Using Firm-Level Data to Assess Gender Wage Discrimination in the Belgian Labour Market

In this paper we explore a matched employer-employee data set to investigate the presence of gender wage discrimination in the Belgian private economy labour market. We identify and measure gender wage discrimination from firm-level data using a labour index decomposition pioneered by Hellerstein and Neumark (1995), which allows us to compare direct estimates of a gender productivity differential with those of a gender labour costs differential. We take advantage of the panel structure of the data set and identify gender wage discrimination from within-firm variation. Moreover, inspired by recent developments in the production function estimation literature, we address the problem of endogeneity in input choice using a structural production function estimator (Levinsohn and Petrin, 2003). Our results suggest that there is no gender wage discrimination inside private firms located in Belgium.labour productivity; wages; gender discrimination; structural production function estimation; panel data

Disaggregating the Matching Function

The aggregate matching (hiring) function relates gross hires to labor market tightness. Decompositions of aggregate hires show how the hiring process differs across different groups of workers and of firms. Decompositions include employment status in the previous month, age, gender and education. Another separates hiring between part-time and full-time jobs, which show different patterns in the current recovery. Shift-share analyses are done based on industry, firm size and occupation to show what part of the residual of the aggregate hiring function can be explained by the composition of vacancies. The hiring process appears to shift as a recovery starts, coinciding with shifts in the Beveridge curve. The paper also discusses some issues in the modeling of the labor market

How Bad is Involuntary Part-Time Work?

We use a set of empirical and analytical tools to conduct parallel analyses of involuntary part-time work and unemployment in the U.S. labor market. In the empirical analysis, we document that the similar cyclical behavior of involuntary part-time work and unemployment masks major differences in the underlying dynamics. Unlike unemployment, variations in involuntary part-time work are mostly explained by its interaction with full-time employment, and since the Great Recession employed workers are at a greater risk of working part-time involuntarily than being unemployed. In the theoretical analysis, we show that the higher probability of regaining full-time employment is key to distinguish involuntary part-time work from unemployment from a worker's perspective. We also quantify the welfare costs of cyclical fluctuations in involuntary part-time work, and the amplification of these costs arising from the elevated levels of involuntary part-time work observed since the Great Recession

Mismatch Unemployment

We develop a framework where mismatch between vacancies and job seekers across sectors translates into higher unemployment by lowering the aggregate job-finding rate. We use this framework to measure the contribution of mismatch to the recent rise in U.S. unemployment by exploiting two sources of cross-sectional data on vacancies, JOLTS and HWOL, a new database covering the universe of online U.S. job advertisements. Mismatch across industries and occupations explains at most one-third of the total observed increase in the unemployment rate, whereas geographical mismatch plays no apparent role. The share of the rise in unemployment explained by occupational mismatch is increasing in the education level