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The age-time-cohort problem and the identification of structural parameters in life-cylce models

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  • Sam Schulhofer-Wohl

Abstract

The standard approach to estimating structural parameters in life-cycle models imposes sufficient assumptions on the data to identify the “age profile” of outcomes, then chooses model parameters so that the model’s age profile matches this empirical age profile. I show that the standard approach is both incorrect and unnecessary: incorrect, because it generally produces inconsistent estimators of the structural parameters, and unnecessary, because consistent estimators can be obtained under weaker assumptions. I derive an estimation method that avoids the problems of the standard approach. I illustrate the method’s benefits analytically in a simple model of consumption inequality and numerically by reestimating the classic life-cycle consumption model of Gourinchas and Parker (2002).

Suggested Citation

  • Sam Schulhofer-Wohl, 2013. "The age-time-cohort problem and the identification of structural parameters in life-cylce models," Working Papers 707, Federal Reserve Bank of Minneapolis.
  • Handle: RePEc:fip:fedmwp:707
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    References listed on IDEAS

    as
    1. Mariacristina De Nardi & Eric French & John B. Jones, 2010. "Why Do the Elderly Save? The Role of Medical Expenses," Journal of Political Economy, University of Chicago Press, vol. 118(1), pages 39-75, February.
    2. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    3. Sam Schulhofer-Wohl & Yang Yang, 2011. "Modeling the evolution of age and cohort effects in social research," Staff Report 461, Federal Reserve Bank of Minneapolis.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. The age-time-cohort problem and the identification of structural parameters in life-cylce models
      by Christian Zimmermann in NEP-DGE blog on 2013-07-22 08:53:16

    Citations

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    Cited by:

    1. Luiz Mello & Simone Schotte & Erwin R. Tiongson & Hernan Winkler, 2017. "Greying the Budget: Ageing and Preferences over Public Policies," Kyklos, Wiley Blackwell, vol. 70(1), pages 70-96, February.
    2. Enrico Moretti & Daniel J. Wilson, 2017. "The Effect of State Taxes on the Geographical Location of Top Earners: Evidence from Star Scientists," American Economic Review, American Economic Association, vol. 107(7), pages 1858-1903, July.
    3. G. C. Lim & Q. Zeng, 2016. "Consumption, Income, and Wealth: Evidence from Age, Cohort, and Period Elasticities," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(3), pages 489-508, September.
    4. Lorenz Kueng & Mu-Jeung Yang & Bryan Hong, 2014. "Sources of Firm Life-Cycle Dynamics: Differentiating Size vs. Age Effects," NBER Working Papers 20621, National Bureau of Economic Research, Inc.
    5. repec:eee:eneeco:v:65:y:2017:i:c:p:161-171 is not listed on IDEAS

    More about this item

    Keywords

    Demography;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • J1 - Labor and Demographic Economics - - Demographic Economics

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