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A Reexamination of the Consumption Function Using Frequency Domain Regressions

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  • Corbae, Dean
  • Ouliaris, Sam
  • Phillips, Peter C B

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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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 19 (1994)
Issue (Month): 4 ()
Pages: 595-609

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Handle: RePEc:spr:empeco:v:19:y:1994:i:4:p:595-609

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References

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  1. 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.
  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 1249-73, November.
  3. 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.
  4. 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.
  5. Park, Joon Y, 1992. "Canonical Cointegrating Regressions," Econometrica, Econometric Society, vol. 60(1), pages 119-43, January.
  6. Peter C.B. Phillips & Mico Loretan, 1989. "Estimating Long Run Economic Equilibria," Cowles Foundation Discussion Papers 928, Cowles Foundation for Research in Economics, Yale University.
  7. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
  8. Stock, James H, 1988. "A Reexamination of Friedman's Consumption Puzzle," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(4), pages 401-07, October.
  9. John H. Cochrane, 1994. "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.
  10. Peter C.B. Phillips & Sam Ouliaris & Joon Y. Park, 1988. "Testing for a Unit Root in the Presence of a Maintained Trend," Cowles Foundation Discussion Papers 880, Cowles Foundation for Research in Economics, Yale University.
  11. Peter C.B. Phillips, 1988. "Spectral Regression for Cointegrated Time Series," Cowles Foundation Discussion Papers 872, Cowles Foundation for Research in Economics, Yale University.
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Citations

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Cited by:
  1. 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.
  2. 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.
  3. 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.
  4. Michael Woodford, 2007. "Does a "two-pillar Phillips curve" justify a two-pillar monetary policy strategy?," Discussion Papers 0607-06, Columbia University, Department of Economics.
  5. Campbell, J.Y. & Perron, P., 1991. "Pitfalls and Opportunities: What Macroeconomics should know about unit roots," Papers 360, Princeton, Department of Economics - Econometric Research Program.
  6. Maslova, Inga & Onder, Harun & Sanghi, Apurva, 2013. "Growth and volatility analysis using wavelets," Policy Research Working Paper Series 6578, The World Bank.
  7. 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.
  8. 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.
  9. 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.
  10. 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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