Labor Market Heterogeneity and the Aggregate Matching Function

Abstract

The matching function -a key building block in models of labor market frictions-implies that the job …nding rate depends only on labor market tightness. We estimate such a matching function and …nd that the relation, although remarkably stable over 1967-2007, broke down spectacularly after 2007. We argue that labor market heterogeneities are not fully captured by the standard matching function, but that a generalized matching function that explicitly takes into account worker heterogeneity and market segmentation is fully consistent with the behavior of the job …nding rate. The standard matching function can break down when, as in the Great Recession, the average characteristics of the unemployed change too much, or when dispersion in labor market conditions -the extent to which some labor markets fare worse than others-increases too much.JEL classi…cations: J6, E24, E32.

Heterogeneity and Unemployment Dynamics

“…A number of researchers have tried to investigate this hypothesis by looking at di¤erences across job seekers in observable characteristics such as demographics, education, industry, occupation, geographical region, and reason for unemployment. Baker (1992), Shimer (2012), and Kroft, Lange, Notowidigdo, and Katz (forthcoming) found that such variables contributed little to variation over time in long-term unemployment rates, while Aaronson, Mazumder and Schechter (2010), Bachmann and Sinning (2012), Barnichon and Figura (2015), Hall (2014), and Hall and Schulhofer-Wohl (2015) documented important di¤erences across observable characteristics. Elsby, Michaels and Solon (2009) found that incorporating observable heterogeneity reduced the imputed role of cyclical variation in unemployment exit rates.…”

Population Aging, Migration Spillovers, and the Decline in Interstate Migration

“…Following the Great Recession, several recent papers study the interactions between the housing market, gross and net worker geographic reallocation, and geographic mismatch. Some examples include Aaronson and Davis (2011), Barnichon and Figura (2011), Valletta (2013), Ferreira et al (2012, Schulhofer-Wohl (2011), Sahin et al (2012, Modestino and Dennett (2013), , Nenov (2012), and Karahan and Rhee (2013).…”

Heterogeneity and Unemployment Dynamics

“…A number of researchers have tried to investigate this hypothesis by looking at differences across job seekers in observable characteristics such as demographics, education, industry, occupation, geographical region, and reason for unemployment. Baker (1992), Shimer (2012), and Kroft, Lange, Notowidigdo, and Katz (2014) found that such variables contributed little to variation over time in long-term unemployment rates, while Aaronson, Mazumder and Schechter (2010), Bachmann and Sinning (2012), Barnichon and Figura (2013), Hall (2014), and Hall and Schulhofer-Wohl (2014) documented important differences across observable characteristics. Elsby, Michaels and Solon (2009) found that incorporating observable heterogeneity reduced the imputed role of cyclical variation in unemployment exit rates.…”