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A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration
Abstract
This paper proposes a simple modification of a conventional method of moments estimator for a discrete response model, replacing response probabilities that require numerical integration with estimators obtained by Monte Carlo simulation.This method of simulated moments (MSM) does not require precise estimates of these probabilities for consistency and asymptotic normality, relying instead on the law of large numbers operating across observations to control simulation error, and hence can use simulations of practical size.The method is useful for models such as high-dimensional multinomial probit (MNP), where computation has restricted applications.
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Citations
Cited by
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Train, K. E. (2001) · doi:10.1017/cbo9780511805271 · Cited by 7,784
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Kamakura, W. A., Wedel, M., de Rosa, F., & Mazzon, J. A. (2003) · International Journal of Research in Marketing · doi:10.1016/s0167-8116(02)00121-0 · Cited by 336
Ursu, R. M. (2018) · Marketing Science · doi:10.1287/mksc.2017.1072 · Cited by 328
Payday Loans, Uncertainty and Discounting: Explaining Patterns of Borrowing, Repayment, and Default
Skiba, P. M., & Tobacman, J. (2008) · doi:10.2139/ssrn.1319751 · Cited by 157
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(1999) · Handbook of Labor Economics · doi:10.1016/s1573-4463(99)03005-9 · Cited by 152
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Jiang, J. (1998) · Journal of the American Statistical Association · doi:10.1080/01621459.1998.10473724 · Cited by 149
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Metadata
- Authors
- McFadden, D.
- Venue
- Econometrica
- Publisher
- JSTOR
- Published
- 1989-09
- Volume
- 57
- Issue
- 5
- Pages
- 995
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2019302713
- Cited by
- 1,637
- References
- 0
- FWCI
- 64.54
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
