treatments are conditionally randomly assigned and the controls are sufficiently flexible to avoid omitted variables bias … treatments. Thus, recent concerns about heterogeneity-induced bias in regressions leveraging potential outcome restrictions (e … contamination bias and propose a new class of efficient estimators of weighted average effects that avoid bias. In a re-analysis of …

In this paper we show that omitted variables and publication bias lead to severely biased estimates of the value of a …

-in-the-field experiments with over 2,000 individuals in Abidjan, Ivory Coast. We show that: (1) individuals judged to be of a lower rank are …

that matters? Using a large-scale experiment we decompose the relative importance of partisan messages vs leader sources …

assisted by AI predictions could outperform both human-alone or AI-alone. We conduct an experiment with professional …

effects of fake reviews on individual demand and welfare. We conduct an incentive-compatible online experiment with a …

improving the elicitation wording, coding experiments, and producing documentation. Second, we discuss the implementation of … experiments using LLMs, focusing on enhancing causal inference by creating consistent experiences, improving comprehension of …