Abstract

We revisit the puzzling finding of negative time trends in empirical matching functions and investigate whether it simply arises from omitted variable bias. We consider three kinds of variables that are typically omitted from the matching function: job seekers beyond the unemployed, measures of inflows as opposed to stocks, and agents' selectivity. We first build a model of all labour market flows and use it to construct series for these flows from aggregate data on the U.S. labour market. Using these series, we obtain a measure for employed and non-participating job seekers. When we thus include all job seekers, the estimated time trend remains unchanged. We similarly obtain measures for inflows into unemployment and vacancies. When these are included, the magnitude of the time trend is halved. Including both the measures of inflows and all job seekers further reduces its magnitude. Indirect evidence suggests that these estimates are still affected by the omission of selectivity, which may explain the remainder of the negative time trend.