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The Politics of the Paycheck Protection Program

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  • Lambert, Thomas
  • Mishra, Prachi

Abstract

This paper examines the incidence of special interests in the allocation of loans through the Paycheck Protection Program (PPP). We find that lobbying at the firm and industry levels helps obtain larger PPP loans during the pandemic. We also observe that PPP lending is more responsive to lobbying in ideologically less conservative areas as well as in industries less affected by the pandemic. Our findings are consistent with the notion that lobbying firms have experience in navigating administrative and policy complexity and can thus benefit more from aid provided under the PPP.

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  • Lambert, Thomas & Mishra, Prachi, 2021. "The Politics of the Paycheck Protection Program," CEPR Discussion Papers 16842, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:16842
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    1. Kempf, Elisabeth & Luo, Mancy & Schäfer, Larissa & Tsoutsoura, Margarita, 2023. "Political ideology and international capital allocation," Journal of Financial Economics, Elsevier, vol. 148(2), pages 150-173.
    2. Morris H. DeGroot & Julia Mortera, 1991. "Optimal Linear Opinion Pools," Management Science, INFORMS, vol. 37(5), pages 546-558, May.
    3. Engelberg, Joseph & Manski, Charles F. & Williams, Jared, 2009. "Comparing the Point Predictions and Subjective Probability Distributions of Professional Forecasters," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 30-41.
    4. Diebold, Francis X. & Shin, Minchul & Zhang, Boyuan, 2023. "On the aggregation of probability assessments: Regularized mixtures of predictive densities for Eurozone inflation and real interest rates," Journal of Econometrics, Elsevier, vol. 237(2).
    5. Bartlett, Robert P. & Morse, Adair, 2021. "Small-Business Survival Capabilities and Fiscal Programs: Evidence from Oakland," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(7), pages 2500-2544, November.
    6. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    7. Del Negro, Marco & Hasegawa, Raiden B. & Schorfheide, Frank, 2016. "Dynamic prediction pools: An investigation of financial frictions and forecasting performance," Journal of Econometrics, Elsevier, vol. 192(2), pages 391-405.
    8. Dingel, Jonathan I. & Neiman, Brent, 2020. "How many jobs can be done at home?," Journal of Public Economics, Elsevier, vol. 189(C).
    9. Coibion, Olivier & Gorodnichenko, Yuriy & Weber, Michael, 2020. "Political Polarization and Expected Economic Outcomes," IZA Discussion Papers 13823, Institute of Labor Economics (IZA).
    10. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    11. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    12. Laurent Bouton & Julia Cagé & Edgard Dewitte & Vincent Pons, 2021. "Small Campaign Donors," SciencePo Working papers Main hal-03878175, HAL.
    13. repec:cdl:econwp:qt9h51c373 is not listed on IDEAS
    14. Francis X. Diebold & Anthony S. Tay & Kenneth F. Wallis, 1997. "Evaluating Density Forecasts of Inflation: The Survey of Professional Forecasters," NBER Working Papers 6228, National Bureau of Economic Research, Inc.
    15. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
    16. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December.
    17. Duchin, Ran & Hackney, John, 2021. "Buying the Vote? The Economics of Electoral Politics and Small-Business Loans," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(7), pages 2439-2473, November.
    18. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    19. Federico Bassetti & Roberto Casarin & Francesco Ravazzolo, 2018. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 675-685, April.
    20. Sergey Chernenko & Nathan Kaplan & Asani Sarkar & David S. Scharfstein, 2023. "Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program?," NBER Working Papers 31172, National Bureau of Economic Research, Inc.
    21. Keane, Michael P & Runkle, David E, 1990. "Testing the Rationality of Price Forecasts: New Evidence from Panel Data," American Economic Review, American Economic Association, vol. 80(4), pages 714-735, September.
    22. Autor, David & Cho, David & Crane, Leland D. & Goldar, Mita & Lutz, Byron & Montes, Joshua & Peterman, William B. & Ratner, David & Villar, Daniel & Yildirmaz, Ahu, 2022. "An evaluation of the Paycheck Protection Program using administrative payroll microdata," Journal of Public Economics, Elsevier, vol. 211(C).
    23. Graham Elliott & Dalia Ghanem & Fabian Krüger, 2016. "Forecasting Conditional Probabilities of Binary Outcomes under Misspecification," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 742-755, October.
    24. Emir Shuford & Arthur Albert & H. Edward Massengill, 1966. "Admissible probability measurement procedures," Psychometrika, Springer;The Psychometric Society, vol. 31(2), pages 125-145, June.
    25. Elisabeth Kempf & Margarita Tsoutsoura, 2021. "Partisan Professionals: Evidence from Credit Rating Analysts," Journal of Finance, American Finance Association, vol. 76(6), pages 2805-2856, December.
    26. Sumit Agarwal & Gene Amromin & Itzhak Ben‐David & Serdar Dinc, 2018. "The Politics of Foreclosures," Journal of Finance, American Finance Association, vol. 73(6), pages 2677-2717, December.
