Working Papers

• Viviano, Davide. Policy design in experiments with unknown interference (March, 2023, Job Market Paper ), submitted
  Draft | Supplement | Slides | [arXiv] | Video
  I propose an experimental design for inference on and estimation of policies under network interference.
  Field implementation (AEA Registry) : Bundling Weather Forecasts and Agronomic Advisory for Farmers in Pakistan (with J. Rudder and Precision Development)
  
• Viviano, Davide. Policy Targeting under Network Interference, Revise and resubmit (second round) at Review of Economic Studies (September, 2023)
  Draft | Supplement | Slides | Replication code | Notes | [arXiv]
  I design and study targeted treatments using data from existing experiments or observational studies in the presence of spillovers.
  
• Viviano, Davide, Kaspar Wüthrich and Paul Niehaus. (When) should you adjust inferences for multiple hypothesis testing? (April, 2023), submitted
  [arXiv] (alphabetical first author ordering)
  We propose an economic framework to explain when, how, and why multiple hypothesis testing adjustments should be done differently.
  (See also related comment on FDA advisory for handling multiple endpoints in clinical trials.)
  
• Viviano, Davide and Jelena Bradic. Dynamic covariate balancing: estimating treatment effects over time with potential local projections (July, 2023), submitted
  Draft | [arXiv] | Slides | Replication code | R-package
  We study inference on time-varying treatments with panel data in the presence of high-dimensional covariates and (unknown) dynamic selection into treatment.
  
• Viviano, Davide. Experimental Design under Network Interference (July, 2022)
  [arXiv] | Replication code
  I propose a statistical framework for two-stage experimental designs under interference, with a focus on precise inference on treatment and spillover effects.
• Viviano, Davide, Lihua Lei, Guido Imbens, Brian Karrer, Okke Schrijvers, Liang Shi. Causal Clustering: design of cluster experiments under network interference (draft coming soon)
  We study when and how researchers should design clusters in experiments with network spillovers.
• Imbens, Guido, Davide Viviano. Identification and Inference for Synthetic Controls with Confounding (draft coming soon)
  We study identification and inference in panel data settings with unobserved confounders.

Accepted or Published Papers

• Viviano, Davide and Jelena Bradic. Fair Policy Targeting. Journal of the American Statistical Association (2023)
  [arXiv] | Accepted version | Supplement | Replication code
  We propose and study treatment allocation rules which are fair and Pareto optimal for applications in welfare programs.
  
• Viviano, Davide and Jelena Bradic. Synthetic Learner: Model-free Inference on Treatments over Time. Journal of Econometrics (2023)
  [arXiv] | Accepted version | Supplement | Replication code
  We study estimation and inference with machine-learning estimators in the context of synthetic controls.