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Comment on “Constrained Optimization Approaches to Estimation of Structural Models”

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  • Fedor Iskhakov
  • Jinhyuk Lee
  • John Rust
  • Bertel Schjerning
  • Kyoungwon Seo

Abstract

We revisit the comparison of mathematical programming with equilibrium constraints (MPEC) and nested fixed point (NFXP) algorithms for estimating structural dynamic models by Su and Judd (2012). Their implementation of the nested fixed point algorithm used successive approximations to solve the inner fixed point problem (NFXP‐SA). We redo their comparison using the more efficient version of NFXP proposed by Rust (1987), which combines successive approximations and Newton–Kantorovich iterations to solve the fixed point problem (NFXP‐NK). We show that MPEC and NFXP are similar in speed and numerical performance when the more efficient NFXP‐NK variant is used.

Suggested Citation

  • Fedor Iskhakov & Jinhyuk Lee & John Rust & Bertel Schjerning & Kyoungwon Seo, 2016. "Comment on “Constrained Optimization Approaches to Estimation of Structural Models”," Econometrica, Econometric Society, vol. 84, pages 365-370, January.
  • Handle: RePEc:wly:emetrp:v:84:y:2016:i::p:365-370
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    Cited by:

    1. Patrick Kofod Mogensen, 2018. "Solving Dynamic Discrete Choice Models: Integrated or Expected Value Function?," Papers 1801.03978, arXiv.org.
    2. Abbring, Jaap & Campbell, J.R. & Tilly, J. & Yang, N., 2017. "Very Simple Markov-Perfect Industry Dynamics : Empirics," Discussion Paper 2017-021, Tilburg University, Center for Economic Research.
    3. Lee, Jinhyuk & Seo, Kyoungwon, 2016. "Revisiting the nested fixed-point algorithm in BLP random coefficients demand estimation," Economics Letters, Elsevier, vol. 149(C), pages 67-70.

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