Suchergebnisse

AbstractI develop a multiproduct nonlinear pricing model where a firm sells both discrete and continuous services to consumers with multidimensional heterogeneity. I derive the optimal selling mechanism and provide primitive conditions under which different bundling strategies arise. Exploiting both the firm and the consumer's optimality conditions, I show that the model structure is nonparametrically identified and propose a semiparametric estimation procedure. An application to China Telecom data shows that mixed bundling of internet and landline phone services is more beneficial to both the firm and the consumer relative to component pricing.

AbstractUncertainty about ex post realized values is an inherent component in many auction environments. In this article, we develop a structural framework to analyze auction data subject to ex post uncertainty as a pure risk. We consider a low‐price sealed‐bid auction model with heterogeneous bidders' preferences and ex post uncertainty. The uncertainty can be common to all bidders or idiosyncratic. We derive the model restrictions and study nonparametric and semiparametric identification of the model primitives under exogenous and endogenous participation. We then develop multistep nonparametric and semiparametric estimation procedures in both cases.