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: Dartmouth College
    amount: $207,206
    city: Hanover, NH
    year: 2018

    To study, by running behavioral experiments, how consumers make decisions about insurance products like annuities

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Erzo Luttmer

    This grant funds work by behavioral economists Erzo Luttmer from Dartmouth and Dmitry Taubinsky from University of California, Berkeley, who are analyzing how behavioral biases might explain the annuity puzzle—the observation that annuities, as a financial product, are not nearly so popular as economic theory and people’s stated preferences would predict them to be. Of the many possible explanations for the annuity puzzle, behavioral biases are not easy to study. Consumers who avoid annuitization might have privileged information and unobserved motivations (like making bequests, for example), or they may be systematically affected by behavioral biases that result in suboptimal choices. Teasing out what accounts for what is not just difficult, but also important for devising potential remedies. Luttmer and Taubinsky have carefully designed a series of controlled experiments where real economic incentives are at stake, but where most other complications from the real world have been abstracted away, thus allowing them to isolate how subjects’ psychological attitudes toward time and risk affect decision-making. By identifying the role behavioral mechanisms play in such decisions, this research will generate new insights about the annuity puzzle in particular, and also about the behavioral welfare economics of risk taking, saving decisions, and insurance markets more generally.

    To study, by running behavioral experiments, how consumers make decisions about insurance products like annuities

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  • grantee: Decision Science Research Institute, Inc.
    amount: $622,549
    city: Eugene, OR
    year: 2018

    To conduct surveys, measurements, and behavioral experiments about public perceptions of risk using new methods and technologies

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Paul Slovic

    Behavioral economists assume that people make decisions based on the perceived probabilities of events. Behavioral experiments, interpretations, and the policies they inform should therefore depend on information about popular perceptions about likelihoods. This grant funds work by Paul Slovic of the University of Oregon and co-principal investigator Howard Kunreuther of the Wharton School to field surveys that will collect data on public perceptions of the probabilities for a host of important events, including nuclear war, chemical attack, opioid addiction, school shootings, as well as the mass adoption of driverless cars or e-cigarettes. Opinions about more than a hundred hazards will be elicited. In addition, Slovic and Kunreuther will conduct textual analyses based on the frequency that Google News describes a given hazard using words with high emotional valence. Last, the team will field a series of experiments designed to probe how people act on those perceptions and what can be done to help everyone make better estimates and better decisions.

    To conduct surveys, measurements, and behavioral experiments about public perceptions of risk using new methods and technologies

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  • grantee: Stanford University
    amount: $125,000
    city: Stanford, CA
    year: 2018

    To advance the design and implementation of causal inference techniques other than randomization in public policy evaluation

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Margaret Levi

    To advance the design and implementation of causal inference techniques other than randomization in public policy evaluation

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  • grantee: National Bureau of Economic Research, Inc.
    amount: $110,527
    city: Cambridge, MA
    year: 2018

    To produce papers, conferences, and a book on how administrative and other big datasets can enhance the calculation of official federal statistics

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

    To produce papers, conferences, and a book on how administrative and other big datasets can enhance the calculation of official federal statistics

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  • grantee: The University of Chicago
    amount: $399,974
    city: Chicago, IL
    year: 2018

    To study the complementarity between prediction algorithms and human decision-making

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Jens Ludwig

    On the one hand, more and more decisions are being made based on what machines can learn about us: who gets a loan, who gets into college, who gets insurance, etc. On the other hand, people have many reservations about the fairness of algorithms, about algorithmic perpetuation of biases built into historical data, about the mis- or overinterpretation of statistical correlations, and more. This grant funds work by economists Jens Ludwig from the University of Chicago and Sendhil Mullainathan from Harvard to study when, why, and how people should override recommendations based on artificial intelligence. The team will focus on how New York City judges decide to release or hold suspects before trial. Machine generated recommendations—ones that use facts about a suspect to predict whether that subject will commit a crime if released back into the community—are already in use. But judges are also privy to information about a subject that a typical algorithm is not, including a suspect’s courtroom dress, demeanor, accompanying associates, etc. Ludwig and Mullainathan will study whether and how these additional factors affect both judicial predictions of suspect behavior as well as AI predictions of judicial behavior.

