6 papers
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…
Statistical Decision Theory with Counterfactual Loss
Benedikt Koch, Kosuke Imai
Many researchers apply classical statistical decision theory to evaluate treatment choices and learn optimal policies. However, because this framework relies solely on realized out…
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…