The Impact of Consumer Credit Constraints on Earnings, Sorting, and Job Finding Rates of Displaced Workers

Earnings losses after layoff are severe on average and differ significantly across individuals (Jacobson et al. [1993], Jacobson et al. [2005], Couch and Placzek [2010], Davis and von Wachter [2011]). While much is known empirically and theoretically about the impact of unemployment benefits on earnings losses (Ljungqvist and Sargent [1998], Saporta-Eksten [2013]), little is known about the role consumer credit plays in the earnings losses of displaced workers, their job finding rates, and the subsequent quality of jobs they take. To answer this question, we merged confidential, quarterly, individual employment records from the Census with proprietary individual credit reports based on social security numbers. Our first contribution is to use this new administrative panel dataset to measure the impact of consumer credit access on job finding rates and re-employment earnings of displaced workers. We find that credit constrained workers have earnings losses that are [X]% greater than unconstrained households, and that the job finding rates of credit constrained workers are [X]% greater then unconstrained households. To understand the impact of credit access on sorting, employment, output, and productivity, we introduce risk aversion into a model with heterogeneous workers and firms, building on the influential prior work by Eeckhout and Kircher [2010], Eeckhout and Kircher [2011] and Hagedorn et al. [2012]. In our model, heterogeneous credit-constrained workers accumulate human capital while working and direct their search for jobs among heterogeneous credit-constrained firms while unemployed. We find that an increase in credit limits equal to [X]% of GDP (decreases or) increases employment by [X]%, increases output by [X]%, and increases productivity by [X]%. The mechanism is that credit access acts as a safety net, allowing workers to sort into better matches with firms.