Job Search and Unemployment Insurance: New Evidence from Time Use Data
Alan Krueger and
Andreas Mueller
No 3667, IZA Discussion Papers from Institute of Labor Economics (IZA)
Abstract:
This paper provides new evidence on job search intensity of the unemployed in the U.S., modeling job search intensity as time allocated to job search activities. The main findings are: 1) the average unemployed worker in the U.S. devotes about 41 minutes to job search on weekdays, which is substantially more than his or her European counterpart; 2) workers who expect to be recalled by their previous employer search substantially less than the average unemployed worker; 3) across the 50 states and D.C., job search is inversely related to the generosity of unemployment benefits, with an elasticity between -1.6 and -2.2; 4) the predicted wage is a strong predictor of time devoted to job search, with an elasticity in excess of 2.5; 5) job search intensity for those eligible for Unemployment Insurance (UI) increases prior to benefit exhaustion; 6) time devoted to job search is fairly constant regardless of unemployment duration for those who are ineligible for UI. A nonparametric Monte Carlo technique suggests that the relationship between job search effort and the duration of unemployment for a cross-section of job seekers is only slightly biased by length-based sampling.
Keywords: job search; unemployment insurance; unemployment; time use; unemployment benefits; inequality (search for similar items in EconPapers)
JEL-codes: J64 J65 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2008-08
New Economics Papers: this item is included in nep-ias, nep-lab and nep-ltv
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Citations: View citations in EconPapers (31)
Published - published in: Journal of Public Economics, 2010, 94 (3-4), 298-307
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Related works:
Journal Article: Job search and unemployment insurance: New evidence from time use data (2010) 
Working Paper: Job Search and Unemployment Insurance: New Evidence from Time Use Data (2008) 
Working Paper: Job Search and Unemployment Insurance: New Evidence from Time Use Data (2008) 
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