« Getting The Fine Down Cartel Regulation 2011 | Main | Breaking News - European Commission posts its Public consultation: Towards a Coherent European Approach to Collective Redress »
February 4, 2011
Simple Markov-perfect industry dynamics
Posted by D. Daniel Sokol
Jaap H. Abbring (CentER, Department of Econometrics & OR, Tilburg University), Jeffrey R. Campbell (Federal Reserve Bank of Chicago), and Nan Yang (VU University Amsterdam and Tinbergen Institute) analyze Simple Markov-perfect industry dynamics.
ABSTRACT: This paper develops a tractable model for the computational and empirical analysis of infinite-horizon oligopoly dynamics. It features aggregate demand uncertainty, sunk entry costs, stochastic idiosyncratic technological progress, and irreversible exit. We develop an algorithm for computing a symmetric Markov-perfect equilibrium quickly by finding the fixed points to a finite sequence of low-dimensional contraction mappings. If at most two heterogenous firms serve the industry, the result is the unique "natural" equilibrium in which a high profitability firm never exits leaving behind a low profitability competitor. With more than two firms, the algorithm always finds a natural equilibrium. We present a simple rule for checking ex post whether the calculated equilibrium is unique, and we illustrate the model's application by assessing how price collusion impacts consumer and total surplus in a market for a new product t! hat requires costly development. The results confirm Fershtman and Pakes' (2000) finding that collusive pricing can increase consumer surplus by stimulating product development. A distinguishing feature of our analysis is that we are able to assess the results' robustness across hundreds of parameter values in only a few minutes on an off-the-shelf laptop computer.
February 4, 2011 | Permalink
TrackBack
TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341bfae553ef0147e16aae7c970b
Listed below are links to weblogs that reference Simple Markov-perfect industry dynamics:
