Causal Inference with Spatio-temporal Data: Estimating the Effects of Airstrikes on Insurgent Violence in Iraq

by   Georgia Papadogeorgou, et al.

Although many causal processes have spatial and temporal dimensions, the classical causal inference framework is not directly applicable when the treatment and outcome variables are generated by spatio-temporal point processes. The methodological difficulty primarily arises from the existence of an infinite number of possible treatment and outcome event locations at each point in time. In this paper, we consider a setting where the spatial coordinates of the treatment and outcome events are observed at discrete time periods. We extend the potential outcomes framework by formulating the treatment point process as a stochastic intervention strategy. Our causal estimands include the expected number of outcome events that would occur in an area of interest under a particular stochastic treatment assignment strategy. We develop an estimation technique by applying the inverse probability of treatment weighting method to the spatially-smoothed outcome surfaces. We show that under a set of assumptions, the proposed estimator is consistent and asymptotically normal as the number of time periods goes to infinity. Our motivating application is the evaluation of the effects of American airstrikes on insurgent violence in Iraq from February 2007 to July 2008. We consider interventions that alter the intensity and target areas of airstrikes. We find that increasing the average number of airstrikes from 1 to 6 per day for seven consecutive days increases all types of insurgent violence.


page 18

page 22

page 25

page 31


Causal Inference for Spatial Treatments

I propose a framework, estimators, and inference procedures for the anal...

Causal Estimation with Functional Confounders

Causal inference relies on two fundamental assumptions: ignorability and...

Identifying Causal Effects in Experiments with Social Interactions and Non-compliance

This paper shows how to use a randomized saturation experimental design ...

Causal Inference With Outcome-Dependent Missingness And Self-Censoring

We consider missingness in the context of causal inference when the outc...

Causal inference with recurrent and competing events

Many research questions concern treatment effects on outcomes that can r...

Policy Evaluation for Temporal and/or Spatial Dependent Experiments in Ride-sourcing Platforms

Policy evaluation based on A/B testing has attracted considerable intere...

Spatio-temporal quasi-experimental methods for rare disease outcomes: The impact of reformulated gasoline on childhood hematologic cancer

Although some pollutants emitted in vehicle exhaust, such as benzene, ar...

Please sign up or login with your details

Forgot password? Click here to reset