TY - JOUR AU - Hornstein,Andreas AU - Krusell,Per AU - Violante,Giovanni L. TI - Frictional Wage Dispersion in Search Models: A Quantitative Assessment JF - National Bureau of Economic Research Working Paper Series VL - No. 13674 PY - 2007 Y2 - November 2007 UR - http://www.nber.org/papers/w13674 L1 - http://www.nber.org/papers/w13674.pdf N1 - Author contact info: Andreas Hornstein Research Department Federal Reserve Bank of Richmond POB 27622 Richmond, VA 23261-7622 E-Mail: Andreas.Hornstein@rich.frb.org Per Krusell Institute for International Economic Studies Stockholm University 106 91 STOCKHOLM SWEDEN E-Mail: per.krusell@iies.su.se Giovanni L. Violante Department of Economics New York University 19 W. 4th Street New York, NY 10012-1119 Tel: 212/992-9771 Fax: 212/995-3932 E-Mail: glv2@nyu.edu AB - Standard search and matching models of equilibrium unemployment, once properly calibrated, can generate only a small amount of frictional wage dispersion, i.e., wage differentials among ex-ante similar workers induced purely by search frictions. We derive this result for a specific measure of wage dispersion -- the ratio between the average wage and the lowest (reservation) wage paid. We show that in a large class of search and matching models this statistic (the "mean-min ratio") can be obtained in closed form as a function of observable variables (i.e., the interest rate, the value of leisure, and statistics of labor market turnover). Various independent data sources suggest that actual residual wage dispersion (i.e., inequality among observationally similar workers) exceeds the model's prediction by a factor of 20. We discuss three extensions of the model (risk aversion, volatile wages during employment, and on-the-job search) and find that, in their simplest versions, they can improve its performance, but only modestly. We conclude that either frictions account for a tiny fraction of residual wage dispersion, or the standard model needs to be augmented to confront the data. In particular, the last generation of models with on-the-job search appears promising. ER -