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Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 130 Studies Say "Probably Not"

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  • Tomas Havranek
  • Anna Sokolova
Abstract
We show that three factors combine to explain the mean excess sensitivity reported in studies estimating consumption Euler equations: the use of macro data, publication bias, and liquidity constraints. When micro data are used, publication bias is corrected for, and the households under examination do not face liquidity constraints, the literature implies no evidence for the excess sensitivity of consumption to income. Hence little remains for pure rule-of-thumb behavior. The results hold when we control for 45 additional variables reflecting the methods employed by researchers and use Bayesian model averaging to account for model uncertainty. The estimates of excess sensitivity are also systematically affected by the order of approximation of the Euler equation, the treatment of non-separability between consumption and leisure, and the choice of proxy for consumption.

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  • Tomas Havranek & Anna Sokolova, 2016. "Do Consumers Really Follow a Rule of Thumb? Three Thousand Estimates from 130 Studies Say "Probably Not"," Working Papers 2016/08, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2016/08
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    4. Balima, Hippolyte W. & Sokolova, Anna, 2021. "IMF programs and economic growth: A meta-analysis," Journal of Development Economics, Elsevier, vol. 153(C).
    5. 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.
    6. Ichiro Iwasaki & Akira Uegaki, 2017. "Central Bank Independence and Inflation in Transition Economies: A Comparative Meta-Analysis with Developed and Developing Economies," Eastern European Economics, Taylor & Francis Journals, vol. 55(3), pages 197-235, May.
    7. Tomas Havranek & Zuzana Irsova, 2017. "Do Borders Really Slash Trade? A Meta-Analysis," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 65(2), pages 365-396, June.
    8. Mark Aguiar & Corina Boar & Mark Bils, 2019. "Who Are the Hand-to-Mouth?," 2019 Meeting Papers 525, Society for Economic Dynamics.
    9. Cristina Blanco-Perez & Abel Brodeur, 2020. "Publication Bias and Editorial Statement on Negative Findings," The Economic Journal, Royal Economic Society, vol. 130(629), pages 1226-1247.
    10. Anna Sokolova & Todd Sorensen, 2021. "Monopsony in Labor Markets: A Meta-Analysis," ILR Review, Cornell University, ILR School, vol. 74(1), pages 27-55, January.
    11. Anton Astakhov & Tomas Havranek & Jiri Novak, 2019. "Firm Size And Stock Returns: A Quantitative Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 33(5), pages 1463-1492, December.
    12. Brodeur, Abel & Cook, Nikolai & Heyes, Anthony, 2018. "Methods Matter: P-Hacking and Causal Inference in Economics," IZA Discussion Papers 11796, Institute of Labor Economics (IZA).
    13. Ichiro Iwasaki & Kazuhiro Kumo, 2019. "J-Curve in Transition Economies: A Large Meta-analysis of the Determinants of Output Changes," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 61(1), pages 149-191, March.
    14. Patrizio Tirelli & Maria Ferrara, 2020. "Disinflation, Inequality, And Welfare In A Tank Model," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1297-1313, July.
    15. Ni, Niannian & Liu, Yulin, 2019. "Financial liberalization and income inequality: A meta-analysis based on cross-country studies," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    16. Peter Ganong & Damon Jones & Pascal J. Noel & Fiona E. Greig & Diana Farrell & Chris Wheat, 2020. "Wealth, Race, and Consumption Smoothing of Typical Income Shocks," NBER Working Papers 27552, National Bureau of Economic Research, Inc.
    17. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    18. Tomáš Lichard & Jan Hanousek & Randall K. Filer, 2021. "Hidden in plain sight: using household data to measure the shadow economy," Empirical Economics, Springer, vol. 60(3), pages 1449-1476, March.

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    More about this item

    Keywords

    Bayesian model averaging; excess sensitivity; liquidity constraints; publication bias; rule-of-thumb consumers;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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