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dc.contributor.authorSu, Che-Linen_US
dc.contributor.authorJudd, Kenneth L.en_US
dc.description.abstractEstimating structural models is often viewed as computationally difficult, an impression partly due to a focus on the nested fixed-point (NFXP) approach. We propose a new constrained optimization approach for structural estimation. We show that our approach and the NFXP algorithm solve the same estimation problem, and yield the same estimates. Computationally, our approach can have speed advantages because we do not repeatedly solve the structural equation at each guess of structural parameters. Monte Carlo experiments on the canonical Zurcher bus-repair model demonstrate that the constrained optimization approach can be significantly faster.en_US
dc.publisherNorthwestern Univ., Kellogg Graduate School of Management, Center for Mathematical Studies in Economics and Management Science Evanstonen_US
dc.relation.ispartofseriesDiscussion Paper, Center for Mathematical Studies in Economics and Management Science 1460en_US
dc.subject.keywordstructural estimationen_US
dc.subject.keyworddynamic discrete choice modelsen_US
dc.subject.keywordconstrained optimizationen_US
dc.titleConstrained optimization approaches to estimation of structural modelsen_US
dc.typeWorking Paperen_US
Appears in Collections:Discussion Papers, Kellogg School of Management, Northwestern University

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