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The age‐time‐cohort problem and the identification of structural parameters in life‐cycle models

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  • Sam Schulhofer‐Wohl

Abstract

A 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 this 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, 2018. "The age‐time‐cohort problem and the identification of structural parameters in life‐cycle models," Quantitative Economics, Econometric Society, vol. 9(2), pages 643-658, July.
    • Handle: RePEc:wly:quante:v:9:y:2018:i:2:p:643-658
    DOI: 10.3982/QE738
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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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    4. 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.
    5. 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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    More about this item

    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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