6 citations · 9 across the 9 of their papers we have counts for
9 papers
When is statistical evidence strong enough? Using hypothesis tests to value data collection
Aristotelis Epanomeritakis, Davide Viviano
Policy decisions often hinge on conventional p-value thresholds, which ignore economic costs and benefits of further data collection. This paper recasts statistical significance as…
Estimating Social Norm Complementarities
Eliana La Ferrara, Cheaheon Lim, Davide Viviano
We develop a model of choice over social norms that allows for complementarities along two dimensions: \textit{technological}, analogous to complementarities between consumption go…
Learning What to Learn: Experimental Design when Combining Experimental with Observational Evidence
Aristotelis Epanomeritakis, Davide Viviano
Experiments deliver credible treatment-effect estimates but, because they are costly, are often restricted to specific sites, small populations, or particular mechanisms. A common…
Triply Robust Panel Estimators
Susan Athey, Guido Imbens, Zhaonan Qu +1
This paper studies estimation of causal effects in a panel data setting. We introduce a new estimator, the Triply RObust Panel (TROP) estimator, that combines (i) a flexible model…
Publication Design with Incentives in Mind
Ravi Jagadeesan, Davide Viviano
The publication process both determines which research receives the most attention, and influences the supply of research through its impact on researchers' private incentives. We…
Evidence aggregation with ignorance in mind: learning what we do (not) know for archetypes discovery
Emily Breza, Arun G. Chandrasekhar, Davide Viviano
When evaluating policy interventions, researchers often pursue two related goals: identifying which individuals or contexts benefit most, and determining whether patterns of treatm…
Program Evaluation with Remotely Sensed Outcomes
Ashesh Rambachan, Rahul Singh, Davide Viviano
We study causal inference in experiments and quasi-experiments, where the economic outcome is imperfectly measured by a remotely sensed variable. The remotely sensed variable is lo…
Identification and Inference for Synthetic Controls with Confounding
Guido W. Imbens, Davide Viviano
This paper studies inference on treatment effects in panel data settings with unobserved confounding. We model outcome variables through a factor model with random factors and load…
Causal clustering: design of cluster experiments under network interference
Davide Viviano, Lihua Lei, Guido Imbens +3
This paper studies the design of cluster experiments to estimate the global treatment effect in the presence of network spillovers. We provide a framework to choose the clustering…