Replication data for: Unemployment Insurance Fraud and Optimal Monitoring
Principal Investigator(s): View help for Principal Investigator(s) David L. Fuller; B. Ravikumar; Yuzhe Zhang
Version: View help for Version V1
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Project Citation:
Fuller, David L., Ravikumar, B., and Zhang, Yuzhe. Replication data for: Unemployment Insurance Fraud and Optimal Monitoring. Nashville, TN: American Economic Association [publisher], 2015. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E114076V1
Project Description
Summary:
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An important incentive problem for the design of unemployment insurance is the fraudulent collection of unemployment benefits by workers who are gainfully employed. We show how to efficiently use a combination of tax/subsidy and monitoring to prevent such fraud. The optimal policy monitors the unemployed at fixed intervals. Employment tax is nonmonotonic: it increases between verifications but decreases after a verification. Unemployment benefits are relatively flat between verifications but decrease sharply after a verification. Our quantitative analysis suggests that the optimal monitoring cost is 60 percent of the cost in the current US system. (JEL D82, H24, J64, J65)
Scope of Project
JEL Classification:
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D82 Asymmetric and Private Information; Mechanism Design
H24 Personal Income and Other Nonbusiness Taxes and Subsidies; includes inheritance and gift taxes
J64 Unemployment: Models, Duration, Incidence, and Job Search
J65 Unemployment Insurance; Severance Pay; Plant Closings
D82 Asymmetric and Private Information; Mechanism Design
H24 Personal Income and Other Nonbusiness Taxes and Subsidies; includes inheritance and gift taxes
J64 Unemployment: Models, Duration, Incidence, and Job Search
J65 Unemployment Insurance; Severance Pay; Plant Closings
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