# Demand and Welfare Analysis in Discrete Choice Models with Social Interactions

## TL;DR

This paper introduces new empirical tools to analyze demand and welfare effects of policies in binary choice models with social interactions, highlighting the importance of underlying mechanisms and providing bounds on welfare impacts.

## Contribution

It connects large game econometrics with social interaction models, develops convergence results, and shows limitations of choice data for welfare analysis despite unique equilibria.

## Key findings

- Choice data are insufficient for welfare calculations under social interactions.
- Distribution-free bounds on welfare can be derived using index restrictions.
- Experimental data on mosquito-net adoption illustrate the theoretical results.

## Abstract

Many real-life settings of consumer-choice involve social interactions, causing targeted policies to have spillover-effects. This paper develops novel empirical tools for analyzing demand and welfare-effects of policy-interventions in binary choice settings with social interactions. Examples include subsidies for health-product adoption and vouchers for attending a high-achieving school. We establish the connection between econometrics of large games and Brock-Durlauf-type interaction models, under both I.I.D. and spatially correlated unobservables. We develop new convergence results for associated beliefs and estimates of preference-parameters under increasing-domain spatial asymptotics. Next, we show that even with fully parametric specifications and unique equilibrium, choice data, that are sufficient for counterfactual demand-prediction under interactions, are insufficient for welfare-calculations. This is because distinct underlying mechanisms producing the same interaction coefficient can imply different welfare-effects and deadweight-loss from a policy-intervention. Standard index-restrictions imply distribution-free bounds on welfare. We illustrate our results using experimental data on mosquito-net adoption in rural Kenya.