Estimating Local Interactions Among Many Agents Who Observe Their Neighbors
Nathan Canen, Jacob Schwartz, Kyungchul Song

TL;DR
This paper introduces a tractable linear model for local strategic interactions among agents in large networks, enabling inference without observing the entire network or knowing the full structure.
Contribution
It develops a new empirical framework that simplifies modeling local interactions in large networks with incomplete information, using linear best responses.
Findings
Explicit form of best responses under certain network conditions
Local payoff interdependence translates into observable local action dependence
Enables asymptotic inference with partial network data
Abstract
In various economic environments, people observe other people with whom they strategically interact. We can model such information-sharing relations as an information network, and the strategic interactions as a game on the network. When any two agents in the network are connected either directly or indirectly in a large network, empirical modeling using an equilibrium approach can be cumbersome, since the testable implications from an equilibrium generally involve all the players of the game, whereas a researcher's data set may contain only a fraction of these players in practice. This paper develops a tractable empirical model of linear interactions where each agent, after observing part of his neighbors' types, not knowing the full information network, uses best responses that are linear in his and other players' types that he observes, based on simple beliefs about the other…
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Taxonomy
TopicsGame Theory and Applications · Experimental Behavioral Economics Studies · Economic theories and models
