AEA RCT Registry currently lists 12198 studies with locations in 170 countries.
I administer an online survey to approximately three to four thousand parents of parents to measure perceptions of college financial aid, along with a few embedded treatments. The measured perceptions of college aid will inform one paper that measures the welfare cost of misperception of marginal aid phaseout rates. The embedded treatments - which include an information treatment, explainer treatment, savings variation, labor supply framing, and question ordering - may be analyzed in separate future papers.
Rice cultivation serves as a crucial source of livelihood and food security for rural populations. However, traditional farming methods often face significant operational and environmental challenges, including high water consumption and the intense labor required for manual paddy transplanting. Rising agricultural wages, water scarcity, and climate volatility contribute to higher production costs, making traditional cultivation increasingly expensive and less profitable for smallholder farmers. This research aims to address these challenges by proposing a cluster randomized controlled trial that provides technical training on Direct Seeded Rice (DSR) technology along with climate-resilient rice variety. This approach enables farmers to substitute technology for manual labor, reducing t...
This study examines how organizational management styles and artificial intelligence (AI) framing influence the decision-making behavior of street-level bureaucrats in citizen-facing contexts. Using an online survey experiment, participants will be randomly assigned to scenarios that manipulate management style (e.g., bureaucratic, innovative, and participatory) and AI system value framing. Participants will then respond to hypothetical situations and be asked to answer post-vignette survey questions, allowing researchers to assess how these factors shape their behavioral orientations and reliance on AI-assisted recommendations in a decision-making process. This research project involves three research questions: 1) how does organizational management style interacted with role percepti...
This project concerns the evaluation of a mathematics intervention in multi-digit arithmetic. The intervention is rolled out as a Randomized Controlled Trial (RCT) in the fall 2026 in around 100 schools in Denmark with the purpose of improving adaptivity, flexibility, accuracy, and mathematics achievement.
We study how identity salience affects preferences. In an online survey with approximately 2,000 respondents, we randomly assign participants to watch one of two short videos before completing incentivised economic tasks. After the video, respondents complete three tasks.
Integration agreements between job seekers and public employment services define mutual obligations for labor market integration, including job search requirements, the support provided by the agency, and the conditions under which compliance is monitored and sanctioned. We study how reminding job seekers of different dimensions of these commitments affects their job search behavior, their knowledge of the rules they are subject to, and their labor market outcomes. The study is conducted in the context of the French Contrat d'Engagement (CE), a mandatory integration agreement signed by job seekers and caseworkers upon registration with the French public employment service, France Travail. The CE includes a personalized action plan specifying activities to support labor market integratio...
We experimentally test whether individuals' causal belief systems are well described by the workhorse model of the literature on causal cognition and misspecified mental models: Causal Bayesian Networks (CBN). We ask two questions. First, are belief systems rationalizable by the theory that individuals process data through the lens of a CBN or a distribution over CBNs? Second, do individuals' beliefs and choices exhibit the comparative statics predicted by the literature on misspecified learning? Participants interact with computer-generated systems involving binary variables, make incentivized choices, and report beliefs about causal relationships.
In many developing countries, traditional industries are declining rapidly amid broader economic growth and market change. Industries that rely on manual production methods and traditional skills transmitted across generations increasingly struggle to compete with mass-produced goods. This study examines whether identifying and better managing intangible commons—such as cultural heritage, shared identity, and collective values sustained through joint action among producers—can help both preserve and revitalize declining traditional industries. Specifically, we evaluate whether interventions that promote cultural-value-based marketing, encourage cooperation among producers, and connect producers with buyers/intermediaries who have expertise in designing products for broader markets impro...
Algorithmic content curation increasingly shapes the information that individuals observe in online environments. Existing concerns about such systems often emphasize echo chambers and reduced exposure to diverse viewpoints. However, information similarity may also affect strategic behavior: when individuals receive more similar information, they may better anticipate what others know and how others will act. Whether this facilitates or undermines collective action depends on the nature of the underlying coordination problem. This study examines how algorithm-driven information similarity affects collective action in a laboratory experiment. Participants make costly reporting decisions in a content-moderation game where successful removal of harmful content depends on collective part...
Governments and development agencies routinely conduct evaluations as part of their workflow. However, this knowledge may not feed back to future policymaking due to information overload. The rise of large language models (LLMs) and artificial intelligence provides a perfect solution to expedite policy learning. However, whether and how these AI agents facilities the use of evidence in policymaking remains untested. To address this question, we examine whether access to a generative AI platform powered by a domain-specific LLM improves the use of evidence in the policymaking process among government officials in Sri Lanka.