5 papers · 1 filter
Dynamic Policy Evaluation and Learning with Spatio-temporal Data
Lingxiao Zhou, Kosuke Imai, Jason Lyall +1
Although sequential decision-making is ubiquitous across domains, policy evaluation and learning with spatio-temporal data remain challenging due to spatial spillover and temporal…
Low-rank Covariate Balancing Estimators under Interference
Souhardya Sengupta, Kosuke Imai, Georgia Papadogeorgou
A key methodological challenge in observational studies with interference between units is twofold: (1) each unit's outcome may depend on many others' treatments, and (2) treatment…
Spatiotemporal causal inference with arbitrary spillover and carryover effects: Airstrikes and insurgent violence in the Iraq War
Mitsuru Mukaigawara, Kosuke Imai, Jason Lyall +1
Social scientists now routinely draw on high-frequency, high-granularity ''microlevel'' data to estimate the causal effects of subnational interventions. To date, most researchers…
Estimating Heterogeneous Treatment Effects for Spatio-Temporal Causal Inference
Lingxiao Zhou, Kosuke Imai, Jason Lyall +1
Scholars from diverse fields increasingly rely on high-frequency spatio-temporal data. Yet, causal inference with these data remains challenging due to spatial spillover and tempor…
Design-based inference for generalized network experiments with stochastic interventions
Ambarish Chattopadhyay, Kosuke Imai, Jose R. Zubizarreta
A growing number of researchers are conducting randomized experiments to analyze causal relationships in network settings where units influence one another. A dominant methodology…