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Found 9 papers, 0 papers with code
Identification and Inference for Synthetic Controls with Confounding
We conclude with a comparison of Synthetic Control estimators with alternatives for factor models.
Causal clustering: design of cluster experiments under network interference
This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of network spillovers.
A model of multiple hypothesis testing
Multiple hypothesis testing practices vary widely, without consensus on which are appropriate when.
Dynamic covariate balancing: estimating treatment effects over time with potential local projections
We propose a method that allows for (i) treatments to be assigned dynamically over time based on high-dimensional covariates, past outcomes and treatments; (ii) outcomes and time-varying covariates to depend on treatment trajectories; (iii) heterogeneity of treatment effects.
Policy design in experiments with unknown interference
This paper studies experimental designs for estimation and inference on policies with spillover effects.
Fair Policy Targeting
One of the major concerns of targeting interventions on individuals in social welfare programs is discrimination: individualized treatments may induce disparities across sensitive attributes such as age, gender, or race.
Experimental Design under Network Interference
This paper studies the design of two-wave experiments in the presence of spillover effects when the researcher aims to conduct precise inference on treatment effects.
Policy Targeting under Network Interference
This paper discusses the problem of estimating treatment allocation rules under network interference.
Synthetic learner: model-free inference on treatments over time
Understanding the effect of a particular treatment or a policy pertains to many areas of interest, ranging from political economics, marketing to healthcare.
