Endogeneity in Entry Games : U.S. Cellphone Service Deployment

In some Bayesian games, payoff-relevant states are influenced by unobserved heterogeneity that also directly affects strategic decisions. When ignored, such endogeneity leads to erroneous parameter inference and policy implications. We introduce a control-function approach for estimating such discrete Bayesian games, and apply the method to an entry game of deploying 4G-LTE technology by major U.S. cellphone service providers. Taking network investment as endogenous, we find that a hypothetical T-Mobile and Sprint merger would reduce 4G-LTE deployment across local markets and disproportionately decrease rural coverage. Ignoring such endogeneity would under-predict the negative impacts of the merger, therefore favoring its approval