Reallocating Bonus Payments Through Competition to Improve Medicare Advantage Plan Quality: A Dynamic Game Approach

This thesis contains two chapters that study competition among firms in regulated markets and auctions. The first chapter of the thesis explores how competition among firms can be used to improve the quality of plan offerings in a managed care setting like Medicare Advantage through changes in the reimbursement policy of the government. In a managed market, private firms provide government sponsored services at regulated prices and compete for subsidies. I study how firms offering Medicare Advantage plans compete in terms of quality and evaluate how the markets would evolve under a competitive bonus payment system rewarding them based on their relative quality performance in a local market. I introduce a dynamic discrete game model of firm quality investment choice and use it to estimate the cost of quality improvements. The estimated model is used to predict the market outcomes in terms of average plan quality under the alternative payment system by calculating the counterfactual equilibria and simulating the markets forward. The results show that 65\% of the counties improve under the new payment rule compared to their observed outcomes in the data, with underperforming counties improving more. \\ The second chapter of the thesis studies collusive behavior of bidders in an ascending price auction. Any exchange of private information or an agreement among participants regarding their behavior in an auction is prohibited by anti-trust laws. I introduce a method of empirically detecting the identities of such colluders under selective entry using the participation and bidding behavior of the potential bidders. I discard the assumption that only the ring leader is observed to participate in every auction, which has been previously used to create the suspect group. I then devise a two-step estimation process where the identity of the colluding members is identified from the identity of the participants, winners, and the value of the winning bid in an ascending price auction. We use both the participation probabilities and distribution of final price across auctions to create the suspect group and show that the identities of the colluders can be detected using a pairwise comparison index