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Volatility in Panel Data of Household Expenditure

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Author Info
Naohito Abe
Abstract

The variance of growth rates of recall food expenditure is usually greater than the variance of the income growth rate. Many researchers regard the strong volatility as a symptom of measurement error. Comparing two data sets, diary data and recall data, I find that the measurement error cannot account for the observed large variance in the consumption data. Variance decomposition of the consumption and income growth rates reveals that the permanent component of the consumption variance is smaller than that of the income variance, suggesting that the consumption smoothing holds in the long run. Short run fluctuation in consumption, however, is not caused by measurement error. The implication of this finding for the modeling of household behavior is also discussed.

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Paper provided by Institute of Economic Research, Hitotsubashi University in its series Hi-Stat Discussion Paper Series with number d07-237.

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Date of creation: Feb 2008
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Handle: RePEc:hst:hstdps:d07-237

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  2. Richard Blundell & Ian Preston, 1998. "Consumption Inequality And Income Uncertainty," The Quarterly Journal of Economics, MIT Press, vol. 113(2), pages 603-640, May. [Downloadable!] (restricted)
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  3. Naohito Abe, 2004. "The Multi-Sector Business Cycle Model and Aggregate Shocks: An Empirical Analysis," The Japanese Economic Review, Japanese Economic Association, vol. 55(1), pages 101-118. [Downloadable!] (restricted)
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  5. Mork, Knut Anton & Smith, V Kerry, 1989. "Testing the Life-Cycle Hypothesis with a Norwegian Household Panel," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(3), pages 287-96, July.
  6. Pierre-Olivier Gourinchas & Jonathan A. Parker, 1999. "Consumption Over the Life Cycle," NBER Working Papers 7271, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  7. Gibson, John, 2002. " Why Does the Engel Method Work? Food Demand, Economies of Size and Household Survey Methods," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 341-59, September. [Downloadable!] (restricted)
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  8. Finn E. Kydland & Edward C. Prescott, 1990. "Business cycles: real facts and a monetary myth," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Spr, pages 3-18. [Downloadable!]
  9. Hall, Robert E & Mishkin, Frederic S, 1982. "The Sensitivity of Consumption to Transitory Income: Estimates from Panel Data on Households," Econometrica, Econometric Society, vol. 50(2), pages 461-81, March. [Downloadable!] (restricted)
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  10. Ohtake, Fumio & Saito, Makoto, 1998. "Population Aging and Consumption Inequality in Japan," Review of Income and Wealth, Blackwell Publishing, vol. 44(3), pages 361-81, September.
  11. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-45, March. [Downloadable!] (restricted)
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  12. Sydney Ludvigson & Christina H. Paxson, 2001. "Approximation Bias In Linearized Euler Equations," The Review of Economics and Statistics, MIT Press, vol. 83(2), pages 242-256, May. [Downloadable!] (restricted)
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  13. Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers W06/21, Institute for Fiscal Studies. [Downloadable!]
  14. Cagetti, Marco, 2003. "Wealth Accumulation over the Life Cycle and Precautionary Savings," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 339-53, July.
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