Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/59626 
Year of Publication: 
2011
Series/Report no.: 
Discussion Paper No. 1460
Publisher: 
Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science, Evanston, IL
Abstract: 
Estimating 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.
Subjects: 
structural estimation
dynamic discrete choice models
constrained optimization
Document Type: 
Working Paper

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