G2TT
来源类型Discussion paper
规范类型论文
来源IDDP14363
DP14363 Identification and Estimation of Demand for Bundles
Alessandro Iaria
发表日期2020-01-29
出版年2020
语种英语
摘要We present novel identification and estimation results for a mixed logit model of demand for bundles with endogenous prices given bundle-level market shares. Our approach hinges on an affine relationship between the utilities of single products and of bundles, on an essential real analytic property of the mixed logit model, and on the existence of exogenous cost shifters. We propose a new demand inverse in the presence of complementarity that enables to concentrate out of the likelihood function the (potentially numerous) market-product specific average utilities, substantially alleviating the challenge of dimensionality inherent in estimation. To illustrate the use of our methods, we estimate demand and supply in the US ready-to-eat cereal industry, where the proposed MLE reduces the numerical search from approximately 12000 to 130 parameters. Our estimates suggest that ignoring Hicksian complementarity among different products often purchased in bundles may result in misleading demand estimates and counterfactuals.
主题Industrial Organization
URLhttps://cepr.org/publications/dp14363
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/543257
推荐引用方式
GB/T 7714
Alessandro Iaria. DP14363 Identification and Estimation of Demand for Bundles. 2020.
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