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Identification and estimation of heterogeneous agent models: A likelihood approach

Author

Listed:
  • Juan Carlos Parra-Alvarez

    (Aarhus University and CREATES)

  • Olaf Posch

    (Hamburg University and CREATES)

  • Mu-Chun Wang

    (Hamburg University)

Abstract

In this paper, we study the statistical properties of heterogeneous agent models with incomplete markets. Using a Bewley-Hugget-Aiyagari model we compute the equilibrium density function of wealth and show how it can be used for likelihood inference. We investigate the identifiability of the model parameters based on data representing a large cross-section of individual wealth. We also study the finite sample properties of the maximum likelihood estimator using Monte Carlo experiments. Our results suggest that while the parameters related to the household's preferences can be correctly identified and accurately estimated, the parameters associated with the supply side of the economy cannot be separately identified leading to inferential problems that persist even in large samples. In the presence of partially identification problems, we show that an empirical strategy based on fixing the value of one of the troublesome parameters allows us to pin down the other unidentified parameter without compromising the estimation of the remaining parameters of the model. An empirical illustration of our maximum likelihood framework using the 2013 SCF data for the U.S. confirms the results from our identification experiments.

Suggested Citation

  • Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2017. "Identification and estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2017-35, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2017-35
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    File URL: ftp://ftp.econ.au.dk/creates/rp/17/rp17_35.pdf
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    References listed on IDEAS

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    1. Brant Abbott & Giovanni Gallipoli & Costas Meghir & Giovanni L. Violante, 2019. "Education Policy and Intergenerational Transfers in Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2569-2624.
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    3. Arlene Wong, 2016. "Population aging and the transmission of monetary policy to consumption," 2016 Meeting Papers 716, Society for Economic Dynamics.
    4. Jess Benhabib & Alberto Bisin & Mi Luo, 2019. "Wealth Distribution and Social Mobility in the US: A Quantitative Approach," American Economic Review, American Economic Association, vol. 109(5), pages 1623-1647, May.
    5. Díaz-Giménez, Javier & Pijoan-Mas, Josep, 2011. "Flat Tax Reforms: Investment Expensing and Progressivity," CEPR Discussion Papers 8238, C.E.P.R. Discussion Papers.
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Yves Achdou & Jiequn Han & Jean-Michel Lasry & Pierre-Louis Lions & Benjamin Moll, 2017. "Income and Wealth Distribution in Macroeconomics: A Continuous-Time Approach," NBER Working Papers 23732, National Bureau of Economic Research, Inc.
    2. Hoang Khieu & Klaus Wälde, 2019. "Capital Income Risk and the Dynamics of the Wealth Distribution," CESifo Working Paper Series 7970, CESifo.
    3. Glawion, Rene & Puche, Marc & Haller, Frédéric, 2020. "A General Equilibrium Model of Earnings, Income, and Wealth," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224580, Verein für Socialpolitik / German Economic Association.
    4. Khieu, Hoang & Wälde, Klaus, 2018. "Capital Income Risk and the Dynamics of the Wealth Distribution," IZA Discussion Papers 11840, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Heterogeneous agent models; Continuous-time; Fokker-Planck equations; Identification; Maximum likelihood;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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