Bayesian Estimation of a Dynamic Model of Two-Sided Markets: Application to the U.S. Video Game Industry
构建并估计了一个包含耐用平台中介和附属产品的双边市场结构模型，应用于美国32/64位视频游戏产业，发现平台参与者的动态行为显著影响平台采用和附属产品市场，且失败平台若在动态双边市场中合理定价本可存活。
This paper develops and estimates a structural model of two-sided markets with durable platform intermediaries and affiliated products. It models buyers’ purchase decisions of platforms and affiliated products and sellers’ decisions of price setting and entry, accounting for the dynamic interaction between the two distinct groups of platform participants. To estimate the proposed model, this paper develops a Bayesian Markov chain Monte Carlo estimation approach that incorporates nonparametric approximation and interpolation methods. The proposed model and estimation method are applied to the 32/64-bit generation of the U.S. video game industry. The results of counterfactual experiments show that the dynamic behavior of platform participants has significant impacts on platform adoption and the affiliated product market, and that a failed platform could have survived if it had priced the two sides properly in a dynamic two-sided market environment. This paper was accepted by Matthew Shum, marketing.