Working Papers

• Viviano, Davide and Jess Rudder. Policy design in experiments with unknown interference (October, 2023, Job Market Paper )
  Draft | Supplement | Slides | [arXiv] | Video | Field implementation (AEA Registry)
  We propose an experimental design for inference on and estimation of policies under network interference.
  (new: follow-up data collection in an implementation reaching over 400,000 participants.)
  
• Imbens, Guido, Davide Viviano. Identification and Inference for Synthetic Controls with Confounding (December, 2023)
  [arXiv]
  We formalize the properties of Synthetic Control estimators with unobserved confounders.
  
• Viviano, Davide, Lihua Lei, Guido Imbens, Brian Karrer, Okke Schrijvers, Liang Shi. Causal Clustering: design of cluster experiments under network interference (January, 2024), submitted
  Draft | [arXiv] | Slides
  We study when and how researchers should design clusters in experiments with network spillovers (with an application to the universe of Facebook users).
  
• Viviano, Davide and Jelena Bradic. Dynamic covariate balancing: estimating treatment effects over time with potential local projections (January, 2024). 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, Kaspar Wüthrich and Paul Niehaus. When should you adjust inferences for multiple hypothesis testing? (December, 2023)
  [arXiv]
  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. 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.

Accepted or Published Papers

• Viviano, Davide. Policy Targeting under Network Interference, Accepted at Review of Economic Studies (2024)
  Accepted version | Supplement | Slides | Replication code | Notes | [arXiv]
  I design and study how to choose whom to treat in the presence of spillovers using data from existing experiments or observational studies.
  R package (developed with Jake Carlson)
  
• Viviano, Davide and Jelena Bradic. Fair Policy Targeting. Journal of the American Statistical Association (2023)
  Published version | [arXiv] | Supplement | Replication code
  We propose and study treatment allocation rules that 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)
  Published version | [arXiv] | Supplement | Replication code
  We study estimation and inference with machine-learning estimators in the context of synthetic controls.