    27. Matthieu Chavaz & Andrew K Rose, 2019. "Political Borders and Bank Lending in Post-Crisis America," Review of Finance, European Finance Association, vol. 23(5), pages 935-959.
    28. Geweke, John & Amisano, Gianni, 2011. "Optimal prediction pools," Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
    29. Akey, Pat & Heimer, Rawley Z. & Lewellen, Stefan, 2021. "Politicizing consumer credit," Journal of Financial Economics, Elsevier, vol. 139(2), pages 627-655.
    30. Chodorow-Reich, Gabriel & Darmouni, Olivier & Luck, Stephan & Plosser, Matthew, 2022. "Bank liquidity provision across the firm size distribution," Journal of Financial Economics, Elsevier, vol. 144(3), pages 908-932.
    31. Fishback, Price V. & Kantor, Shawn & Wallis, John Joseph, 2003. "Can the New Deal's three Rs be rehabilitated? A program-by-program, county-by-county analysis," Explorations in Economic History, Elsevier, vol. 40(3), pages 278-307, July.
    32. Chernenko, Sergey & Scharfstein, David, 2024. "Racial disparities in the Paycheck Protection Program," Journal of Financial Economics, Elsevier, vol. 160(C).
    33. Granja, João & Makridis, Christos & Yannelis, Constantine & Zwick, Eric, 2022. "Did the paycheck protection program hit the target?," Journal of Financial Economics, Elsevier, vol. 145(3), pages 725-761.
    34. Olivier Coibion & Yuriy Gorodnichenko & Rupal Kamdar, 2018. "The Formation of Expectations, Inflation, and the Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 56(4), pages 1447-1491, December.
    35. Dean Croushore & Tom Stark, 2019. "Fifty Years of the Survey of Professional Forecasters," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 4(4), pages 1-11, October.
    36. Anna Cororaton & Samuel Rosen, 2021. "Public Firm Borrowers of the U.S. Paycheck Protection Program [The risk of being a fallen angel and the corporate dash for cash in the midst of COVID]," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 10(4), pages 641-693.
    37. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2017. "Combining density forecasts using focused scoring rules," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1298-1313, November.
    38. Garratt, Anthony & Henckel, Timo & Vahey, Shaun P., 2023. "Empirically-transformed linear opinion pools," International Journal of Forecasting, Elsevier, vol. 39(2), pages 736-753.
    39. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    40. Carlos Capistrán & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2‐3), pages 365-396, March.
    41. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 269-298.
    42. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
    43. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Density characteristics and density forecast performance: a panel analysis," Empirical Economics, Springer, vol. 48(3), pages 1203-1231, May.
    44. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    45. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, June.
    46. Li, Lei & Strahan, Philip E., 2021. "Who Supplies PPP Loans (and Does It Matter)? Banks, Relationships, and the COVID Crisis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(7), pages 2411-2438, November.
    47. Conflitti, Cristina & De Mol, Christine & Giannone, Domenico, 2015. "Optimal combination of survey forecasts," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1096-1103.
    48. David Autor & David Cho & Leland D. Crane & Mita Goldar & Byron Lutz & Joshua Montes & William B. Peterman & David Ratner & Daniel Villar & Ahu Yildirmaz, 2022. "The $800 Billion Paycheck Protection Program: Where Did the Money Go and Why Did It Go There?," Journal of Economic Perspectives, American Economic Association, vol. 36(2), pages 55-80, Spring.
    49. Elisabeth Kempf & Margarita Tsoutsoura, 2024. "Political Polarization and Finance," NBER Working Papers 32792, National Bureau of Economic Research, Inc.
    50. Kenneth F. Wallis, 2005. "Combining Density and Interval Forecasts: A Modest Proposal," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 983-994, December.
    51. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    52. Samuels, Jon D. & Sekkel, Rodrigo M., 2017. "Model Confidence Sets and forecast combination," International Journal of Forecasting, Elsevier, vol. 33(1), pages 48-60.
    53. Smets, Frank & Warne, Anders & Wouters, Rafael, 2014. "Professional forecasters and real-time forecasting with a DSGE model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 981-995.
    54. McAlinn, Kenichiro & West, Mike, 2019. "Dynamic Bayesian predictive synthesis in time series forecasting," Journal of Econometrics, Elsevier, vol. 210(1), pages 155-169.
    55. Dagostino, Ramona & Gao, Janet & Ma, Pengfei, 2023. "Partisanship in loan pricing," Journal of Financial Economics, Elsevier, vol. 150(3).
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    More about this item

    Keywords

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    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation
    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • H81 - Public Economics - - Miscellaneous Issues - - - Governmental Loans; Loan Guarantees; Credits; Grants; Bailouts

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