Bayesian Estimation of a Dynamic Model of Two-Sided Markets: Application to the US Video Game Industry

• 成果类型: Article
• 署名作者: Zhou, Yiyi
• 署名单位: State University of New York (SUNY) System; Stony Brook University; State University of New York (SUNY) System; Stony Brook University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2016.2529
• 发表日期: 2017
• 页码: 3874-3894
• 关键词: Two-sided market; indirect network effect; Bayesian Markov chain Monte Carlo estimation; video game market

摘要

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.