The author proposes a way to model firm mergers using a matching game known as the roommate problem, whereby the firms are assumed to make preference rankings of potential merger partners. The position of a firm in another firm’s ranking is assumed to be governed by an index, which in turn consists of a deterministic part and of a stochastic part, similar to the latent indices used in standard discrete choice models. Given preferences of all the firms, game-theoretic mechanisms leads to a matching, whereby each firm is either self-matched or assigned a merger partner. The author derive expressions for the probability of a merger between a specific firm pair, and also a log-likelihood function for estimation using firm specific data. Using simulation in a setting with groups of three firms involved in roommate game, within each group, the paper examines the finite sample properties of the model.
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