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Simulation and the Asymptotics of Optimization Estimators
Abstract
A general central limit theorem is proved for estimators defined by minimization of the length of a vector-valued, random criterion function. No smoothness assumptions are imposed on the criterion function in order that the results might apply to a broad class of simulation estimators. Complete analyses of two simulation estimators, one introduced by A. Pakes (1986) and the other by D. McFadden (1989), illustrate the application of the general theorems. These examples illustrate how simulation can be used to circumvent two computational problems that arise frequently in applied econometrics: evaluating intractable aggregation formulae and evaluating discrete response probabilities. Copyright 1989 by The Econometric Society.
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Citations
Cited by
Discrete Choice Methods with Simulation
Train, K. E. (2001) · doi:10.1017/cbo9780511805271 · Cited by 7,784
Automobile Prices in Market Equilibrium
Berry, S., Levinsohn, J., & Pakes, A. (1995) · Econometrica · doi:10.2307/2171802 · Cited by 4,883
Self-citationChapter 36 Large sample estimation and hypothesis testing
Newey, W. K., & McFadden, D. (1994) · Handbook of Econometrics · doi:10.1016/s1573-4412(05)80005-4 · Cited by 1,743
Incentives Work: Getting Teachers to Come to School
Duflo, E., Hanna, R., & Ryan, S. P. (2012) · American Economic Review · doi:10.1257/aer.102.4.1241 · Cited by 928
Adda, J., Dustmann, C., & Stevens, K. (2017) · Journal of Political Economy · doi:10.1086/690952 · Cited by 467
Metadata
- Authors
- Pakes, A., & Pollard, D.
- Venue
- Econometrica
- Publisher
- JSTOR
- Published
- 1989-09
- Volume
- 57
- Issue
- 5
- Pages
- 1027
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2005747881
- Cited by
- 1,494
- References
- 0
- FWCI
- 22.57
- Type
- journal article
- Language
- en
- Open access
- closed
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