Estimation of Random-Coefficient Demand Models: Two Empiricists' Perspective

Christopher Knittel and Konstantinos Metaxoglou
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Konstantinos Metaxoglou: Bates White LLC

The Review of Economics and Statistics, 2014, vol. 96, issue 1, 34-59

Abstract: We document the numerical challenges we experienced estimating random-coefficient demand models as in Berry, Levinsohn, and Pakes (1995) using two well-known data sets and a thorough optimization design. The optimization algorithms often converge at points where the first- and second-order optimality conditions fail. There are also cases of convergence at local optima. On convergence, the variation in the values of the parameter estimates translates into variation in the models' economic predictions. Price elasticities and changes in consumer and producer welfare following hypothetical merger exercises vary at least by a factor of 2 and up to a factor of 5. © 2014 The President and Fellows of Harvard College and the Massachusetts Institute of Technology

Keywords: random-coefficient demand; optimization (search for similar items in EconPapers)
JEL-codes: C61 C63 L13 L44 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (74)

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