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

• Tác giả: Michael P Leung
• Ngôn ngữ: eng
• Ký hiệu phân loại: 302.13 Social choice
• Thông tin xuất bản: 2019
• Bộ sưu tập: Metadata
• ID: 163611

Tóm tắt

This paper studies inference in models of discrete choice with social interactions when the data consists of a single large network. We provide theoretical justification for the use of spatial and network HAC variance estimators in applied work, the latter constructed by using network path distance in place of spatial distance. Toward this end, we prove new central limit theorems for network moments in a large class of social interactions models. The results are applicable to discrete games on networks and dynamic models where social interactions enter through lagged dependent variables. We illustrate our results in an empirical application and simulation study.