Welfare Analysis Meets Causal Inference

Working Paper: NBER ID: w27640

Authors: Amy Finkelstein; Nathaniel Hendren

Abstract: We describe a framework for empirical welfare analysis that uses the causal estimates of a policy’s impact on net government spending. This framework provides guidance for which causal effects are (and are not) needed for empirical welfare analysis of public policies.The key ingredient is the construction of each policy’s marginal value of public funds (MVPF). The MVPF is the ratio of beneficiaries’ willingness to pay for the policy to the net cost to the government. We discuss how the MVPF relates to “traditional” welfare analysis tools such as the marginal excess burden and marginal cost of public funds. We show how the MVPF can be used in practice by applying it to several canonical empirical applications from public finance, labor, development, trade, and industrial organization.

Keywords: No keywords provided

JEL Codes: H0


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
MVPF framework (D79)causal effects of policy changes (E65)
marginal value of public funds of 1.50 (H49)benefits to beneficiaries (H55)
policy changes (J18)government spending (H59)
government spending (H59)welfare (I38)
causal estimates of policies (E65)cost assessments (O22)
behavioral responses (D91)government revenue (H27)
policy change (D78)behavioral responses (D91)

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