Grants

Funding for Research Projects

2025 $49,050
J-PAL North America – Social Policy Research Initiative

Reducing Frictions in Access to ChildCare: A Pilot Evaluation of AI-Guided Family Support

Pilot evaluation testing AI-powered guidance to help families navigate complex childcare application processes. The project measures how personalized, technology-enabled support can reduce procedural barriers and connect families with high-quality early learning opportunities. Led by Christopher Neilson (Yale University) in collaboration with partner organizations, the study follows J-PAL's rigorous standards for randomized evaluations, transparency, and data sharing.

View Details ↗
2023 $73,489
Alfred P. Sloan Foundation

Alfred P. Sloan Research Fellowship

Sloan Research Fellowship prize with grant funds used to support the Childcare Deserts Project (LUCI initiative). The Sloan Research Fellowship is awarded to early-career scientists and scholars of outstanding promise who are making important contributions to their fields. The grant funds from this fellowship supported a pilot research project mapping and measuring access to early childhood care in Latin American cities. This work developed a scalable, city-level mapping system to identify gaps in childcare supply across Santiago (Chile), Bogotá (Colombia), and Santo Domingo (Dominican Republic), combining urban data science, administrative microdata, and geospatial analytics to create the first harmonized, cross-city map of childcare access in major Latin American capitals. This foundational research led to the creation of LUCI (Latin American Urban Childcare Initiative), a multi-country research and policy initiative working with governments to modernize childcare information systems, expand access, and reduce burdens on working families.

Related Projects:
Latin American Urban Childcare Initiative (LUCI)
Award #FG-2023-20963 View Details ↗
2019 $558,589
National Science Foundation (NSF)

Biased Beliefs and Search in Education Markets

This research will use experimental methods to study the reasons parents make school choices with very little information about options available to them. The research will study the relative importance of two mechanisms through which this occurs: (i) difficulty and cost of acquiring information about school characteristics, and/or (ii) families have incorrect beliefs about the distribution of schools, believing that all schools are the same. The research will develop a theoretical model based on parent's beliefs about school quality and how these beliefs change as they receive new information. The research will then test this theory by providing different amounts of information to parents to see how this affects their school choice decisions. The pilot study was conducted in 2017 and the first research paper is titled Search Costs, Biased Beliefs and School Choice under Endogenous Consideration Sets, coauthored with Adam Kapor, Claudia Allende, and Patrick Agte.

Related Projects:
A Decade of Centralized School Choice in Chile Heterogenous Beliefs, School Choice Systems and Mechanism Design Solutions
Related Papers:
Search and Biased Beliefs in Education Markets
Award #1919504 View Details ↗
2016 $457,853
National Science Foundation (NSF)

Beliefs, Understanding, and Strategic Behavior in School Choice Mechanisms

The project combines a household survey measuring the preferences, sophistication, and beliefs of potential school choice participants with administrative records of school choice and, academic outcomes to estimate a latent utility model of school choice participation. We will conduct this study in the context of the public school district in New Haven, Connecticut, which uses a centralized mechanism closely related to the "immediate acceptance" or "Boston" algorithm to administer school choice.

Related Projects:
Heterogenous Beliefs, School Choice Systems and Mechanism Design Solutions
Award #1629226 View Details ↗
2019 $85,000
Overdeck Princeton Education Fund

How the Design of School Choice Systems Affects Welfare and Student Outcomes

This project leverages a partnership between academic researchers and policymakers in the New Haven, Connecticut school district. It aims to design, implement, and evaluate the effects of innovations to the transparency and ease of use of the school choice system. The main goal will be to evaluate what innovations to school choice models are successful and to generate evidence so these models can be replicated elsewhere.

Related Projects:
Heterogenous Beliefs, School Choice Systems and Mechanism Design Solutions
2018 $500,000
Wellspring Philanthropic Fund

Incubation of Human Capital Technology Organization

Incubate the development of NGO ConsiliumBots and the research and development of AI technology to help people make better human capital investment decisions.

2017 $20,000
Microsoft Research

Leveraging Administrative Data and Machine Learning Techniques to Improve Education Policy in Developing Countries

This projects looks to take advantage of the extensive scalable computational resources provided by cloud computing to use large administrative datasets and machine learning techniques to help inform policies that will help reduce the amount of students that drop out of school in developing countries.

