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

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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).

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  • 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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    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

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    6. Hippolyte d’Albis & Ikpidi Badji, 2017. "Intergenerational inequalities in standards of living in France," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 491-492, pages 71-92.
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    8. Frank T Denton & Byron G Spencer & Terry A Yip, 2019. "Age-Income Dynamics Over The Life Course: Cohort Transition Patterns In Relative Income Based On Canadian Tax Returns," Department of Economics Working Papers 2019-02, McMaster University.
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    10. 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.
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    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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