Scenario Sampling for Large Supermodular Games / Bryan S. Graham, Andrin Pelican.

Format:

Book

Author/Creator:

Graham, Bryan S.

Contributor:

National Bureau of Economic Research.

Pelican, Andrin.

Series:

Working Paper Series (National Bureau of Economic Research) no. w31511.

NBER working paper series no. w31511

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2023.

Summary:

This paper introduces a simulation algorithm for evaluating the log-likelihood function of a large supermodular binary-action game. Covered examples include (certain types of) peer effect, technology adoption, strategic network formation, and multi-market entry games. More generally, the algorithm facilitates simulated maximum likelihood (SML) estimation of games with large numbers of players, T, and/or many binary actions per player, M (e.g., games with tens of thousands of strategic actions, TM=O(10⁴)). In such cases the likelihood of the observed pure strategy combination is typically (i) very small and (ii) a TM-fold integral who region of integration has a complicated geometry. Direct numerical integration, as well as accept-reject Monte Carlo integration, are computationally impractical in such settings. In contrast, we introduce a novel importance sampling algorithm which allows for accurate likelihood simulation with modest numbers of simulation draws.

Notes:

Print version record

July 2023.