IDEAS home Printed from https://ideas.repec.org/p/yon/wpaper/2023rwp-216.html
   My bibliography  Save this paper

News or Animal Spirits? Consumer Confidence and Economic Activity: Redux

Author

Listed:
  • Sangyyup Choi

    (Yonsei University)

  • Jaehun Jeong

    (Duke University)

  • Dohyeon Park

    (Sogang University)

  • Donghoon Yoo

    (Academia Sinica)

Abstract

Barsky and Sims (2012, AER) demonstrated, via indirect inference, that confidence innovations can be viewed as noisy signals about medium-term economic growth. They highlighted that the connection between confidence and subsequent activity, such as consumption and output, is primarily driven by news shocks about the future. We expand upon their research in two significant ways. First, we incorporate the Great Recession and ZLB episodes, and second, we employ unique state-level data to offer insights into how to interpret the relationship between consumer confidence and economic activity. Our results confirm the main finding of Barsky and Sims (2012) that this relationship is predominantly driven by news about the future.

Suggested Citation

  • Sangyyup Choi & Jaehun Jeong & Dohyeon Park & Donghoon Yoo, 2023. "News or Animal Spirits? Consumer Confidence and Economic Activity: Redux," Working papers 2023rwp-216, Yonsei University, Yonsei Economics Research Institute.
    • Handle: RePEc:yon:wpaper:2023rwp-216
    as

