Constrained Optimization Approaches to Estimation of Structural Models: Comment

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

Constrained Optimization Approaches to Estimation of Structural Models: Comment

Fedor Iskhakov, John Rust, Bertel Schjerning, Lee Jinhyuk, 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 (SJ, 2012). They used an inefficient version of the nested fixed point algorithm that relies on successive approximations. We re-do 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-NK are similar in performance when the sample size is relatively small. However, in problems with larger sample sizes, NFXP-NK outperforms MPEC by a significant margin.

Originalsprog	Engelsk
Antal sider	10
Status	Udgivet - 2015

Navn	University of Copenhagen. Institute of Economics. Discussion Papers (Online)
Nummer	5
Vol/bind	2015
ISSN	1601-2461

Adgang til dokumentet

http://www.econ.ku.dk/english/research/publications/wp/dp_2015/1505.pdfLicens: Ikke-specificeret

Citationsformater

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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 (SJ, 2012). They used an inefficient version of the nested fixed point algorithm that relies on successive approximations. We re-do 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-NK are similar in performance when the sample size is relatively small. However, in problems with larger sample sizes, NFXP-NK outperforms MPEC by a significant margin.",

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