Constrained optimization approaches to estimation of structural models

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Discussion Paper ; No. 1460

Classification and Topics

• Classification: Wirtschaft
• Subject: structural estimation ; dynamic discrete choice models ; constrained optimization

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Su, Che-Lin ; Judd, Kenneth L.
• Event: Veröffentlichung
• (who): Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science
• (where): Evanston, IL
• (when): 2011

Further information

• Handle: http://hdl.handle.net/10419/59626
• Last update: 10.03.2025, 11:41 AM CET