    Download full text from publisher

    File URL: http://121.254.254.220/repec/yon/wpaper/2023rwp-216.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Case Karl E. & Quigley John M. & Shiller Robert J., 2005. "Comparing Wealth Effects: The Stock Market versus the Housing Market," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-34, May.
    2. Carroll, Christopher D & Fuhrer, Jeffrey C & Wilcox, David W, 1994. "Does Consumer Sentiment Forecast Household Spending? If So, Why?," American Economic Review, American Economic Association, vol. 84(5), pages 1397-1408, December.
    3. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, July.
    4. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    5. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
    6. Roger E. A. Farmer, 2012. "Confidence, Crashes and Animal Spirits," Economic Journal, Royal Economic Society, vol. 122(559), pages 155-172, March.
    7. Robert B. Barsky & Susanto Basu & Keyoung Lee, 2015. "Whither News Shocks?," NBER Macroeconomics Annual, University of Chicago Press, vol. 29(1), pages 225-264.
    8. repec:mcb:jmoncb:v:45:y:2013:i::p:559-590 is not listed on IDEAS
    9. Wei Dai & Mark Weder & Bo Zhang, 2020. "Animal Spirits, Financial Markets, and Aggregate Instability," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(8), pages 2053-2083, December.
    10. Stephanie Schmitt-Grohé & Martín Uribe, 2017. "Liquidity Traps and Jobless Recoveries," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(1), pages 165-204, January.
    11. Lucia F. Dunn & Ida A. Mirzaie, 2006. "Turns in Consumer Confidence: An Information Advantage Linked to Manufacturing," Economic Inquiry, Western Economic Association International, vol. 44(2), pages 343-351, April.
    12. Sydney C. Ludvigson, 2004. "Consumer Confidence and Consumer Spending," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 29-50, Spring.
    13. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
    14. Jonathan Heathcote & Fabrizio Perri, 2018. "Wealth and Volatility," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(4), pages 2173-2213.
    15. Jess Benhabib & Mark M Spiegel, 2019. "Sentiments and Economic Activity: Evidence from US States," The Economic Journal, Royal Economic Society, vol. 129(618), pages 715-733.
    16. Thomas A. Garrett & Ruben Hernandez-Murillo & Michael T. Owyang, 2005. "Does consumer sentiment predict regional consumption?," Review, Federal Reserve Bank of St. Louis, vol. 87(Mar), pages 123-135.
    17. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    18. Jonathon Hazell & Juan Herreño & Emi Nakamura & Jón Steinsson, 2022. "The Slope of the Phillips Curve: Evidence from U.S. States," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(3), pages 1299-1344.
    19. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    20. Matsusaka, John G & Sbordone, Argia M, 1995. "Consumer Confidence and Economic Fluctuations," Economic Inquiry, Western Economic Association International, vol. 33(2), pages 296-318, April.
    21. Lance A. Fisher & Hyeon-seung Huh, 2016. "On the econometric modelling of consumer sentiment shocks in SVARs," Empirical Economics, Springer, vol. 51(3), pages 1033-1051, November.
    22. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    23. Kajal Lahiri & George Monokroussos & Yongchen Zhao, 2016. "Forecasting Consumption: the Role of Consumer Confidence in Real Time with many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1254-1275, November.
    24. Klein, Mathias & Linnemann, Ludger, 2021. "Real exchange rate and international spillover effects of US technology shocks," Journal of International Economics, Elsevier, vol. 129(C).
    25. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
    26. Chadi S. Abdallah & William D. Lastrapes, 2013. "Evidence on the Relationship between Housing and Consumption in the United States: A State-Level Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 559-590, June.
    27. Christopher Biolsi & Bocong Du, 2020. "Do shocks to animal spirits cause output fluctuations?," Southern Economic Journal, John Wiley & Sons, vol. 87(1), pages 331-368, July.
    28. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    29. Andy C.C. Kwan & John A. Cotsomitis, 2006. "The Usefulness of Consumer Confidence in Forecasting Household Spending in Canada: A National and Regional Analysis," Economic Inquiry, Western Economic Association International, vol. 44(1), pages 185-197, January.
    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. Hashmat Khan & Jean-François Rouillard & Santosh Upadhayaya, 2019. "Consumer Confidence and Household Investment," Carleton Economic Papers 19-06, Carleton University, Department of Economics, revised 04 Jan 2024.
    2. Hashmat Khan & Santosh Upadhayaya, 2020. "Does business confidence matter for investment?," Empirical Economics, Springer, vol. 59(4), pages 1633-1665, October.
    3. Hector H. Sandoval & Anita N. Walsh, 2021. "The role of consumer confidence in forecasting consumption, evidence from Florida," Southern Economic Journal, John Wiley & Sons, vol. 88(2), pages 757-788, October.
    4. Gric, Zuzana & Ehrenbergerova, Dominika & Hodula, Martin, 2022. "The power of sentiment: Irrational beliefs of households and consumer loan dynamics," Journal of Financial Stability, Elsevier, vol. 59(C).
    5. Andresa Lagerborg & Evi Pappa & Morten O Ravn, 2023. "Sentimental Business Cycles," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(3), pages 1358-1393.
    6. Badi H. Baltagi, 2021. "Dynamic Panel Data Models," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 187-228, Springer.
    7. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.
    8. Vasilev, Aleksandar, 2022. "How Important Are Consumer Confidence Shocks for the Propagation of Business Cycles in Bulgaria?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 63(10-12), pages 589-603.
    9. Patrick Fève & Alain Guay, 2019. "Sentiments in SVARs," The Economic Journal, Royal Economic Society, vol. 129(618), pages 877-896.
    10. Sangyup Choi & Kimoon Jeong & Jiseob Kim, 2023. "One Monetary Policy and Two Bank Lending Standards: A Tale of Two Europes," Working papers 2023rwp-209, Yonsei University, Yonsei Economics Research Institute.
    11. Ahmed, M. Iqbal & Cassou, Steven P., 2016. "Does consumer confidence affect durable goods spending during bad and good economic times equally?," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 86-97.
    12. Thales A. J. T. T. Maion & Marcio Issao Nakane, 2019. "News shocks and consumer expectations: evidence for Brazil," Working Papers, Department of Economics 2019_11, University of São Paulo (FEA-USP).
    13. Simona Malovaná & Martin Hodula & Jan Frait, 2021. "What Does Really Drive Consumer Confidence?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(3), pages 885-913, June.
    14. Tufan Ekici, 2016. "Subjective Financial Distress in the Formation of Consumer Confidence: Evidence from Novel Household Data," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 30(2), pages 11-36.
    15. Lenka Mynaříková & Vít Pošta, 2023. "The Effect of Consumer Confidence and Subjective Well-being on Consumers’ Spending Behavior," Journal of Happiness Studies, Springer, vol. 24(2), pages 429-453, February.
    16. MAÏ ASSAN CHEDI, Maman, 2022. "Does Defence Expenditure Affect Education and Health expenditures in Saharan Africa?," African Journal of Economic Review, African Journal of Economic Review, vol. 10(4), September.
    17. Aneta Maria Kłopocka, 2017. "Does Consumer Confidence Forecast Household Saving and Borrowing Behavior? Evidence for Poland," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(2), pages 693-717, September.
    18. Herzer, Dierk & Nunnenkamp, Peter, 2015. "Income inequality and health: Evidence from developed and developing countries," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-56.
    19. Debes, Sebastian & Gareis, Johannes & Mayer, Eric & Rüth, Sebastian, 2014. "Towards a consumer sentiment channel of monetary policy," W.E.P. - Würzburg Economic Papers 91, University of Würzburg, Department of Economics.
    20. Delis, Manthos D. & Kouretas, Georgios P. & Tsoumas, Chris, 2014. "Anxious periods and bank lending," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 1-13.

    More about this item

    Keywords

    Consumer confidence; news; animal spirits; Great Recession; state-level analysis.;
    All these keywords.

    JEL classification:

    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E71 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on the Macro Economy

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:yon:wpaper:2023rwp-216. 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: YERI (email available below). General contact details of provider: https://edirc.repec.org/data/eryonkr.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.