IDEAS home Printed from https://ideas.repec.org/a/fip/a00068/99644.html
   My bibliography  Save this article

In Optimism We Trust? Explaining the Disconnect between Post-Election Optimism and Own-Firm Expectations

Author

Listed:
  • Brent Meyer
  • Daniel J. Weitz

Abstract

We randomly split the CFO survey panel into two separate surveys around the 2024 US elections to discern whether the results of the elections had any impact on financial decision makers' expectations. Respondents to the post-election survey reported sharply higher optimism about the US economy and an improved macroeconomic outlook relative to the pre-election responses. In contrast, own-firm optimism and revenue growth expectations were not meaningfully changed between the two surveys. Among many possible reasons for this disconnect, we highlight the expected impact of the new administration's policies and attendant uncertainty related to these policies.

Suggested Citation

  • Brent Meyer & Daniel J. Weitz, 2025. "In Optimism We Trust? Explaining the Disconnect between Post-Election Optimism and Own-Firm Expectations," Policy Hub, Federal Reserve Bank of Atlanta, vol. 2025(2), pages 1-10, March.
    • Handle: RePEc:fip:a00068:99644
    DOI: 10.29338/ph2025-02
    as

    Download full text from publisher

    File URL: https://www.atlantafed.org/-/media/documents/research/publications/policy-hub/2025/03/04/02--post-election-optimism-and-own-firm-expectations.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.29338/ph2025-02?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Susanto Basu & Brent Bundick, 2017. "Uncertainty Shocks in a Model of Effective Demand," Econometrica, Econometric Society, vol. 85, pages 937-958, May.
    2. Bartosz Mackowiak & Mirko Wiederholt, 2009. "Optimal Sticky Prices under Rational Inattention," American Economic Review, American Economic Association, vol. 99(3), pages 769-803, June.
    3. Brent Meyer & Nicholas B. Parker & Xuguang Sheng, 2021. "Unit Cost Expectations and Uncertainty: Firms' Perspectives on Inflation," FRB Atlanta Working Paper 2021-12a, Federal Reserve Bank of Atlanta.
    4. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luca Gambetti & Dimitris Korobilis & John D. Tsoukalas & Francesco Zanetti, 2023. "Agreed and Disagreed Uncertainty," Working Paper series 23-01, Rimini Centre for Economic Analysis.
    2. Bachmann, Rüdiger & Born, Benjamin & Elstner, Steffen & Grimme, Christian, 2019. "Time-varying business volatility and the price setting of firms," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 82-99.
    3. Canales, Mario & Lopez-Martin, Bernabe, 2024. "Exchange rates, uncertainty, and price-setting: Evidence from CPI microdata," Economic Modelling, Elsevier, vol. 139(C).
    4. Laura Veldkamp & Anna Orlik, 2016. "Understanding Uncertainty Shocks and the Role of the Black Swan," Working Papers 16-04, New York University, Leonard N. Stern School of Business, Department of Economics.
    5. Mario Canales & Bernabe Lopez-Martin, 2021. "Uncertainty, Risk, and Price-Setting: Evidence from CPI Microdata," Working Papers Central Bank of Chile 908, Central Bank of Chile.
    6. Bonciani, Dario, 2015. "Estimating the effects of uncertainty over the business cycle," MPRA Paper 65921, University Library of Munich, Germany.
    7. Idriss Fontaine, 2021. "Uncertainty and Labour Force Participation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(2), pages 437-471, April.
    8. Wen Xu, 2016. "Estimation of Dynamic Panel Data Models with Stochastic Volatility Using Particle Filters," Econometrics, MDPI, vol. 4(4), pages 1-13, October.
    9. Yang Liu & Mariano Croce & Ivan Shaliastovich & Ric Colacito, 2016. "Volatility Risk Pass-Through," 2016 Meeting Papers 135, Society for Economic Dynamics.
    10. Yoshito Funashima, 2022. "Economic policy uncertainty and unconventional monetary policy," Manchester School, University of Manchester, vol. 90(3), pages 278-292, June.
    11. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    12. Bonciani, Dario, 2014. "Uncertainty shocks: it's a matter of habit," MPRA Paper 59370, University Library of Munich, Germany.
    13. Miescu, Mirela & Rossi, Raffaele, 2021. "COVID-19-induced shocks and uncertainty," European Economic Review, Elsevier, vol. 139(C).
    14. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    15. Bloom, Nicholas & Bunn, Philip & Chen, Scarlet & Mizen, Paul & Smietanka, Pawel & Thwaites, Gregory, 2019. "The impact of Brexit on UK firms," Bank of England working papers 818, Bank of England.
    16. Alessandro Paolo Rigamonti & Giulio Greco & Mariarita Pierotti & Alessandro Capocchi, 2024. "Macroeconomic uncertainty and earnings management: evidence from commodity firms," Review of Quantitative Finance and Accounting, Springer, vol. 62(4), pages 1615-1649, May.
    17. Chen, Cheng & Senga, Tatsuro & Sun, Chang & Zhang, Hongyong, 2023. "Uncertainty, imperfect information, and expectation formation over the firm’s life cycle," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 60-77.
    18. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    19. Bandi, Federico M. & Bretscher, Lorenzo & Tamoni, Andrea, 2023. "Return predictability with endogenous growth," Journal of Financial Economics, Elsevier, vol. 150(3).
    20. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.

    More about this item

    Keywords

    business survey; economic growth; optimism; policies;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:a00068:99644. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Robert Sarwark (email available below). General contact details of provider: https://edirc.repec.org/data/frbatus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.