Are Sufficient Statistics Necessary? Nonparametric Measurement of Deadweight Loss from Unemployment Insurance

Central to the welfare analysis of income transfer programs is the deadweight loss associated with possible reforms. To aid analytical tractability, its measurement typically requires specifying a simplified model of behavior. We employ a complementary “decomposition” approach that compares the beha...

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Bibliographic Details
Published in:Journal of labor economics 2021-04, Vol.39 (S2), p.S455-S506
Main Authors: Lee, David S., Leung, Pauline, O’Leary, Christopher J., Pei, Zhuan, Quach, Simon
Format: Article
Language:English
Subjects:
Earnings
Insurance policies
Labor economics
Measurement
Nonparametric statistics
Quasi-experimental methods
Taxation
Unemployment insurance
Welfare
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Summary:Central to the welfare analysis of income transfer programs is the deadweight loss associated with possible reforms. To aid analytical tractability, its measurement typically requires specifying a simplified model of behavior. We employ a complementary “decomposition” approach that compares the behavioral and mechanical components of a policy’s total impact on the government budget to study the deadweight loss of two unemployment insurance policies. Experimental and quasi-experimental estimates using state administrative data show that increasing the weekly benefit is more efficient (with a fiscal externality of 53 cents per dollar of mechanical transferred income) than reducing the program’s implicit earnings tax.
ISSN:0734-306X
1537-5307
DOI:10.1086/711594