Dynamic Pricing and Entry ina Two-Sided Market: The Case of Video Games

In two-sided markets with positive indirect network e�ect, the number of consumers on a platform depends on the entry and prices of the a�liated products, and the success of the a�liated products depends on the number of consumers. Moreover, platform markets are often inherently dynamic environments due to the durability of platform intermediaries and the a�liated products. In the dynamic two-sided market environment, overpricing one side of the market not only discourages demand on that side but also discourages participation on the other side, and so can lead to a death spiral. This dissertation presents a dynamic structural model to analyze consumers' purchase decisions for competing hardware platforms and their a�liated software products, and software �rms' dynamic pricing and entry decisions. Consumers are heterogeneous and forward-looking and have rational expectations about software entry and prices in the future. They choose when to purchase the hardware and the a�liated software. Software �rms decide on price and whether to a�liate with a platform, accounting for competitors' reactions, consumer composition, and consumer forwardlooking behavior. This dissertation provides a new practical methodology for structural estimation of dynamic equilibrium models. It combines the Bayesian Markov Chain Monte Carlo (MCMC) algorithm and the dynamic equilibrium model solution algorithm into a single algorithm that estimates the parameters and solves the model simultaneously. It partially solves for each agent's best response and value function given that other agents play the equilibrium strategies at each draw of parameter vectors. It uses those pseudo-best response functions and pseudo-value functions to non-parametrically approximate the equilibrium strategies and the value functions at the current trial paii rameter vector. The estimation method is applied to the U.S.

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