Working Paper: NBER ID: w11900
Authors: Gabriel Weintraub; C. Lanier Benkard; Ben Van Roy
Abstract: We propose an approximation method for analyzing Ericson and Pakes (1995)-style dynamic models of imperfect competition. We develop a simple algorithm for computing an ``oblivious equilibrium,'' in which each firm is assumed to make decisions based only on its own state and knowledge of the long run average industry state, but where firms ignore current information about competitors' states. We prove that, as the market becomes large, if the equilibrium distribution of firm states obeys a certain ``light-tail'' condition, then oblivious equilibria closely approximate Markov perfect equilibria. We develop bounds that can be computed to assess the accuracy of the approximation for any given applied problem. Through computational experiments, we find that the method often generates useful approximations for industries with hundreds of firms and in some cases even tens of firms.
Keywords: dynamic models; imperfect competition; Markov Perfect Equilibria; approximation method
JEL Codes: C63; C73; L11; L13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| oblivious equilibrium (D50) | Markov Perfect Equilibria (MPE) (C73) |
| market size increases (D40) | oblivious equilibrium approximates MPE closely (D00) |
| equilibrium distribution satisfies light-tail condition (C46) | oblivious equilibrium approximates MPE closely (D00) |
| increase in vertical product differentiation (F12) | transition from fragmented to concentrated market structure (L19) |
| oblivious strategies (L21) | improved understanding of industry dynamics (L16) |