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Testing the nested fixed-point algorithm in BLP random coefficients demand estimation
- Issue Date
- 2017
- Publisher
- Korean Econometric Society
- Keywords
- Nested fixedpoint algorithm; Newton’s method; Numerical methods; Random coefficients logit demand
- Citation
- Journal of Economic Theory and Econometrics, v.28, no.4, pp.1 - 21
- Indexed
- SCOPUS
KCI
- Journal Title
- Journal of Economic Theory and Econometrics
- Volume
- 28
- Number
- 4
- Start Page
- 1
- End Page
- 21
- ISSN
- 1229-2893
- Abstract
- This paper examines the numerical properties of the nested fixed point algorithm (NFP) using Monte Carlo experiments in the estimation of Berry, Levinsohn, and Pakes’s (1995) random coefficient logit demand model. We find that in speed, convergence and accuracy, nested fixed-point (NFP) approach using Newton’s method performs well like a mathematical programming with equilibrium constraints (MPEC) approach adopted by Dubé, Fox, and Su (2012). © 2017, Korean Econometric Society. All rights reserved.
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