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Why is consumption more log normal than income? Gibrat's law revisited

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Author Info
Erich Battistin () (Institute for Fiscal Studies)
Richard Blundell () (Institute for Fiscal Studies and University College London)
Arthur Lewbel (Institute for Fiscal Studies and Boston College)

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Abstract

Significant departures from log normality are observed in income data, in violation of Gibrat's law. We identify a new empirical regularity, which is that the distribution of consumption expenditures across households is, within cohorts, closer to log normal than the distribution of income. We explain these empirical results by showing that the logic of Gibrat's law applies not to total income, but to permanent income and to maginal utility. These findings have important implications for welfare and inequality measurement, aggregation, and econometric model analysis.

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Paper provided by Institute for Fiscal Studies in its series IFS Working Papers with number W07/08.

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Date of creation: Jul 2007
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Handle: RePEc:ifs:ifsewp:07/08

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  1. Richard Blundell & Luigi Pistaferri & Ian Preston, 2004. "Imputing consumption in the PSID using food demand estimates from the CEX," IFS Working Papers W04/27, Institute for Fiscal Studies. [Downloadable!]
  2. Richard Blundell & Ian Preston, 1995. "Income, expenditure and the living standards of UK households," Fiscal Studies, Institute for Fiscal Studies, vol. 16(3), pages 40-54, August. [Downloadable!]
  3. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 971-87, December. [Downloadable!] (restricted)
  4. 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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  5. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January. [Downloadable!] (restricted)
  6. Costas Meghir & Luigi Pistaferri, 2004. "Income Variance Dynamics and Heterogeneity," Econometrica, Econometric Society, vol. 72(1), pages 1-32, 01. [Downloadable!] (restricted)
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  7. Deaton, Angus & Paxson, Christina, 1994. "Intertemporal Choice and Inequality," Journal of Political Economy, University of Chicago Press, vol. 102(3), pages 437-67, June. [Downloadable!] (restricted)
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  8. Bruce D. Meyer & James X. Sullivan, 2003. "Measuring the Well-Being of the Poor Using Income and Consumption," NBER Working Papers 9760, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  9. Erich Battistin, 2002. "Errors in Survey Reports of Consumption Expenditures," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C4-2, International Conferences on Panel Data. [Downloadable!]
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  10. Xavier Gabaix, 1999. "Zipf'S Law For Cities: An Explanation," The Quarterly Journal of Economics, MIT Press, vol. 114(3), pages 739-767, August. [Downloadable!] (restricted)
  11. Richard Blundell & Luigi Pistaferri & Ian Preston, 2004. "Consumption inequality and partial insurance," IFS Working Papers W04/28, Institute for Fiscal Studies. [Downloadable!]
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  1. Matteo Barigozzi & Lucia Alessi & Marco Capasso & Giorgio Fagiolo, 2008. "The Distribution of Consumption-Expenditure Budget Shares. Evidence from Italian Households," Papers on Economics and Evolution 2008-09, Max Planck Institute of Economics, Evolutionary Economics Group. [Downloadable!]
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