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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

    (Federal Reserve Bank of Minneapolis)

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 generically produces inconsistent estimators of the structural parameters, and unnecessary, because consistent estimators can be obtained under weaker fewer assumptions. I derive an identification method that avoids the problems of the standard approach and illustrate its benefits in a simple model of consumption inequality.

Suggested Citation

  • Sam Schulhofer-Wohl, 2012. "The Age-Time-Cohort Problem and the Identification of Structural Parameters in Life-Cycle Models," 2012 Meeting Papers 575, Society for Economic Dynamics.
    • Handle: RePEc:red:sed012:575
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    References listed on IDEAS

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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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    Cited by:

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    2. Hippolyte d'Albis & Ikpidi Badji, 2017. "Les inégalités de niveaux de vie entre les générations en France," PSE-Ecole d'économie de Paris (Postprint) halshs-01524882, HAL.
    3. 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.
    4. Bardazzi, Rossella & Pazienza, Maria Grazia, 2017. "Switch off the light, please! Energy use, aging population and consumption habits," Energy Economics, Elsevier, vol. 65(C), pages 161-171.
    5. Jesse Rothstein, 2023. "The Lost Generation? Labor Market Outcomes for Post-Great Recession Entrants," Journal of Human Resources, University of Wisconsin Press, vol. 58(5), pages 1452-1479.
    6. Cao, Shutao & Meh, Césaire A. & Ríos-Rull, José-Víctor & Terajima, Yaz, 2021. "The welfare cost of inflation revisited: The role of financial innovation and household heterogeneity," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 366-380.
    7. 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.
    8. Jelnov, Pavel & Weiss, Yoram, 2022. "Influence in economics and aging," Labour Economics, Elsevier, vol. 77(C).
    9. Bardazzi, Rossella & Pazienza, Maria Grazia, 2018. "Ageing and private transport fuel expenditure: Do generations matter?," Energy Policy, Elsevier, vol. 117(C), pages 396-405.
    10. 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.
    11. Päivi Kankaanranta, 2019. "A Cohort-Analysis of Age-Wealth Profile in Finland," Discussion Papers 130, Aboa Centre for Economics.
    12. Zoë Fannon & B. Nielsen, 2018. "Age-period cohort models," Economics Papers 2018-W04, Economics Group, Nuffield College, University of Oxford.
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    14. 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.
    15. 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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    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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