政府與行政學系講座: Causal Inference with Panel Data under Temporal and Spatial Interference
講者: 王也教授, 助理教授, 政治學院, 北卡羅來納大學教堂山分校
日期：2024年3月15日 (星期五)
時間：09:30 – 11:00
地點: Zoom https://umac.zoom.us/j/93997071548?pwd=SVVmbmdQeEF2VXU5WHByOXZNQnhHQT09
會議ID: 939 9707 1548
密碼: 678685
內容: Many social events and policy interventions generate treatment effects that persistently spill over into neighboring areas, resulting in a phenomenon statisticians refer to as “interference” both in time and space. In this paper, I put forward a design-based framework to identify and estimate these spillover effects in panel data with a spatial dimension, when temporal and spatial interference intertwine in intricate ways that are unknown to researchers. The framework defines estimands that enable researchers to measure the influence of each type of interference, and I propose estimators that are consistent and asymptotically normal under the assumption of sequential ignorability and mild regularity conditions. I show that fixed effects models in panel data analysis, such as the difference-in-differences (DID) estimator, can lead to significant biases in such scenarios. I test the method’s performance on both simulated datasets and the replication of two empirical studies.
