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

Working Paper: NBER ID: w25574

Authors: David S. Lee; Pauline Leung; Christopher J. O'Leary; Zhuan Pei; Simon Quach

Abstract: 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.

Keywords: Unemployment Insurance; Fiscal Externality; Deadweight Loss

JEL Codes: C14; C20; C31; H2; H23; J64; J65; J68


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Traditional sufficient statistics approach (C29)Overestimate of fiscal externality (D62)
Increasing the weekly benefit amount (J65)Fiscal externality of 53 cents per dollar of mechanical transferred income (H29)
Reducing the implicit earnings tax (H31)Fiscal externality of 138 cents per dollar (H29)
Behavioral response to an increase in benefits (D91)Higher total payments to claimants (J33)
Behavioral response to an increase in benefits (D91)No significant effect on earnings (J31)
Behavioral response (D91)Fiscal externality related to benefit payments (H29)
Behavioral response (D91)Fiscal externality related to tax receipts (H29)

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