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.
|Date of creation:||Mar 2017|
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