We use four incentivized representative surveys to study the endowment effect for lotteries in 4,000 U.S. adults. We replicate the standard finding of an endowment effect--the divergence between Willingness to Accept (WTA) and Willingness to Pay (WTP), but document three new findings. First, we...

Although fake online customer reviews have become prevalent on platforms such as Amazon, Google, and Facebook, little is known about how these reviews influence consumer behavior. This paper provides the first experimental estimates of the effects of fake reviews on individual demand and...

We investigate the potential for Large Language Models (LLMs) to enhance scientific practice within experimentation by identifying key areas, directions, and implications. First, we discuss how these models can improve experimental design, including improving the elicitation wording, coding...

Economics research has largely overlooked non-binary individuals. We aim to jump-start the literature by providing data on several economically-important beliefs and preferences. Among many results, non-binary individuals report more gender-based discrimination and express different career and...

How do political leaders affect constituents' beliefs? Is it rhetoric, leader identity, or the interaction of the two that matters? Using a large-scale experiment we decompose the relative importance of partisan messages vs leader sources, in the context of beliefs about immigration....

This paper provides novel insights into the science of scaling by examining an educational mentoring program in Mexico. Our analysis encompasses two separate field experiments, and takes advantage of a unique opportunity to learn from the government's implementation of the program on a large...

While Artificial Intelligence (AI) algorithms have achieved performance levels comparable to human experts on various predictive tasks, human experts can still access valuable contextual information not yet incorporated into AI predictions. Humans assisted by AI predictions could outperform both...

We study the interpretation of regressions with multiple treatments and flexible controls. Such regressions are often used to analyze stratified randomized control trials with multiple intervention arms, to estimate value-added (for, e.g., teachers) with observational data, and to leverage the...

Clinical trials following the "gold standard" of random assignment frequently use independent lotteries to allocate patients to treatment and control arms. However, independent assignment can generate treatment and control arms that are unbalanced (i.e. treatment and control populations with...

This study investigates how to use regression adjustment to reduce variance in experimental data. We show that the estimators recommended in the literature satisfy an orthogonality property with respect to the parameters of the adjustment. This observation greatly simplifies the derivation of...