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: George Washington University
    amount: $50,000
    city: Washington, DC
    year: 2018

    To design, vet, and launch plans for federal agencies and private data holders to cooperate on improving federal economic statistics

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Andrew Reamer

    To design, vet, and launch plans for federal agencies and private data holders to cooperate on improving federal economic statistics

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  • grantee: University of Florida
    amount: $124,998
    city: Gainesville, FL
    year: 2018

    To pilot the acquisition, ingestion, and standardization processes necessary to compile a national voter registration database for use by academics and officials conducting non-partisan research

    • Program Research
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Michael McDonald

    To pilot the acquisition, ingestion, and standardization processes necessary to compile a national voter registration database for use by academics and officials conducting non-partisan research

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  • grantee: Fordham University
    amount: $7,500
    city: Bronx, NY
    year: 2018

    To support a global summit on anthropological contributions to research on business and economics

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Timothy Malefyt

    To support a global summit on anthropological contributions to research on business and economics

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  • grantee: University of California, Berkeley
    amount: $20,000
    city: Berkeley, CA
    year: 2018

    To support a workshop on improving the process and utility of eliciting expert forecasts of social science research results

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Stefano DellaVigna

    To support a workshop on improving the process and utility of eliciting expert forecasts of social science research results

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  • grantee: American Friends of Toulouse School of Economics
    amount: $300,000
    city: Salisbury, MD
    year: 2018

    To build out an open-source platform for reproducibly running large-scale behavioral experiments both online and in the laboratory

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Daniel Chen

    The suite of open source software tools known as “oTree” makes it simple to conduct behavioral experiments online or in laboratories. (The word “Tree” in the name refers to decision trees, and the prefix “o” stands for “open.”) Without the need for sophisticated programming, researchers can easily build and run games on oTree that test all kinds of hypotheses about human decision-making. This grant funds a project by Toulouse economics professor Daniel Chen to expand oTree’s capabilities. Planned improvements include handling large-scale experiments, supporting continuous-time games, integrating oTree with other open source tools, improving documentation, diversifying its users and funders, and enhancing its long-term sustainability.  

    To build out an open-source platform for reproducibly running large-scale behavioral experiments both online and in the laboratory

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  • grantee: California Institute of Technology
    amount: $308,614
    city: Pasadena, CA
    year: 2018

    To develop, test, and apply neuro-economic models of how decision-makers switch between habit-driven and goal-seeking behaviors

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Colin Camerer

    This grant supports a project by Caltech economist Colin Camerer to use insights from neuroscience to develop better predictions and explanations of consumer behavior. Camerer is developing, testing, and applying neuro-economic models of how people switch between behaviors that are habit-driven or routine on the one hand and behaviors that are goal-seeking and deliberative on the other—with particular focus on measuring the differences in price elasticities associated with one type of behavior vs. the other. Camerer will test the predictions of his model against a meta-analysis of previous results as well as in a field experiment using vending machines to measure economic variables, including price and quantity responses, and psychological variables, including response times and attention patterns.

    To develop, test, and apply neuro-economic models of how decision-makers switch between habit-driven and goal-seeking behaviors

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  • grantee: University of California, Berkeley
    amount: $287,500
    city: Berkeley, CA
    year: 2018

    To support a special semester on the foundations and applications of data privacy research

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Shafi Goldwasser

    The Simons Institute for the Theory of Computing at the University of California, Berkeley regularly devotes a semester to a given research topic, inviting interested researchers to make progress on the selected topic by either visiting regularly or taking up residence. This grant supports a semester at the Simons Institute devoted to advancing the theory and practice of data privacy. Funds will support visitors, events, and projects covering three themes: foundations of data privacy; interactions with other areas, such as statistics and geometry; and socio-technical aspects of data privacy—including modern privacy regulation, practical deployment challenges, and fairness, accountability, and transparency (FAT) issues. Program participants will include 23 senior visitors, 8 postdoctoral fellows, and over 20 graduate students. Expected outputs from this grant include a series of academic papers published by collaborating attendees and a white paper that describes findings and their implications for policy and practice.

    To support a special semester on the foundations and applications of data privacy research

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  • grantee: The Pennsylvania State University
    amount: $234,416
    city: University Park, PA
    year: 2018

    To strengthen the microfoundations of macroeconomics by building and calibrating behavioral models of order-book activity in financial markets

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator John Liechty

    An “order book” is a list of various traders’ buy or sell instructions for a given financial instrument.  A stock exchange uses such an order book to keep track of how many shares are being bid or offered at each potential price point.  That information, in turn, determines the actual price quoted by the exchange at any moment in time.  This grant funds work by John Liechty and Mark Flood to study the behavior of traders when they send messages to a financial exchange for inclusion in an order book. The researchers will model how trader behavior depends on available information and attentiveness, exploring how asymmetries in these qualities can have dramatic effects.  Liechty and Flood will also focus very specifically on whether detailed order-book data could help financial regulators predict or mitigate systemic market failures. 

    To strengthen the microfoundations of macroeconomics by building and calibrating behavioral models of order-book activity in financial markets

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  • grantee: ideas42
    amount: $189,873
    city: New York, NY
    year: 2018

    To field test how machine-learning algorithms compare with traditional techniques for estimating heterogeneous effects in behavioral experiments

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Josh Wright

    Funds from this grant support research by Josh Wright, working in concert with economists Sendhil Mullainathan of the University of Chicago and Susan Athey of Stanford, to test innovative new machine learning techniques in economics field experiments. The group intends to investigate whether machine learning can improve randomly controlled trials in two ways. First, can machine learning enhance the assignment of subjects to control and treatment groups in ways that can lower necessary sample size without sacrificing rigor? Second, can machine learning techniques expand our ability to identify and analyze heterogenous treatment effects? Wright and his team will deploy state-of-the-art machine learning techniques in a series of actual economic field experiments and then share their findings via conferences, talks, and papers.

    To field test how machine-learning algorithms compare with traditional techniques for estimating heterogeneous effects in behavioral experiments

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  • grantee: Social Science Research Council
    amount: $500,000
    city: New York, NY
    year: 2018

    To facilitate scholarly research on proprietary social media data through a process that incorporates peer reviews, ethical reviews, and privacy reviews

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Alondra Nelson

    To facilitate scholarly research on proprietary social media data through a process that incorporates peer reviews, ethical reviews, and privacy reviews

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