Structural Analysis of Nonlinear Pricing
Luo, Yao; Perrigne, Isabelle; Vuong, Quang
This paper proposes a new methodology for analyzing nonlinear pricing data. We establish identification of the model primitives with a known tariff and characterize the model restrictions on observables. We propose a quantile-based nonparametric estimator that achieves consistency at the parametric rate. We introduce unobserved product heterogeneity with an unknown tariff and show how our identification and estimation results extend. A Monte Carlo study analyzes the robustness of our methodology to menus of two-part tariffs. Analysis of cellular service data assesses the performance of various pricing strategies. We discuss extensions to network effects, multiproduct firms, bundling, differentiated products, and oligopolies.