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A Reexamination of the Consumption Function Using Frequency Domain Regressors

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Abstract

This paper reexamines the permanent income hypothesis (PIH) in the frequency domain. Using a simple model, we demonstrate that the PIH implies the marginal propensity to consume (MPC) out of zero frequency income is unity. The PIH also implies that the MPC out of transitory (or high frequency) income is smaller than the long-run MPC. The paper employs a systems spectral regression procedure to test the PIH that accommodates stochastic trends in the consumption and income series as well as the joint dependence in these series. Monte Carlo simulations suggest that single equation techniques can produce inefficient tests of the PIH and that systems spectral regression methods provide substantially better tests. New empirical estimates of the consumption function and tests of the PIH based on systems spectral regression methods are reported for U.S. aggregate consumption and income data over the period 1948-1990. The empirical results provide partial support for the theoretical implications of the PIH in the frequency domain.

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  • Dean Corbea & Sam Ouliaris & Peter C.B. Phillips, 1991. "A Reexamination of the Consumption Function Using Frequency Domain Regressors," Cowles Foundation Discussion Papers 997, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:997
    Note: CFP 894.
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    2. Campbell, John Y, 1987. "Does Saving Anticipate Declining Labor Income? An Alternative Test of the Permanent Income Hypothesis," Econometrica, Econometric Society, vol. 55(6), pages 1249-1273, November.
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    4. Peter C. B. Phillips & Mico Loretan, 1991. "Estimating Long-run Economic Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 407-436.
    5. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    6. Peter C.B. Phillips, 1988. "Spectral Regression for Cointegrated Time Series," Cowles Foundation Discussion Papers 872, Cowles Foundation for Research in Economics, Yale University.
    7. Geweke, John F. & Singleton, Kenneth J., 1981. "Latent variable models for time series : A frequency domain approach with an application to the permanent income hypothesis," Journal of Econometrics, Elsevier, vol. 17(3), pages 287-304, December.
    8. Stock, James H, 1988. "A Reexamination of Friedman's Consumption Puzzle," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(4), pages 401-407, October.
    9. Cochrane, John H. & Sbordone, Argia M., 1988. "Multivariate estimates of the permanent components of GNP and stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 255-296.
    10. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    11. Engle, Robert F, 1974. "Band Spectrum Regression," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 1-11, February.
    12. John H. Cochrane, 1990. "Univariate vs. Multivariate Forecasts of GNP Growth and Stock Returns: Evidence and Implications for the Persistence of Shocks, Detrending Methods," NBER Working Papers 3427, National Bureau of Economic Research, Inc.
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    Cited by:

    1. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    2. Woodford, Michael, 2007. "Does a 'Two-Pillar Phillips Curve' Justify a Two-Pillar Monetary Policy Strategy?," CEPR Discussion Papers 6447, C.E.P.R. Discussion Papers.
    3. Feng Zhu, 2005. "The fragility of the Phillips curve: A bumpy ride in the frequency domain," BIS Working Papers 183, Bank for International Settlements.
    4. Peter C.B. Phillips & Binbin Guo & Zhijie Xiao, 2002. "Efficient Regression in Time Series Partial Linear Models," Cowles Foundation Discussion Papers 1363, Cowles Foundation for Research in Economics, Yale University.
    5. Fabio Busetti & Michele Caivano, 2017. "Low frequency drivers of the real interest rate: a band spectrum regression approach," Temi di discussione (Economic working papers) 1132, Bank of Italy, Economic Research and International Relations Area.
    6. repec:zbw:bofrdp:1995_034 is not listed on IDEAS
    7. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    8. Kitamura, Yuichi & Phillips, Peter C. B., 1997. "Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments," Journal of Econometrics, Elsevier, vol. 80(1), pages 85-123, September.
    9. Richard K. Crump & Nikolay Gospodinov & Ignacio Lopez Gaffney, 2024. "A Simple Diagnostic for Time-Series and Panel-Data Regressions," Staff Reports 1132, Federal Reserve Bank of New York.
    10. Zhijie Xiao & Peter C.B. Phillips, 1998. "Higher Order Approximations for Wald Statistics in Cointegrating Regressions," Cowles Foundation Discussion Papers 1192, Cowles Foundation for Research in Economics, Yale University.
    11. Assenmacher-Wesche, Katrin & Gerlach, Stefan, 2008. "Interpreting euro area inflation at high and low frequencies," European Economic Review, Elsevier, vol. 52(6), pages 964-986, August.
    12. Monteiro, Paulo Santos, 2008. "Testing Full Consumption Insurance in the Frequency Domain," Economic Research Papers 269910, University of Warwick - Department of Economics.
    13. Assenmacher-Wesche, Katrin & Gerlach, Stefan, 2008. "Money growth, output gaps and inflation at low and high frequency: Spectral estimates for Switzerland," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 411-435, February.
    14. Sierimo, Carolina & Virén, Matti, 1995. "Financial factors and the macroeconomy," Research Discussion Papers 34/1995, Bank of Finland.
    15. Xiao, Zhijie & Phillips, Peter C. B., 2002. "Higher order approximations for Wald statistics in time series regressions with integrated processes," Journal of Econometrics, Elsevier, vol. 108(1), pages 157-198, May.
    16. Maslova, Inga & Onder, Harun & Sanghi, Apurva, 2013. "Growth and volatility analysis using wavelets," Policy Research Working Paper Series 6578, The World Bank.
    17. Sierimo, Carolina & Virén, Matti, 1995. "Financial factors and the macroeconomy," Bank of Finland Research Discussion Papers 34/1995, Bank of Finland.
    18. Xiao, Zhijie & Phillips, Peter C. B., 1998. "Higher-order approximations for frequency domain time series regression," Journal of Econometrics, Elsevier, vol. 86(2), pages 297-336, June.

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    More about this item

    Keywords

    Permanent income; hypothesis; consumption; consumer economics;
    All these keywords.

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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