Reynaert, Mathias and Verboven, Frank (2014) Improving the performance of random coefficients demand models: The role of optimal instruments. Journal of Econometrics, 179 (1). pp. 83-98.

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We shed new light on the performance of Berry, Levinsohn and Pakes' (1995) GMM estimator of the aggregate random coefficient logit model. Based on an extensive Monte Carlo study, we show that the use of Chamberlain’s (1987) optimal instruments overcomes many problems that have recently been documented with standard, non-optimal instruments. Optimal instruments reduce small sample bias, but they prove even more powerful in increasing the estimator's efficiency and stability. We consider a wide variety of data-generating processes and an empirical application to the automobile market. We also consider the gains of other recent methodological advances when combined with optimal instruments.

Item Type: Article
Language: English
Date: 2014
Refereed: Yes
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 05 Nov 2015 15:11
Last Modified: 02 Apr 2021 15:50
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