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: National Bureau of Economic Research, Inc.
    amount: $289,788
    city: Cambridge, MA
    year: 2021

    To facilitate, promote, and diversify scholarly research about the economics of artificial intelligence

    • Program Research
    • Initiative Economic Analysis of Science and Technology (EAST)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Avi Goldfarb

    This grant supports Ajay Agrawal, Avi Goldfarb, Joshua Gans, and Catherine Tucker, who are coordinating a conference on the economics of artificial intelligence at the Rotman School of Management, University of Toronto. Five years since its successful launch in 2017, the fall 2022 instalment of the conference will focus on specific applications of AI—particularly in the realms of national security, infrastructure, and health. The conference will, therefore, seek to connect the community of economics of AI scholars with scholars from these disciplines. AI applications like those in health economics, for example, precipitate questions about privacy, ethics, venture capital, and regulatory issues. In addition to activities relating to the conference, the organizers are also planning to join efforts with the Sloan-supported Working Group on the Economics of Digitization at the National Bureau of Economic Research.

    To facilitate, promote, and diversify scholarly research about the economics of artificial intelligence

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  • grantee: Boston University
    amount: $405,180
    city: Boston, MA
    year: 2021

    To study the conduct and consequences of labor markets where established platforms compete with start-up firms for STEM workers

    • Program Research
    • Initiative Economic Analysis of Science and Technology (EAST)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator James Bessen

    Economists justify government intervention in a market when, left to their own devices, economic agents produce an inefficient outcome—a “market failure”. Perhaps the most well-known example is the excessive accumulation of market power by large firms, which at the extreme can create a monopoly. Market power allows large companies to tilt the playing field in their favor, impose significant barriers to market entry, and ultimately squash competition. There’s also a less well-known mechanism through which large companies can stifle competition and innovation—by scooping up all the workers. There is reason to believe that in the tech industry, small companies are being systematically outbid by large companies in the market for talent. In a theoretically efficient market, workers receive compensation commensurate with their productivity. In an inefficient market, however, large firms can afford to hire talent at outsized salaries—even to perform tasks that do not put them to their best use. This is not just a problem for the small, innovative startups that compete with large tech firms. It is also a problem for the economy and wider society, since startups play a key role in commercializing scientific and technological advances which, in turn, benefit lives and produce economic growth. This grant supports James Bessen at Boston University, who is studying the conduct and consequences of labor markets where established platforms compete with startup firms for STEM workers. Bessen’s team will explore how competition for employees from large companies affects the growth, financing, and performance of startups, and the implications for policymaking. Their research will pay particular attention to the impacts on those startups whose founders are women or persons from marginalized groups. The project’s empirical approach will combine three datasets: Burning Glass data, which covers job openings; Crunchbase, a large database of corporations which contains information on firm founding and financing amounts; and Compustat, which provides extensive financial data on publicly listed firms. In addition to their own analyses, the team will make their code publicly available, creating a valuable public good for other researchers.

    To study the conduct and consequences of labor markets where established platforms compete with start-up firms for STEM workers

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  • grantee: Harvard University
    amount: $50,000
    city: Cambridge, MA
    year: 2021

    To support the print publication of the Harvard Data Science Review’s special issue on implications of differential privacy for the U.S. Census

    • Program Research
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Xiao-Li Meng

    To support the print publication of the Harvard Data Science Review’s special issue on implications of differential privacy for the U.S. Census

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  • grantee: Association for Computing Machinery
    amount: $20,000
    city: New York, NY
    year: 2021

    To support an inclusive conference on how computational tools, together with economic approaches, can address equity, access, and other urgent societal challenges

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Rediet Abebe

    This grant supports computer scientist Rediet Abebe at the University of California, Berkeley and economist Maximilian Kasy at the University of Oxford, who are organizing the Association for Computing Machinery’s inaugural conference focused on Equity and Access in Algorithms, Mechanisms, and Optimization—EAAMO 2021. The virtual conference will convene experts from academia, government, and industry working on the computational tools and relevant economic or social science research required to address urgent societal problems. EAAMO 2021 seeks to foster community-bridging collaborations for addressing issues such as access to education and healthcare, interventions for alleviating poverty, as well as policies to promote fairness and privacy in labor markets.

    To support an inclusive conference on how computational tools, together with economic approaches, can address equity, access, and other urgent societal challenges

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  • grantee: University College London
    amount: $20,000
    city: London, United Kingdom, United Kingdom
    year: 2021

    To support and expand the operations of Microeconomic Insights, an online source for summaries of top microeconomics research targeting policy audiences

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Ariel Pakes

    To support and expand the operations of Microeconomic Insights, an online source for summaries of top microeconomics research targeting policy audiences

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  • grantee: Tufts University
    amount: $200,000
    city: Medford, MA
    year: 2021

    To support the operations and expansion of EconoFact, an online source that disseminates policy-relevant economics research

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Michael Klein

    EconoFact (https://econofact.org) is a website that specializes in disseminating non-partisan and rigorous analysis from leading economists. Their work is edited in the form of short memos and podcasts that are accessible and digestible to a broad audience. Michael Klein, the leader of this effort, has assembled a network of more than 100 prominent economists who regularly contribute to EconoFact. Topics covered include employment, the costs of pollution, debts and deficits, household finance, and Medicaid reform, among others. Since its 2018 launch, the site has garnered almost 1.9 million pageviews and its work has been mentioned in major news outlets, including the PBS Newshour, the New Yorker, the Washington Post, The New York Times, The Financial Times, and NPR’s “All Things Considered”. By 2020, EconoFact had become an important source for analysis of the economic impacts of the COVID-19 pandemic, publishing more than 50 memos and 18 podcasts on the topic. Funds from this grant provide support for the continued operation and expansion of EconoFact, including the production of 150 new memos, 100 podcasts, and 36 video pieces, providing accessible, expert economic analysis on topics relevant to policymakers and the public alike.

