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  5. New Advances in Fiscal Policy
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New Advances in Fiscal Policy

Paper Session

Friday, Jan. 6, 2023 10:15 AM - 12:15 PM (CST)

Hilton Riverside, Chart B
Hosted By: American Economic Association
  • Chair: David Autor, Massachusetts Institute of Technology and NBER

An Evaluation of the Paycheck Protection Program Using Administrative Payroll Microdata

David Autor
,
Massachusetts Institute of Technology and NBER
David Ratner
,
Federal Reserve Board
David Cho
,
Federal Reserve Board
Leland D. Crane
,
Federal Reserve Board
Byron Lutz
,
Federal Reserve Board
Mita Goldar
,
City University of New York
Joshua Montes
,
Federal Reserve Board
William B. Peterman
,
Federal Reserve Board
Daniel Villar Vallenas
,
Federal Reserve Board
Ahu Yildirmaz
,
ADP

Abstract

The Paycheck Protection Program (PPP), a principal element of the fiscal stimulus enacted by Congress in response to the COVID-19 economic shock, is intended to assist small businesses to maintain employment and wages during the crisis. An obstacle to assessing whether the PPP achieved this goal is the absence of granular, high-frequency employment data that can precisely capture any causal effect of the PPP on employment. We use administrative data from ADP—one of the world’s largest payroll processing firms—to contrast the evolution of payroll employment at PPP-eligible and PPP-ineligible firms, where eligibility is determined by industry-specific firm-size cutoffs. We estimate that the PPP boosted employment at eligible firms by 2 to 4.5 percent, with a preferred central tendency estimate of approximately 3.25 percent. Our estimates imply that the PPP increased aggregate U.S. employment by 1.4 million to 3.2 million jobs through the first week of June 2020, with a preferred central tendency estimate of about 2.3 million workers. In an alternative analysis, we identify the effect of the PPP from a set of firms for which we can observe loan take-up and obtain results at the upper end of the range of estimates. Although the evidence is supportive of a causal effect of the PPP on aggregate employment, we are careful to highlight puzzles where they occur and view our work as preliminary in nature. Future work will leverage loan-level PPP data to calibrate the relationship between eligibility, take-up, and employment.

Fiscal Policy and Households’ Inflation Expectations: Evidence from a Randomized Control Trial

Olivier Coibion
,
University of Texas at Austin and NBER
Yuriy Gorodnichenko
,
University of California-Berkeley and NBER
Michael Weber
,
University of Chicago and NBER

Abstract

Rising government debt levels around the world are raising the specter that authorities might seek to inflate away the debt. In theoretical settings where fiscal policy “dominates” monetary policy, higher debt without offsetting changes in primary surpluses should lead households to anticipate this higher inflation. Are household inflation expectations sensitive to fiscal considerations in practice? We field a large randomized control trial on U.S. households to address this question by providing randomly chosen
subsets of households with information treatments about the fiscal outlook and then observing how they revise their expectations about future inflation as well as taxes and government spending. We find that information about the current debt or deficit levels has little impact on inflation expectations but that news about future debt leads them to anticipate higher inflation, both in the short run and long run. News about rising debt also induces households to anticipate rising spending and a higher rate of interest for
government debt.

Do Analysts Act On Fiscal Spending?

Nancy Xu
,
Boston College
Yang You
,
University of Hong Kong

Abstract

We document that actual fiscal distributions from the Federal government to firms are undetected in analyst forecasts of firm earnings. We first construct a transaction-level procurement contract database for all transactions using data from a publicly-accessible government website. Using a final sample consisting of 1239 public firms between 2008Q1 and 2022Q3, we find that a one standard deviation (SD) increase in the log transaction amount -- especially across firms -- significantly predicts an around 2.6%-3.9% higher chance of the actual earnings per share beating the median forecast, a 0.10 SD increase in earnings surprise, and an increase in daily returns of 10.36 basis points on earnings announcement day. Consistent with a missing information mechanism, the earnings surprise predictability significantly weakens for (a) firms with more forecasts, (b) firms whose analysts ask more questions about and show more interest in government contracts during conference calls, and (c) periods with active fiscal debates -- all situations in which analysts might have access to better information about government contracts. Finally, a long-short portfolio based on firms’ government contract transaction amounts earns 87 (35) basis points per month among small (all) firms; cash flow information about public procurement from small firms should be less known to the market, which explains their current under-pricing.

Discussant(s)
André Kurmann
,
Drexel University
Eric M. Leeper
,
University of Virginia
Dongho Song
,
Johns Hopkins University
JEL Classifications
  • E6 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
  • H3 - Fiscal Policies and Behavior of Economic Agents