Grants Database

The Foundation awards approximately 200 grants per year (excluding the Sloan Research Fellowships), totaling roughly $80 million dollars in annual commitments in support of research and education in science, technology, engineering, mathematics, and economics. This database contains grants for currently operating programs going back to 2008. For grants from prior years and for now-completed programs, see the annual reports section of this website.

Grants Database

Grantee
Amount
City
Year
  • grantee: University of California, Riverside
    amount: $19,990
    city: Riverside, CA
    year: 2016

    To support a conference on causal inference methodologies both in computer science and in the social sciences

    • Program Economics
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Kevin Esterling

    To support a conference on causal inference methodologies both in computer science and in the social sciences

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  • grantee: University of Georgia Research Foundation, Inc.
    amount: $19,754
    city: Athens, GA
    year: 2016

    To test how behavioral factors can predict insurance choices

    • Program Economics
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Marc Ragin

    To test how behavioral factors can predict insurance choices

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  • grantee: Brandeis University
    amount: $45,500
    city: Waltham, MA
    year: 2016

    To support an international conference on heterogeneous agents and agent-based modeling in macroeconomics

    • Program Economics
    • Initiative Financial and Institutional Modeling in Macroeconomics (FIMM)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Blake LeBaron

    To support an international conference on heterogeneous agents and agent-based modeling in macroeconomics

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  • grantee: University College London
    amount: $20,000
    city: London, United Kingdom
    year: 2016

    To support Microeconomic Insights, an online source for accessible summaries of high quality microeconomic research

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Richard Blundell

    To support Microeconomic Insights, an online source for accessible summaries of high quality microeconomic research

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  • grantee: Third Way Foundation
    amount: $93,500
    city: Washington, DC
    year: 2016

    To develop, test, and calibrate models of how administrative data from online platforms relate to official employment statistics

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Michael Mandel

    To develop, test, and calibrate models of how administrative data from online platforms relate to official employment statistics

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  • grantee: University of California, Berkeley
    amount: $95,158
    city: Berkeley, CA
    year: 2016

    To develop, document, and freely distribute linked administrative data derived from federal tax and educational records

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Emmanuel Saez

    To develop, document, and freely distribute linked administrative data derived from federal tax and educational records

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  • grantee: Harvard University
    amount: $326,688
    city: Cambridge, MA
    year: 2016

    To develop behaviorally informed versions of basic macroeconomic models

    • Program Economics
    • Initiative Behavioral and Regulatory Effects on Decision-making (BRED)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Xavier Gabaix

    This grant funds the work of theoretical macroeconomist Xavier Gabaix, who is endeavoring to explain puzzling macroeconomic phenomena by importing into macroeconomic models insights gleaned from behavioral psychology. Contrary to the prevailing wisdom among macroeconomists, Gabaix’s work assumes human beings have limited attentional resources and must make choices about what to pay attention to and what to ignore. When attention is scarce, Gabaix argues, the pressing concerns of today crowd out consideration of distant tomorrows. This much microeconomists have known for some time. Gabaix’s contribution has been to show how this scarcity of attention and the consequent focus on the now can, in the aggregate, have predictable macroeconomic effects. Indeed, in early work Gabaix has used these assumptions to predict certain stubborn macroeconomic facts—like the absence of inflation in the U.S. despite years of low interest rates—that have vexed more traditional economic models. Funds from this grant provide three years of support to Gabaix to expand and continue this work. Supported activities include the testing and calibrating of Gabaix’s models against real-world data and the writing of a textbook that uses his framework to explain standard, well-understood macroeconomic phenomena.

    To develop behaviorally informed versions of basic macroeconomic models

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  • grantee: Urban Institute
    amount: $263,000
    city: Washington, DC
    year: 2016

    To develop, document, and make freely available both linked mortgage datasets, as well as new tools for analyzing large collections of administrative data

    • Program Economics
    • Initiative Economic Analysis of Science and Technology (EAST)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Alanna McCargo

    This grant funds a project led by Alanna McCargo and Laurie Goodman at the Urban Institute’s Housing Finance Policy Center, to create a relational research database that links mortgage data made available through the Home Mortgage Disclosure Act with geographic and other data from the Census Bureau’s American Community Survey (ACS). The resulting dataset promises to provide economists and other researchers with a powerful new resource for investigating questions related to loan markets, geographic variations in housing prices, and consumer demand for credit. The Urban Institute team will design and implement a distributed, cloud-based architecture to house the database, and provide online computational access to the data through the Institute’s Spark Social Science computational platform. The team will also create and disseminate public guidelines and best practices for solving common problems with distributed, cloud-based data storage and the analysis of massive datasets.     In addition to the value of the dataset itself to researchers, the project will bolster the Urban Institute’s institutional expertise in addressing legal, security, privacy, and data acquisition and management issues related to large administrative datasets.

    To develop, document, and make freely available both linked mortgage datasets, as well as new tools for analyzing large collections of administrative data

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  • grantee: National Academy of Sciences
    amount: $301,470
    city: Washington, DC
    year: 2016

    To conduct an independent management study of processes, portfolios, and programs at the National Academy of Sciences

    • Program Economics
    • Initiative Economic Analysis of Science and Technology (EAST)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Marcia McNutt

    The National Academy of Sciences (NAS) was chartered by Abraham Lincoln “to give advice to the nation.” And, man, does it ever. Commissioned studies released during the first few days of September 2016 alone, for example, cover everything from clean electric power options to molybdenum-99 production, from eye health to eldercare. Funders and clients alike know the Academy’s work to be prestigious, authoritative, and impartial, but slow, inefficient, and expensive. Internal studies of NAS operations conducted sporadically over the years have resulted in only modest modifications. Now the incoming president, Marcia McNutt, wants to do more than that. A former editor of Science magazine and the first woman ever elected to lead the Academies, she is committed to comprehensive reform of how the NAS functions. Her first step is commissioning an outside management study by a distinguished but independent panel. The National Academy of Public Administration has agreed to carry out the project. Funds from this grant provide partial support for this independent management study.

    To conduct an independent management study of processes, portfolios, and programs at the National Academy of Sciences

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  • grantee: Stanford University
    amount: $1,807,297
    city: Stanford, CA
    year: 2016

    To develop services that model how access to administrative data can facilitate reliable, reproducible, and groundbreaking research in economics

    • Program Economics
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Mark Cullen

    Empirical economists tell tales of woe about the difficulties of accessing, processing, linking, and analyzing administrative data. Many have tried to address such impediments independently in the course of this or that research project. A piecemeal approach, however, is less effective than what might be accomplished by working together. This grant supports a project by a team of empirical economists and technologists at Stanford University to build and staff a new Stanford Data Core that will reduce social scientists’ struggles, and enhance their triumphs, with administrative data. Led by principal investigator Mark Cullen, the team has already gained access to over 230 administrative datasets, more than 100 server racks, and petabytes of data storage. The team will begin by harmonizing, documenting, cleaning, and adding to these datasets and then moving computations on them to the cloud in collaboration with Google. After the data have been pulled together, the team will test this new computational environment through the launch of four pilot research projects covering topics in economics from economic opportunity to contract labor markets. Though interesting in themselves, the projects will primarily serve as useful test cases to measure the functioning of the new computational environment. Finally, the project team is particularly keen on finding, sharing, and standardizing solutions to the legal challenges that encumber research on administrative data. Working with university lawyers at Stanford, the team will model what routine nondisclosure and data use agreements can and should look like. They will then promote this resource and these contracts to the wider scientific community.

    To develop services that model how access to administrative data can facilitate reliable, reproducible, and groundbreaking research in economics

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