Treatment Effect Accounting for Network Changes

• 成果类型: Article
• 署名作者: Comola, Margherita; Prina, Silvia
• 署名单位: Universite Paris Saclay; Paris School of Economics; Northeastern University
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest_a_00908
• 发表日期: 2021-07
• 页码: 597-604
• 关键词: spatial autoregressive model; social networks; identification; savings; gmm

摘要

Networks may rewire in response to interventions. We propose a measure of the treatment effect when an intervention affects the structure of a social network. We develop a treatment-response model that incorporates dynamic peer effects and provide its identification conditions and the associated instrumental-variable strategy. We illustrate our estimation procedure using a panel data set containing information on a financial network before and after a field experiment that randomized access to savings accounts. Results show that neglecting the network change results in underestimation of the impact of the intervention and the role played by informal networks through which the intervention diffuses.