets, finding that the upward sloping age-wage profile mirrors the upward sloping ageproductivity profile. Similar results were obtained by Hellerstein, Neumark and Troske (1999), while Haegeland and Klette (1999) found that the wage premium for workers with higher experience (more than 15 years) exceeds their relative productivity, whereas the opposite is true for workers with 8 to 15 years of experience.…”

“…Both simply relate average wage and productivity levels to firm characteristics and the composition of its workforce. However, as also noted by Haegeland and Klette (1999) Similarly, van Ours and Stoeldraijer (2010) show that the productivity equation can be derived from a standard Cobb-Douglas production function augmented to include controls for firm-specific characteristics. Structural interpretation of the productivity equation is possible under the assumption that workers of different age groups are substitutes for each other, although their marginal productivity is allowed to differ (for details, see van Ours and Stoeldraijer, 2010).…”

“…As noted by Haegeland and Klette (1999) and Haltiwanger et al (1999), these two equations can be interpreted as simple descriptive equations with no behavioral content. Both simply relate average wage and productivity levels to firm characteristics and the composition of its workforce.…”

Age, Wage and Productivity in Dutch Manufacturing

“…To provide an idea about how this might affect our parameter estimates we discuss the results of similar studies which did have information about education, skills or experience of their employees. According to Haegeland and Klette (1999) there is a positive premium for all education levels for both wage and productivity. Wage returns to education correspond quite well to productivity differences.…”

“…The method used by Hellerstein et al (1999) is expanded by implementing panel data estimation which tries to remove some of the bias associated to OLS estimation of production functions. One of the first studies which uses matched employer-employee panel data is Haegeland and Klette (1999) who estimate plant level production functions using Norwegian data for the period 1986-1993. Their results indicate that the higher wages earned by workers with higher education largely correspond to their higher productivity.…”