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, Berkeley
    amount: $124,966
    city: Berkeley, CA
    year: 2018

    To create a publicly accessible panel dataset of residential electric utility rates for all United States utilities to develop more refined electricity cost models

    • Program Energy and Environment
    • Investigator Severin Borenstein

    To create a publicly accessible panel dataset of residential electric utility rates for all United States utilities to develop more refined electricity cost models

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  • grantee: University of Texas, Austin
    amount: $74,996
    city: Austin, TX
    year: 2018

    To support HOMEChem documentation as a basis for education and outreach activities

    • Program Science
    • Sub-program Chemistry of Indoor Environments
    • Investigator Lea Hildebrandt Ruiz

    To support HOMEChem documentation as a basis for education and outreach activities

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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: Code for Science and Society
    amount: $123,240
    city: Portland, OR
    year: 2018

    To support community engagement and beta testing of Stencila Sheets

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Nokome Bentley

    To support community engagement and beta testing of Stencila Sheets

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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: Massachusetts Institute of Technology
    amount: $1,043,399
    city: Cambridge, MA
    year: 2018

    To produce a comprehensive, multidisciplinary Future of Storage study that will consider the role key storage technologies might play in electricity systems over different time scales and service requirements

    • Program Energy and Environment
    • Investigator Robert Armstrong

    This grant provides partial support for a new report, The Future of Storage, which will bring together scientific, engineering, economic, and policy perspectives to describe the current state and future potential of technologies to store electricity and the differing roles these technologies might play in the evolving energy sector. Part of MIT’s well-regarded “Future of” series, the project will assemble a panel of top scholars from mechanical engineering, energy systems analysis, and economics to address a host of policy-relevant questions about electricity storage. Questions to be addressed by the study include what role storage might play in electricity systems over the near term (by 2030), midterm (by 2040), and long term (by 2050, and beyond); which storage technologies have the greatest potential for application over various time scales and service requirements; and what public policy, technology development, and market factors most influence the future of electricity storage. Grant funds will provide approximately one-third of the total study cost. 

    To produce a comprehensive, multidisciplinary Future of Storage study that will consider the role key storage technologies might play in electricity systems over different time scales and service requirements

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  • grantee: The University of Chicago
    amount: $605,281
    city: Chicago, IL
    year: 2018

    To support the training of early career scholars in developing a more detailed, granular approach to estimating damage functions that can contribute to providing more transparent estimates of the social cost of carbon

    • Program Energy and Environment
    • Investigator Michael Greenstone

    The social cost of carbon (SCC) is defined as the cost to society in dollars of releasing the equivalent of one ton of carbon dioxide into the atmosphere. The SCC is a key input measure to almost every legally required cost-benefit analysis of energy and environmental regulation. To properly quantify the SCC researchers need to improve the estimation of damage functions, the models that lay out how climate changes affect the economy. The Climate Impact Lab (CIL) at the University of Chicago, partnering with scientists at the University of California, Berkeley and Rutgers University, is developing the next generation of climate-economic damage functions. The new functions are orders of magnitude more advanced than existing integrated assessment models, providing a spatially detailed, granular set of damage functions for over 25,000 regions globally. Grant funds will support development of the CIL model, its computing infrastructure, and salary support for one postdoctoral and two predoctoral fellows participating in the project.

    To support the training of early career scholars in developing a more detailed, granular approach to estimating damage functions that can contribute to providing more transparent estimates of the social cost of carbon

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