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

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  • 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)

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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Bibliographic Info

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. "Consumption inequality and partial insurance," IFS Working Papers W04/28, Institute for Fiscal Studies.
  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.
  3. 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.
  4. Angus Deaton & Christina Paxson, 1993. "Intertemporal Choice and Inequality," NBER Working Papers 4328, National Bureau of Economic Research, Inc.
  5. 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.
  6. 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.
  7. Erich Battistin, 2003. "Errors in survey reports of consumption expenditures," IFS Working Papers W03/07, Institute for Fiscal Studies.
  8. Xavier Gabaix, 1999. "Zipf'S Law For Cities: An Explanation," The Quarterly Journal of Economics, MIT Press, vol. 114(3), pages 739-767, August.
  9. Wooldridge, Jeffrey M. & White, Halbert, 1988. "Some Invariance Principles and Central Limit Theorems for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 4(02), pages 210-230, August.
  10. 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.
  11. Costas Meghir & Luigi Pistaferri, 2001. "Income variance dynamics and heterogenity," IFS Working Papers W01/07, Institute for Fiscal Studies.
  12. 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.
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