    To support the operations and expansion of EconoFact, an online source that disseminates policy-relevant economics research

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  • grantee: National Bureau of Economic Research, Inc.
    amount: $207,702
    city: Cambridge, MA
    year: 2021

    To support the growth of research on behavioral public economics through training for early-career scholars

    • Program Research
    • Initiative Behavioral and Regulatory Effects on Decision-making (BRED)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Douglas Bernheim

    Many policies, like cigarette and alcohol taxes, are partly motivated by concerns that people can fail to act in their own best interests. Behavioral public economics (BPE) is a field that seeks to apply insights from behavioral economics to understand and evaluate such policies—with the ultimate goal of creating better policies. Despite its potential for improving policies, and lives, BPE remains a relatively niche and undersubscribed field at universities. This grant supports a team of BPE scholars working to change that. Douglas Bernheim at Stanford University, together with Hunt Allcott at Harvard University and Dmitry Taubinsky at the University of California, Berkeley, are launching a bootcamp to help grow the BPE research community. Grant funds will allow the team to run biennial two-day bootcamps at the National Bureau of Economic Research’s offices, which will include training sessions, keynote lectures, and networking opportunities for early-career scholars. To ensure educational offerings reach the widest possible audience, the effort includes focused outreach to women and underrepresented groups as well as the online posting of recorded sessions, expanding access to those unable to participate in person.

    To support the growth of research on behavioral public economics through training for early-career scholars

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  • grantee: Massachusetts Institute of Technology
    amount: $244,562
    city: Cambridge, MA
    year: 2021

    To employ behavioral economics to study why people believe and share misinformation online

    • Program Research
    • Initiative Behavioral and Regulatory Effects on Decision-making (BRED)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Adam Berinsky

    To employ behavioral economics to study why people believe and share misinformation online

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  • grantee: Harvard College Open Data Project
    amount: $20,000
    city: Cambridge, MA
    year: 2021

    To develop and validate new methodology that enables the creation of synthetic micro datasets at highly granular levels

    • Program Research
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Ethan Lee

    To develop and validate new methodology that enables the creation of synthetic micro datasets at highly granular levels

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  • grantee: University of Maryland, College Park
    amount: $2,201,539
    city: College Park, MD
    year: 2021

    To produce, test, and scale infrastructure for re-engineering official economic statistics using administrative data from businesses

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

    Perhaps the most important economic statistic calculated by the government is the Consumer Price Index (CPI). The CPI is used as a guide for fiscal and monetary decision-making, as a deflator to compare times series data in constant dollars, and as an inflation-measure to adjust the purchasing power of federal benefits like Social Security. The basic methodology for calculating the CPI, however, has hardly changed since the statistic was first introduced over a century ago. First, using a series of voluntary surveys of businesses and consumers, the Bureau of Labor Statistics attempts to measure average monthly prices in 38 geographical areas for 211 broad consumption categories like men’s shirts. Second, the BLS estimates the proportion that each of these individual categories represents of a typical household’s spending on all 211 categories. The goal is to calculate how much a typical basket of goods and services would cost today, then compare that to the cost of the same basket at the end of some fixed period. Although this may sound straightforward, worrisome and worsening challenges arise from this methodology. First, the time required to collect responses to these surveys and aggregate data means that the CPI is not calculated for months after data is collected. Second, falling response rates to polls and surveys of all kinds means that the CPI calculation is increasingly reliant on an ever-smaller set of data, with consequent worries about accuracy. Third, the metadata collected by surveys about goods and services sold is often insufficient to gauge how much the price increase in, say, a mobile phone, reflects improvements in the phone’s quality or feature-set. Funds from this grant support a project called RESET, Re-Engineering Statistics Using Economic Transactions, led by economist John Haltiwanger (University of Maryland College Park), Matthew Shapiro (University of Michigan) and Ron Jarmin (U.S. Census Bureau). The RESET team has forged data partnerships with major online retailers and market data analysis firms to allow them access to real-time, highly granular information about the prices and features of retail products for sale online. The team proposes to use advanced machine learning techniques to solve the problems with current data collection methods. The RESET partnerships promise to be able to calculate the CPI more quickly, using more comprehensive data, and in a way that promises to give both regulators and researchers more ability to calculate how much of a price variation is due to systemic inflation and how much actually reflects changes in product quality.

    To produce, test, and scale infrastructure for re-engineering official economic statistics using administrative data from businesses

    More
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