AEA RCT Registry currently lists 12261 studies with locations in 170 countries.
In this study we aim to estimate the consumer demand curve for off-net (“interoperable”) payments, by randomizing the price that consumers face for off-net payments, within an FSP's digital payments apps, with users of the Philippines' instant retail payment switch, InstaPay. An experimentally-generated estimate of demand would be informative for a number of purposes, including for FSPs’ own pricing decisions, and for pricing regulation decisions by policymakers. The demand curve can also be inverted to generate an aggregate estimate of consumer welfare from access to off-net payments, identified with experimental variation in a real-stakes, field setting. We will also study spillovers of instant payments usage on other financial inclusion behaviors, including other payments channels, a...
Youth-employment and entrepreneurship programs in low- and middle-income countries (LMICs) routinely deliver programs, including grants and credit, through groups (self-formed or program-assigned). What such grouping creates economies of scale, such grouping and joint ventures can be prone to free-riding while entailing significant coordination costs. The size of this hidden “tax”, what we call the cost of grouping, is currently unknown, as is the cost of assignment (the additional welfare loss when the program, rather than the recipient, picks the partners). This study uses an incentivized double-bounded dichotomous-choice (DBDC) experiment to estimate three demand curves, individual, self-formed group, and program-assigned group, in the same currency as the transfer itself (Ethiopian ...
We conduct an online experiment on Prolific to measure the willingness-to-pay to discriminate against female coworkers, using the price-of-prejudice paradigm of Hedegaard and Tyran (2018). We add a treatment of hidden productivity to highlight the differences between taste-based and statistical discrimination. This document pre-registers the hypotheses, estimation strategy, and power analysis.
This pilot project explores the impact of early exposure to AI-powered learning tools and teacher training on students’ educational outcomes in Ethiopia. Focused on underserved and low-resource settings, the study employs a randomized controlled trial to assess improvements in student engagement, digital readiness, interest in STEM pathways, and teacher retention. Insights from this work will inform the design of a larger randomized evaluation to assess the long-term impacts of AI integration in education, guiding future policies for enhancing digital literacy and educational quality in East Africa.
We survey firms in New Zealand to examine their online and offline pricing strategies. To complement the survey data, we pair web-scraped prices with synchronized, in-store price observations for identical products. Finally, using a randomized controlled trial (RCT), we administer information treatments regarding the inflation outlook to analyze how new macroeconomic information impacts both firm expectations and their subsequent digital and physical pricing decisions.
We study whether different narratives about an NGO’s domestic violence initiative influence individual and collective decision-making. In a field experiment with 3,060 rural women in Kyrgyzstan and a complementary online experiment with 3,000 U.S.- based women, participants are randomly assigned to one of three video treatments. All videos present identical factual content about the NGO’s legal-aid and gendernorm programs but differ in their interpretation of the same evidence: the baseline video simply portrays factual evidence without drawing inferences; the optimism-based “easy-fix” narrative frames gender-norm change as a scalable solution based on crosscountry correlations (Eliaz and Spiegler, 2020); the data-driven “overfitting” narrative suggests historical program effec...
This randomized control trial evaluates the impact of peer-to-peer tutoring in French and Mathematics on academic and non-academic outcomes of students in French primary schools. The intervention consists of two six-week implementation periods, with three 25-to-30-minute sessions per week per subject, and will be conducted during the 2025-2026 school year. Primary and secondary outcomes include students’ academic achievement, socio-emotional skills, as well as classroom climate and friendship networks. The evaluation relies on national assessment results, standardized tests administered at baseline (pre-intervention) and at endline (post-intervention), administrative records, student and teacher surveys, and program monitoring data. The study is designed to assess whether participat...
This project evaluates a smart thermostat program designed to help reduce electricity demand during periods of high system stress. Participating households will be enrolled in a thermostat program that can automatically adjust thermostat settings during occasional peak-demand events. Households will always have the option to override or opt out of these adjustments. Participants will be randomly assigned to different program conditions, allowing the research team to compare how households respond to alternative program designs. The study will use information generated by participating thermostats, including thermostat operation, temperature settings, and whether households choose to opt out of an event. These data will be used to evaluate how program design influences electricity ...
This laboratory experiment investigates the strategic interactions between a digital platform and consumers, testing the theoretical boundaries of data-driven price discrimination and consumer data manipulation. In a controlled laboratory setting, we implement a game between consumers and the platform. Consumers (played by subjects) are assigned types and choose their platform usage levels (denoted by action T and action M), which generates behavioral data. Simultaneously, the platform decides on its unobservable data-processing investment(i), which determines the probability of successfully decoding usage data for personalized pricing. If data processing succeeds, the platform offers a personalized price to the consumer; otherwise, an anonymous uniform price is charged based on the p...
This document outlines the analysis plan for a cluster-randomized controlled trial of an AI tool to assist prosecutors pursuing labor trafficking cases in Brazil, a tool complementing and working with an AI-native decision support tool Bússola I.A.. The experiment will test whether federal labor prosecutors using the tool to identify the most promising cases, compile supporting documentation,and prepare prosecutions faster yields improved prosecution outcomes. This pre-analysis plan provides intervention details, methodology, and a plan for analyzing the results of the experiment.