Inference in Models of Discrete Choice with Social Interactions Using Network Data

Discrete Choice with Social Interactions

This paper provides an analysis of aggregate behavioural outcomes when individual utility exhibits social interaction effects. We study generalized logistic models of individual choice which incorporate terms reflecting the desire of individuals to conform to the behaviour of others in an environment of noncooperative decisionmaking. Laws of large numbers are generated in such environments. Mul...

Social Discrete Choice Models

Human decision making underlies data generating process in multiple application areas, and models explaining and predicting choices made by individuals are in high demand. Discrete choice models are widely studied in economics and computational social sciences. As digital social networking facilitates information flow and spread of influence between individuals, new advances in modeling are nee...

Data Models for Discrete Choice

Dynamic Discrete Choice Models with Lagged Social Interactions: with an Application to a Signaling Game Experiment

This article generalizes Heckman’s (1981) dynamic discrete choice panel data models by introducing lagged social interactions, so that the models can accommodate interrelationships of decisions across cross-sectional units. The likelihood function for a general model with dynamic social interactions is derived and simulation methods based on the unbiased GHK simulator are proposed to implement ...

Variational inference for large-scale models of discrete choice

Discrete choice models are commonly used by applied statisticians in numerous fields, such as marketing, economics, finance, and operations research. When agents in discrete choice models are assumed to have differing preferences, exact inference is often intractable. Markov chain Monte Carlo techniques make approximate inference possible, but the computational cost is prohibitive on the large ...