Improving the performance of random coefficients demand models: The role of optimal instruments
AbstractWe shed new light on the performance of Berry, Levinsohn and Pakes? (1995) GMM estimator of the aggregate random coe¢ cient logit model. Based on an extensive Monte Carlo study, we show that the use of Chamberlain?s (1987) optimal instruments overcomes most of the problems that have recently been documented with standard, non-optimal instruments. Optimal instruments reduce small sample bias, but prove even more powerful in increasing the estimator?s e¢ ciency and stability. Other recent methodological advances (MPEC, polynomial-based integration of the market shares) greatly improve computational speed, but they are only successful in terms of bias and e¢ ciency when combined with optimal instruments.
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Bibliographic InfoPaper provided by University of Antwerp, Faculty of Applied Economics in its series Working Papers with number 2012011.
Length: 31 pages
Date of creation: Jun 2012
Date of revision:
Other versions of this item:
- Reynaert, Mathias & Verboven, Frank, 2012. "Improving the performance of random coefficients demand models: the role of optimal instruments," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/350314, Katholieke Universiteit Leuven.
- Mathias REYNAERT & Frank VERBOVEN, 2012. "Improving the performance of random coefficients demand models: the role of optimal instruments," Center for Economic Studies - Discussion papers ces12.07, Katholieke Universiteit Leuven, Centrum voor Economische Studiën.
- Reynaert, Mathias & Verboven, Frank, 2012. "Improving the Performance of Random Coefficients Demand Models: the Role of Optimal Instruments," CEPR Discussion Papers 9026, C.E.P.R. Discussion Papers.
- C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
- L00 - Industrial Organization - - General - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-06-25 (All new papers)
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