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How Credit Constraints Impact Job Finding Rates, Sorting & Aggregate Output*

January 2016

Working Paper Number:

CES-16-25

Abstract

We empirically and theoretically examine how consumer credit access affects dis- placed workers. Empirically, we link administrative employment histories to credit reports. We show that an increase in credit limits worth 10% of prior annual earnings allows individuals to take .15 to 3 weeks longer to find a job. Conditional on finding a job, they earn more and work at more productive firms. We develop a labor sorting model with credit to provide structural estimates of the impact of credit on employ- ment outcomes, which we find are similar to our empirical estimates. We use the model to understand the impact of consumer credit on the macroeconomy. We find that if credit limits tighten during a downturn, employment recovers quicker, but output and productivity remain depressed. This is because when limits tighten, low-asset, low- productivity job losers cannot self-insure. Therefore, they search less thoroughly and take more accessible jobs at less productive firms.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
economist, earnings, finance, labor, recession, job, estimates employment, borrower, lending, loan, bankruptcy, lender, borrowing, incentive, debt, employment dynamics, bankrupt, credit, unemployed, impact employment, recession employment

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:
Metropolitan Statistical Area, National Science Foundation, Ordinary Least Squares, Cobb-Douglas, Federal Reserve Bank, Survey of Income and Program Participation, University of Minnesota, Longitudinal Employer Household Dynamics, PSID, State Energy Data System

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