M. Daniele Paserman

Professor of Economics

Department of Economics, Boston University

NLS user since 1995

Citations
  • “Job Search and Impatience,” (with Stefano DellaVigna). Journal of Labor Economics, 23(3), July 2005, pages 527-588.
  • “Job Search and Hyperbolic Discounting: Structural Estimation and Policy Implications.” Economic Journal, 118(531), August 2008, pages 1418-1452.
What I learned from NLS data

The NLS has helped to uncover important facts about the job search process: how it is affected by individual preferences about intertemporal discounting, and how active search effort and reservation wages affect the probability of finding a job.

By using the NLS for my teaching, I have also learned many additional facts about the labor market (recent example: controlling for actual work experience rather than potential experience does almost nothing to reduce the gender gap in wages -- this was a very surprising result!)

Why I chose NLS data

The richness of the data, the possibility to construct a variety of measures of individual preferences, to control for cognitive ability, and to track the same individuals (and their children) over an entire lifetime.