    To study the complementarity between prediction algorithms and human decision-making

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  • grantee: National Bureau of Economic Research, Inc.
    amount: $914,250
    city: Cambridge, MA
    year: 2018

    To develop an active and diverse research community that studies the economics of artificial intelligence

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Avi Goldfarb

    This grant funds efforts by Avi Goldfarb, Joshua Gans, and Ajay Agrawal, three leading economists from the University of Toronto, and Catherine Tucker, Sloan Distinguished Professor of Management at MIT, to facilitate rigorous research on the economics of artificial intelligence (AI). Building on a successful conference on the economics of AI held in Toronto in 2017, the team plans to hold a series of three more annual conferences on related topics, commissioning papers for each conference, then publishing and disseminating the collected conference proceedings. Over three years, the team anticipates commissioning more than 50 academic papers. The team will also organize extensive training, support, and other services for graduate students and postdoctoral fellows interested in studying the economics of AI. The plan is to train more than 90 early-career researchers in advanced methodological and analytic techniques.

    To develop an active and diverse research community that studies the economics of artificial intelligence

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  • grantee: National Academy of Sciences
    amount: $241,190
    city: Washington, DC
    year: 2018

    To report on how social and behavioral insights can improve the reliability and reproducibility of scientific findings

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Barbara Wanchisen

    This grant provides partial support to the National Academy of Sciences for a consensus report on how to use insights from the behavioral, social, and statistical sciences to improve the reliability and reproducibility of research. The project will include five committee meetings featuring various experts across the sciences, five commissioned papers on reproducibility, an expert panel on behavioral economics and the professional incentives facing producers and consumers of research, and a final consensus report. While the majority of the funding will be provided by NSF, this grant will provide supplementary support both for including economic perspectives in the study and for disseminating the final report.  

    To report on how social and behavioral insights can improve the reliability and reproducibility of scientific findings

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  • grantee: Brookings Institution
    amount: $993,178
    city: Washington, DC
    year: 2018

    To organize, structure, and synthesize research on the measurement of productivity

    • Program Economics
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Louise Sheiner

    Between 1947 and 1973, U.S. productivity grew an average of nearly 3 percent per year. Since 2007, that rate has dropped to 1.3 percent. Since 2010, it has plummeted to 0.5 percent. China and India excepted, other countries around the world have experienced similar drops in productivity growth. Why? What is going on? This grant funds a project by a team led by Louise Sheiner at the Hutchins Center on Fiscal and Monetary Policy at the Brookings Institution to shed light on this “productivity puzzle.” Over the next two years, Brookings will conduct and commission original and rigorous research on productivity, engage with stakeholders at U.S. statistical agencies about the quality and limitations of existing productivity measurements, produce 10 to 12 peer reviewed papers, hold six conferences on this and related issues, produce a conference volume, and disseminate recommendations on how to improve research and statistics about economic productivity.

    To organize, structure, and synthesize research on the measurement of productivity

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  • grantee: National Bureau of Economic Research, Inc.
    amount: $241,690
    city: Cambridge, MA
    year: 2018

    To build a research community on the economics of science by holding regular conferences and by other community-building activities

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

    This grant supports the launch and operation of a new working group at the National Bureau of Economic Research (NBER) dedicated to studying the “economics of science.” Led by Paula Stephan, the group will bring together top flight economists to share existing work and findings, identify new areas for research, examine methodological and data issues, and commission new research. Topics include incentives in the current system, how the structure of grants and review systems affects scientific risk taking, the costs and efficiencies of different research funding models, how to judge scientific quality, and how to measure return on investment in basic and applied science. Along with four meetings of the working group, the grant will fund administrative and planning costs, support for small research grants, and partnerships between the working group and institutions like research universities or other science funders.

    To build a research community on the economics of science by holding regular conferences and by other community-building activities

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  • grantee: Duke University
    amount: $385,631
    city: Durham, NC
    year: 2018

    To launch an international summer school on Computational Social Science

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

    This grant supports the expansion of a popular seminar on computational social science, run by Matthew Salganik of Princeton University and Christopher Bail of Duke University. The instructional program, which takes place over the summer, involves lectures, group problem sets, and participant-led research projects. The seminar also includes outside speakers who conduct computational social science research in academia, industry, and government. Topics covered include text as data, website scraping, digital field experiments, nonprobability sampling, mass collaboration, and ethics. Interest in the program has been robust, with more than 10 times as many applicants as available slots each year. Sloan funds will allow lectures and course content to be broadcast via interactive video to six new satellite locations, including City University of New York; Northwestern; University of Colorado, Boulder; Seattle; Helsinki; and Cape Town. Additional satellite sites may be added in future years.

    To launch an international summer school on Computational Social Science

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