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The Predictability Of Aggregate Consumption Growth In Oecd Countries: A Panel Data Analysis

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  • Gerdie Everaert
  • Lorenzo Pozzi

Abstract

SUMMARY We examine aggregate consumption growth predictability. We derive a dynamic consumption equation which encompasses relevant predictability factors: habit formation, intertemporal substitution, current income consumption and non‐separabilities between private consumption and both hours worked and government consumption. We estimate this equation for a panel of 15 OECD countries over the period 1972–2007, taking into account parameter heterogeneity, endogeneity and error cross‐sectional dependence using a GMM version of the common correlated effects mean group estimator. Small‐sample properties are demonstrated using Monte Carlo simulations. The estimation results support income growth as the only variable with significant predictive power for aggregate consumption growth. Copyright © 2013 John Wiley & Sons, Ltd.

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  • Gerdie Everaert & Lorenzo Pozzi, 2014. "The Predictability Of Aggregate Consumption Growth In Oecd Countries: A Panel Data Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 431-453, April.
    • Handle: RePEc:wly:japmet:v:29:y:2014:i:3:p:431-453
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    Cited by:

    1. Havranek, Tomas & Rusnak, Marek & Sokolova, Anna, 2017. "Habit formation in consumption: A meta-analysis," European Economic Review, Elsevier, vol. 95(C), pages 142-167.
    2. Kapetanios, George & Price, Simon & Tasiou, Menelaos & Ventouri, Alexia, 2021. "State-level wage Phillips curves," Econometrics and Statistics, Elsevier, vol. 18(C), pages 1-11.
    3. Tim Buyse & Freddy Heylen & Ruben Schoonackers, 2015. "On The Role Of Public Policies And Wage Formation For Private Investment In R&D: A Long-Run Panel Analysis," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/911, Ghent University, Faculty of Economics and Business Administration.
    4. Vasco J. Gabriel & Ioannis Lazopoulos & Diana Lima, 2023. "Institutional Arrangements and Inflation Bias: A Dynamic Heterogeneous Panel Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(1), pages 43-76, February.
    5. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    6. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    7. Yvonne Adema & Lorenzo Pozzi, 2012. "Business Cycle Fluctuations and Private Savings in OECD Countries: A Panel Data Analysis," Tinbergen Institute Discussion Papers 12-144/VI, Tinbergen Institute.
    8. Lorenzo Pozzi & Barbara Sadaba, 2021. "Macroeconomic disasters and consumption smoothing," Tinbergen Institute Discussion Papers 21-030/VI, Tinbergen Institute.
    9. 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.
    10. Adema, Yvonne & Pozzi, Lorenzo, 2015. "Business cycle fluctuations and household saving in OECD countries: A panel data analysis," European Economic Review, Elsevier, vol. 79(C), pages 214-233.
    11. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    12. Tzu-Ming Liu, 2020. "Habit formation or word of mouth: What does lagged dependent variable in tourism demand models imply?," Tourism Economics, , vol. 26(3), pages 461-474, May.
    13. Muhammad Ibrahim Shah & Shujaat Abbas & Aminat Olayinka Olohunlana & Avik Sinha, 2023. "The impacts of land use change on biodiversity and ecosystem services: An empirical investigation from highly fragile countries," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(3), pages 1384-1400, June.

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