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The endogenous grid method for discrete‐continuous dynamic choice models with (or without) taste shocks

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  • Fedor Iskhakov
  • Thomas H. Jørgensen
  • John Rust
  • Bertel Schjerning

Abstract

We present a fast and accurate computational method for solving and estimating a class of dynamic programming models with discrete and continuous choice variables. The solution method we develop for structural estimation extends the endogenous grid‐point method (EGM) to discrete‐continuous (DC) problems. Discrete choices can lead to kinks in the value functions and discontinuities in the optimal policy rules, greatly complicating the solution of the model. We show how these problems are ameliorated in the presence of additive choice‐specific independent and identically distributed extreme value taste shocks that are typically interpreted as “unobserved state variables” in structural econometric applications, or serve as “random noise” to smooth out kinks in the value functions in numerical applications. We present Monte Carlo experiments that demonstrate the reliability and efficiency of the DC‐EGM algorithm and the associated maximum likelihood estimator for structural estimation of a life‐cycle model of consumption with discrete retirement decisions.

Suggested Citation

  • Fedor Iskhakov & Thomas H. Jørgensen & John Rust & Bertel Schjerning, 2017. "The endogenous grid method for discrete‐continuous dynamic choice models with (or without) taste shocks," Quantitative Economics, Econometric Society, vol. 8(2), pages 317-365, July.
  • Handle: RePEc:wly:quante:v:8:y:2017:i:2:p:317-365
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    Cited by:

    1. Thomas Hintermaier & Winfried Koeniger, 2018. "Differences in Euro-Area Household Finances and their Relevance for Monetary-Policy Transmission," CESifo Working Paper Series 7088, CESifo.
    2. Christopher Busch & Dirk Krueger & Alexander Ludwig & Irina Popova & Zainab Iftikhar, 2020. "Should Germany Have Built a New Wall? Macroeconomic Lessons from the 2015-18 Refugee Wave," Working Papers 2020-020, Human Capital and Economic Opportunity Working Group.
    3. Dennis Kristensen & Patrick K. Mogensen & Jong-Myun Moon & Bertel Schjerning, 2019. "Solving dynamic discrete choice models using smoothing and sieve methods," CeMMAP working papers CWP15/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Sumudu Kankanamge & Alexandre Gaillard, 2019. "Entrepreneurship, Inter-Generational Business Transmission and Aging," 2019 Meeting Papers 1503, Society for Economic Dynamics.
    5. Jang, Youngsoo & Lee, Soyoung, 2019. "A Generalized Endogenous Grid Method for Models with the Option to Default," MPRA Paper 95721, University Library of Munich, Germany.
    6. Alexander Ludwig & Jochen Mankart & Jorge Quintana & Mirko Wiederholt & Nathanael Vellekoop, 2019. "House Price Expectations and Housing Choice," 2019 Meeting Papers 848, Society for Economic Dynamics.
    7. Thomas Hintermaier & Winfried Koeniger, 2018. "Differences in Euro-Area Household Finances and their Relevance for Monetary-Policy Transmission," CESifo Working Paper Series 7088, CESifo.
    8. Kankanamge, Sumudu & Gaillard, Alexandre, 2020. "Buying and Selling Entrepreneurial Assets," TSE Working Papers 20-1078, Toulouse School of Economics (TSE).
    9. Grey Gordon, 2019. "Efficient Computation with Taste Shocks," Working Paper 19-15, Federal Reserve Bank of Richmond, revised 11 Sep 2019.

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