【主题】Estimating Social Network Models with Missing Links
【报告人】Arthur Lewbel（教授，波士顿学院）
【时间】2023年11月7日周二15:30-17:00
【地点】经济学院710室
【语言】英语
【摘要】We propose an adjusted 2SLS estimator for social network models when some existing network links are missing from the sample (due, e.g., to recall errors by survey respondents, or lapses in data input). In the feasible structural form, missing links make all covariates endogenous and add a new source of correlation between the structural errors and endogenous peer outcomes (in addition to simultaneity), thus invalidating conventional estimators used in the literature. We resolve these issues by rescaling peer outcomes with estimates of missing rates and constructing instruments that exploit properties of the noisy network measures. We apply our method to study peer effects in household decisions to participate in a microfinance program in Indian villages. We find that ignoring missing links and applying conventional instruments would result in a sizeable upward bias in peer effect estimates.
【报告人简介】Arthur Lewbel，美国波士顿学院教授，MIT大学经济学博士。文章多次发表于Econometrica，American Economic Review，Journal of Political Economy，Quarterly Journal of Economics，Review of Economic Studies，Journal of Econometrics等国际顶级经济学期刊。现任Econometric Theory的联合主编，曾任Journal of Business and Economic Statistics和Economics Letters联合主编及Econometric Theory, Journal of Applied Econometrics和Journal of Econometrics的副主编，并当选为国际应用计量经济学学会会士（Fellow of the International Association of Applied Econometrics）。研究领域包括非参数模型的理论识别和实证估计，其研究广泛应用于产业组织及劳动经济学实证估计。
