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Is Consumption Too Smooth? Long Memory and the Deaton Paradox

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Author Info
Diebold, Francis X
Rudebusch, Glenn D

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Abstract

Under common ARIMA representations of income, the permanent-income hypothesis predicts that the volatility of consumption should be larger than the volatility of unanticipated shocks to income; this prediction is not supported by the data. The authors examine whether this apparent excess smoothness of consumption is the result of the ARIMA representation's implicit restrictions on low-frequency dynamics. By using a generalized long-memory stochastic representation, the authors construct confidence intervals for the long-run impulse response of income in the absence of such low-frequency restrictions. These intervals are quite wide and include regions in which excess smoothness vanishes. Copyright 1991 by MIT Press.

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Publisher Info
Article provided by MIT Press in its journal Review of Economics & Statistics.

Volume (Year): 73 (1991)
Issue (Month): 1 (February)
Pages: 1-9
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Handle: RePEc:tpr:restat:v:73:y:1991:i:1:p:1-9

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  1. Morten Ørregaard Nielsen & Per Frederiksen, 2005. "Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration," Working Papers 1189, Queen's University, Department of Economics. [Downloadable!]
  2. John Barkoulas & Christopher F. Baum & Mustafa Caglayan, 1998. "Fractional Monetary Dynamics," Boston College Working Papers in Economics 321., Boston College Department of Economics. [Downloadable!]
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  3. Katsumi Shimotsu, 2002. "Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend," Economics Discussion Papers 543, University of Essex, Department of Economics. [Downloadable!]
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  4. Francis X. Diebold & Glenn D. Rudebusch, 2001. "Five questions about business cycles," Economic Review, Federal Reserve Bank of San Francisco, pages 1-15. [Downloadable!]
  5. Stephen R. Blough, 1994. "Near common factors and confidence regions for present value models," Working Papers 94-3, Federal Reserve Bank of Boston. [Downloadable!]
  6. Mark J. Jensen, 1998. "An Approximate Wavelet MLE of Short and Long Memory Parameters," Econometrics 9802003, EconWPA, revised 21 Jun 1999. [Downloadable!]
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  7. L. Gil-Alana, . "A Generalized Fractional Time Series Model," Sonderforschungsbereich 373 2000-107, Humboldt Universitaet Berlin.
  8. Gary Koop, 1995. "Bayesian Analysis of Long Memory and Persistence using ARFIMA Models," Working Papers gkoop-95-01, University of Toronto, Department of Economics. [Downloadable!]
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  9. Jesús Gonzalo, Tae-Hwy Lee, 2000. "On the robustness of cointegration tests when series are fractionally intergrated," Journal of Applied Statistics, Taylor and Francis Journals, vol. 27(7), pages 821-827, September. [Downloadable!] (restricted)
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  10. Marc Henry & Paolo Zaffaroni, 2002. "The long range dependence paradigm for macroeconomics and finance," Discussion Papers 0102-19, Columbia University, Department of Economics. [Downloadable!]
  11. John Barkoulas & Christopher F. Baum, 2003. "Long-Memory Forecasting of U.S. Monetary Indices," Boston College Working Papers in Economics 558, Boston College Department of Economics. [Downloadable!]
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  12. Mark J. Jensen, 1997. "Using Wavelets to Obtain a Consistent Ordinary Least Squares Estimator of the Long Memory Parameter," Econometrics 9710002, EconWPA. [Downloadable!]
  13. Gil-Alana, L. A., 2003. "A Generalized Fractional Time Series Model: Testing the Order of Integration of Trend Seasonal and Cyclical components," Review on Economic Cycles, International Association of Economic Cycles, vol. 7(1), December. [Downloadable!]
  14. Joseph G. Haubrich, 1990. "Consumption and fractional differencing: old and new anomalies," Working Paper 9010, Federal Reserve Bank of Cleveland. [Downloadable!]
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  15. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics. [Downloadable!]
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