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Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers

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  • Kajal Lahiri

    () (University at Albany, SUNY)

  • Yongchen Zhao

    () (Towson University)

Abstract

We study the information content of the University of Michigan’s Index of Consumer Sentiment as well as its five components. Using household data from the Surveys of Consumers over 1979-2013, we identify the main determinants of these indicators and document their varying role over the business cycle. Our results suggest that while at the aggregate level, macroeconomic conditions explain sentiment well, important and additional information is contained at the level of households. We compare the role of objective and subjective information in determining household level sentiment, and show that significant heterogeneity in the absorption of news from local network sources is a major feature of consumer sentiment. The differential interpretation of current macroeconomic conditions is found to be more pervasive in periods of falling sentiment that typically predates business cycle peaks, and thus helps sentiment to foreshadow recessions.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:jbuscr:v:12:y:2016:i:2:d:10.1007_s41549-016-0010-5
    DOI: 10.1007/s41549-016-0010-5
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    Cited by:

    1. Zhao, Yongchen, 2019. "Updates to household inflation expectations: Signal or noise?," Economics Letters, Elsevier, vol. 181(C), pages 95-98.
    2. An, Zidong & Liu, Dingqian & Wu, Yuzheng, 2021. "Expectation formation following pandemic events," Economics Letters, Elsevier, vol. 200(C).
    3. Camilo Alberto Cárdenas-Hurtado & María Alejandra Hernández-Montes, 2019. "Understanding the Consumer Confidence Index in Colombia: A structural FAVAR analysis," Borradores de Economia 1063, Banco de la Republica de Colombia.
    4. Petar Soric & Mateo Zokalj & Marija Logarusic, 2020. "Economic determinants of Croatian consumer confidence: real estate prices vs. macroeconomy," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 18(2B), pages 240-257.
    5. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    6. E. Balatskiy V. & M. Yurevich A. & Е. Балацкий В. & М. Юревич А., 2018. "Прогнозирование инфляции: практика использования синтетических процедур // Inflation Forecasting: The Practice of Using Synthetic Procedures," Мир новой экономики // The world of new economy, Финансовый университет при Правительстве Российской Федерации // Financial University under The Governtment оf The Russian Federation, vol. 12(4), pages 20-31.
    7. Ben Zhe Wang & Jeffrey Sheen & Stefan Truck & Shih-Kang Chao & Wolfgang Karl Hardle, 2020. "A note on the impact of news on US household inflation expectations," Papers 2009.11557, arXiv.org.
    8. Allen N. Berger & Felix Irresberger & Raluca A. Roman, 2020. "Bank Size and Household Financial Sentiment: Surprising Evidence from University of Michigan Surveys of Consumers," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(S1), pages 149-191, October.
    9. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
    10. Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2015. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 5468, CESifo.
    11. Marwane El Alaoui & Elie Bouri & Nehme Azoury, 2020. "The Determinants of the U.S. Consumer Sentiment: Linear and Nonlinear Models," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 8(3), pages 1-13, July.
    12. Hardik A. Marfatia & Christophe Andre & Rangan Gupta, 2020. "Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties," Working Papers 202061, University of Pretoria, Department of Economics.
    13. Petar Sorić & Mirjana Čižmešija & Marina Matošec, 2020. "EU Consumer Confidence and the New Modesty Hypothesis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(3), pages 899-921, December.
    14. Liudmila Kitrar & Tamara Lipkind & Georgy Ostapkovich, 2020. "Information Content of Russian Services Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(1), pages 59-74, April.

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    More about this item

    Keywords

    Consumer confidence; Cross-sectional heterogeneity; Asymmetry; News; Recessions;
    All these keywords.

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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