{'fraction_non_alphanumeric': 0.020637898686679174, 'fraction_numerical': 0.0, 'mean_word_length': 5.883870967741935, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Markov-Perfect Network Formation An Applied Framework for Bilateral Oligopoly and Bargaining in Buyer-Seller Networks ∗

We develop a tractable and applicable dynamic model of network formation with transfers in the presence of externalities. Our primary application is the estimation of primitives and prediction of counterfactual outcomes in bilateral oligopoly and buyer-seller networks. The framework takes as primitives each agent’s static profits, and provides the equilibrium recurrent class of networks and negotiated transfers. Importantly, agents anticipate future changes to the network, and links may be costly to form, maintain, or break. We detail the computation and estimation of a Markov-Perfect equilibrium in this environment, and highlight the approach using simulated data motivated by insurer-hospital negotiations. We explore the impact of hospital mergers on negotiated payments, insurer premiums, and consumer welfare, and demonstrate how accounting for dynamics yields substantively different predictions than traditional static approaches.