This paper develops a simple model of firm entry, competition, and exit in oligopolistic markets. It features toughness of competition, sunk entry costs, and market-level demand and cost shocks, but assumes that firms' expected payoffs are identical when entry and survival decisions are made.We prove that this model has an essentially unique symmetric Markov-perfect equilibrium, and we provide an algorithm for its computation. Because this algorithm only requires finding the fixed points of a finite sequence of contraction mappings, it is guaranteed to converge quickly.
This paper develops a simple model of firm entry, competition, and exit in oligopolistic markets. It features toughness of competition, sunk entry costs, and market‐level demand and cost shocks, but assumes that firms' expected payoffs are identical when entry and survival decisions are made. We prove that this model has an essentially unique symmetric Markov‐perfect equilibrium, and we provide an algorithm for its computation. Because this algorithm only requires finding the fixed points of a finite sequence of contraction mappings, it is guaranteed to converge quickly.
This paper develops an econometric model of industry dynamics for concentrated markets that can be estimated very quickly from market-level panel data on the number of producers and consumers using a nested fixedpoint algorithm. We show that the model has an essentially unique symmetric Markov-perfect equilibrium that can be calculated from the fixed points of a finite sequence of low-dimensional contraction mappings. Our nested fixed point procedure extends Rust's (1987) to account for the observable implications of mixed strategies on survival. We illustrate the model's empirical application with ten years of County Business Patterns data from the Motion Picture Theaters industry in 573 Micropolitan Statistical Areas. The results are suggestive of fierce competition between theaters in the market for film exhibition rights.
This paper develops an econometric model of firm entry, competition, and exit in oligopolistic markets. The model has an essentially unique symmetric Markov-perfect equilibrium, which can be computed very quickly. We show that its primitives are identified from market-level data on the number of active firms and demand shifters, and we implement a nested fixed point procedure for its estimation. Estimates from County Business Patterns data on U.S. local cinema markets point to tough local competition. Sunk costs make the industry's transition following a permanent demand shock last 10 to 15 years.
We analyze reputation dynamics in an online market for illicit drugs using a novel dataset of prices and ratings. The market is a black market, and so contracts cannot be enforced. We study the role that reputation plays in alleviating adverse selection in this market. We document the following stylized facts: (i) There is a positive relationship between the price and the rating of a seller. This effect is increasing in the number of reviews left for a seller. A mature highly-rated seller charges a 20% higher price than a mature low-rated seller. (ii) Sellers with more reviews charge higher prices regardless of rating. (iii) Low-rated sellers are more likely to exit the market and make fewer sales. We show that these stylized facts are explained by a dynamic model of adverse selection, ratings, and exit, in which buyers form rational inferences about the quality of a seller jointly from his rating and number of sales. Sellers who receive low ratings initially charge the same price as highly-rated sellers since early reviews are less informative about quality. Bad sellers exit rather than face lower prices in the future. We provide conditions under which our model admits a unique equilibrium. We estimate the model, and use the result to compute the returns to reputation in the market. We find that the market would have collapsed due to adverse selection in the absence of a rating system.
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