2015 $1,498,979
DIV-USAID

Learning the Value of Education in the Dominican Republic

Large scale impact evaluation implemented in conjunction with the government of the Dominican Republic (IDEICE) that looks to increase investment in human capital by reducing information frictions among adults and children regarding the cost, benefit, and feasibility of higher education levels. A panel of in-depth household surveys are conducted on a custom-designed application measure time use, parental investments, and labor supply decisions. Administrative data is used to evaluate the impact and survey data is used through the lens of a dynamic human capital accumulation model to study the mechanisms through which information on financial aid, returns to levels of education, and to the field of study can affect investment in human capital and labor supply.

Related Projects:
Information and Dynamic Human Capital Accumulation
Award #AID-0AA-F-14-00030
2015 $977,690
United States Department of Labor (DoL)

Getting Children to Stay in School and out of work: The role of Informative and Persuasive Marketing

Large scale impact evaluation to assess how the provision of this information affects drop-out rates and parents' and students' perceptions and decisions. A panel of in-depth household surveys are conducted on a custom-designed application measure time use, parental investments, and labor supply decisions. Administrative data is used to evaluate the impact and survey data is used through the lens of a dynamic human capital accumulation model to study the mechanisms through which information on financial aid and returns affects human capital investment decisions.

Award #IL-26701-14-75-K-9
2016 $202,000
Peruvian Government and International Bank for Reconstruction and Development (BIRF)

Evaluating online platform to reduce information asymmetries w/in students and parents

Studying the role of information asymmetries in higher education choice in the Peruvian market and how informative online platforms can help shift educational choices. Ministry of Education and Innovations for Poverty Action are leading the project.

Award #038-2016/BIRF 8212-PE
2016 $50,000
Post Primary Initiative JPAL Global

Education Mismatch and Information about Relative Performance

Large scale impact evaluation implemented in conjunction with the government of the Dominican Republic (Pruebas Nacionales and IDEICE) looks to inform students of high academic performance through letters that contain information and motivational messages. Its main goal is to reduce dropout rates in developing countries. Currently working partnered with the government in the Dominican Republic, Peru, and Chile. JPAL and the government of the Dominican Republic are the leaders of this project.

Award #5710004043
2018 $49,479
Skills for Youth Program, J-PAL LAC

Building a better future with informed investment in higher education: Evaluating the impact of personalized provision of information on earnings and financial aid in the Dominican Republic

In this study, we collaborate with the government of the Dominican Republic to construct an information system and deploy a state-of-the-art application that leverages innovations in artificial intelligence and machine learning to improve the quality of the personalization of information provision. Labor market earnings information, as well as detailed financial aid information and skills profiles by major, will be provided through an application used by social workers who visit students who participate in the national conditional cash transfer program PROSOLI. Using the custom application, social workers will help the prospective student navigate the complex higher education landscape with prompts from the app, making sure to discuss how financial aid works in their specific case and how it can change depending on what they choose to study and where.

2018 $256,893
Post Primary Education Initiative, J-PAL

Financial Aid and College Access in the Dominican Republic

In this project, we work together with the Ministry of Higher Education of the Dominican Republic to design and evaluate different aspects of their post-secondary financial aid policy. Guided by both theory and empirical evidence, we work with the government to design and implement several randomized control trials to evaluate different aspects of the financial aid policy, focusing on recruitment, selection, and retainment of talented but underprivileged students in post-secondary education. Estimates of these various margins will help inform the design of the final version of constrained-optimal financial aid policy.

2018 $48,990
Governance Initiative, J-PAL

Reducing free-riding in public goods: An experimental approach to improving payment compliance for trash collection in the Dominican Republic

This is a collaborative project with the City government of Santo Domingo to design and evaluate different interventions to improve payment compliance for public garbage collection. In a first stage, we will analyze data on payment histories, as well as undertake targeted interviews and focus groups to gain a deeper understanding of the determinants of payment compliance. In the second stage, we will design and implement several randomized control trials to evaluate different behavioral and non-behavioral approaches to reduce free-riding. The interventions considered are: 1) Simplification of communication and payment instructions; 2) A lottery for households with timely payments; 3) Informing households about the consequences on their credit history of not paying the bill; 4) Informing households about debt relief options; 5) Informing citizens about actual compliance rates in high compliance neighborhoods. This will shed light on how to improve a state's capacity to effectively collect payments for government services.