The $900 Billion Paycheck Protection Program: Can a Self-Targeted Relief Program Achieve Optimal Allocation? Open Access

Chan, Daryl (Spring 2022)

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What happens when governments rely on self-targeted relief programs to mitigate an economic fallout? I study the Paycheck Protection Program (PPP), a large and unprecedented small business loan program enacted as a response to the COVID-19 crisis in the U.S. with the goal of preserving jobs. The program was self-targeted by nature and small businesses regardless of need can apply. This paper assesses the extent to which governments can rely on firms to self-select into these programs based on the government's objective of preserving jobs. I show using a theoretical model that firm optimal behaviour is asymmetric to government objective, and the design of the PPP does not skew to firms that would layoff the most employees. Empirical analysis shows some evidence of self-targeting by firms in the early days of the program, but the effect was marginal and eventually neutralized as the pandemic progressed. I estimate that only 30% of total grants provided to businesses reached the government's desired objective and allowed for full employment restoration, while at least 17% of grants had close to no effect on employment. With the need of delivering aid to businesses quickly in mind, this paper suggests that the efficiency of PPP would greatly increase with some "low-cost" targeting based on need and the implementation of an ordeal mechanism to discourage resilient firms from applying.

Table of Contents

Introduction (Page 1) Basics of the Paycheck Protection Program (Page 5) Model (Page 9) Setup (Page 9) Empirical Evidence (Page 19) Data (Page 19) First Stage of Self-Targeting: Applying (Page 19) Second Stage of Self-Targeting: Loan Forgiveness (Page 31) Discussion (Page 35)

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