Returns to on-the-job search and the dispersion of wages

A wide class of models with On-the-Job Search (OJS) predicts that workers gradually select into better-paying jobs. We develop a simple methodology to test predictions implied by OJS using two sources of identification: (i) time-variation in job-finding rates and (ii) the time since the last lay-off. Conditional on the termination date of the job, job duration should be distributed uniformly. This methodology is applied to the NLSY 79. We find remarkably strong support for all implications. The standard deviation of the wage offer distribution is about 15%. OJS accounts for 30% of the experience profile, 9% of total wage dispersion and an average wage loss of 11% following a lay-off

A job ladder model with stochastic employment opportunities

We set up a model with on-the-job search in which firms infrequently post vacancies for which workers occasionally apply. The model nests the standard job ladder and stock-flow models as special cases, while remaining analytically tractable and easy to estimate from standard panel data sets. The parameters from a structurally estimated model on US data are significantly different from either the restrictions imposed by a stock-flow or job ladder model. Imposing these restrictions significantly understates the search option associated with employment and are, unlike our model, inconsistent with recent survey evidence and declining job finding rates and starting wage with duration of unemployment, both of which are present in the data

Wage posting, nominal rigidity, and cyclical inefficiencies

We consider a Burdett/Mortensen style wage posting model with aggregate shocks. We analyze the equilibrium under two alternative assumptions on wage setting in ongoing jobs: either fully flexible or downwardly rigid. In the model firms optimally pay only retention premiums. The equilibrium is characterized by a Taylor expansion. The model yields two simultaneous relations for wages and quits, of which the parameters are simple functions of three empirically observable arrival rates of: (i) jobs, (ii) lay offs, and (iii) aggregate shocks. Hence, there are overidentifying restrictions, which are supported remarkably well by the data. We find strong evidence for wage downward rigidity and inefficiently low job-to-job transitions during the downturn. Furthermore, we find evidence that firms pay only retention premiums, not hiring premiums. A model with wage rigidity in ongoing jobs and OJS is therefore a useful benchmark for a wage equation in macro models. Under rigidity, job-to-job transitions are in efficiently low during the downturn

Essays on Models of the Labour Market with On-the-Job Search

In my first chapter, I provide a solution for how to model bargaining when there is on-the-job search and worker turnover depends on the wage. Bargaining is a standard feature in models without on-the-jobs search, but, due to endogeneity of the match surplus, a solution does not exist when worker turnover depends on the wage. My solution is based on wages being infrequently renegotiated. With renegotiation, the equilibrium wage distribution and the bargaining outcomes are both unique and the model nests earlier models in the literature as limit cases when wages are either continuously or never renegotiated. Furthermore, the rate of renegotiation has important implications for the nature of the equilibrium. A higher rate of renegotiation lowers the response of the match duration to a wage increase, which decreases a firm's willingness to accept a higher wage. This results in a lower share of the match surplus going to the worker. Moreover, a high rate of renegotiation also lowers the positive wage spillovers from a minimum wage increase, since these spillovers rely on firms' incentives to use higher wages to reduce turnover. In the standard job ladder model, search is modelled via an employment-specific Poisson rate. The size of the Poisson rate governs the size of the search friction. The Poisson rate can represent the frequency of applications by workers or the rate at which firms post suitable vacancies. In the second chapter, which is co-authored with Jake Bradley, we set up a model which has both of these aspects. Firms infrequently post vacancies and workers occasionally apply for these vacancies. The model nests the standard job ladder model and a version of the stock-flow model as special cases while remaining analytically tractable and easy to estimate empirically from standard panel data sets. The structurally estimated parameters are consistent with recent survey evidence of worker behavior. The model fits moments of the data that are inconsistent with the standard job ladder model and in the process reconciles the level of frictional wage dispersion in the data with replacement ratios used in the macro labor literature. In my third chapter, which is co-authored with Coen Teulings, we develop a simple method to measure the position in the job ladder in models with on-the-job search. The methodology uses two implications from models with on-the-job search: workers gradually select into better paying jobs until they get laid off at which time they start again to climb the job ladder. The measure relies on two sources of variation: (i) time-variation in job-finding rates and (ii) individual variation in the time since the last lay-off. We use the method to quantify the returns to on-the-job search and to establish the shape of the wage offer distribution by means of simple OLS regressions with wages as dependent variables. Moreover, we derive a simple prediction on the distribution of job durations. Applying the method to the NLSY 79, we find strong support for this class of models. We estimate the standard deviation of the wage offer distribution to be 12%. OJS accounts for 30% of the experience profile and 9% of the total wage dispersion