This work funds methodological work by economist Susan Athey, who is aiming to develop rigorous new statistical algorithms that will allow machine learning programs to isolate causal relationships in large, complex datasets. Athey is building special new tools to handle methodological tasks that economists care about but often find challenging. These include novel techniques for taking heterogeneity into account while estimating treatment effects, calculating optimal policies, and testing hypotheses in very large and varied populations. Athey’s focus will be on computing algorithms that are particularly useful for evaluating policy interventions and that enable one to isolate how policy changes differentially affect the behavior of heterogeneous populations. As a result of her work, she expects to publish several pieces in peer reviewed statistical and econometric journals and all the algorithms, code, documentation, and nonproprietary data Athey and her team generates will be made freely available to other researchers.

Though it has been ten years since the Great Recession, the comprehensive macroeconomic models in use at central banks, government agencies, and other large financial institutions are not noticeably improved from a decade ago. Conversations with leaders of those institutions point to two fundamental flaws in traditional models, namely, the assumptions about representative agents and about rational expectations. These imply not only that the economy evolves as if there is only one consumer and only one firm but also that the consumer and the firm make optimal decisions based on predictions that are realized. Why are macroeconomists so reluctant to give up these stultifying assumptions? Because as hard as it is to run models with those assumptions, it is nearly impossible to compute much without them. Chris Carroll of Johns Hopkins University wants to fix this situation. While serving as chief economist at the Consumer Financial Protection Bureau (CFPB), he started constructing an open source computational tool kit for macroeconomists that can specifically handle non-rational heterogeneous agents. The platform, the Heterogeneous Agents Resources Kit (HARK), is capable of modeling how microeconomic interactions among heterogeneous agents can lead to macroeconomic outcomes different from those predicted by traditional techniques. It is also possible to assign less-than-rational behaviors—such as hyperbolic discounting, anchoring, or herding—to parts of the population. Running simulations under those circumstances can reveal phenomena that traditional models can neither explain nor even generate. This grant provides three years of support to Carroll as he further expands and develops HARK and creates tools to facilitate its use.

This grant funds a project by Hunt Allcott, Dmitry Taubinsky, and Jonathan Zinman to four common kinds of consumer decisions and then use those models to analyze the welfare implications of potential policy interventions aimed at altering these decisions. They plan to examine supposed “mistakes” people make making decisions about sugar-sweetened beverages, credit card borrowing, checking account overdrafts, and college enrollment. In each context, the research team will start by formulating a theoretical model that can accommodate a range of consumer behaviors. Next, they will perform empirical analyses using experimental, quasi-experimental, and survey designs to identify biases and test predictions. Then they will analyze the empirical welfare implications various regulatory or other interventions aimed at altering consumer choices in these areas. In addition to covering data collection costs, grant funds will support a research assistants and a single project manager for all four studies.

While advances in information technology may be changing our lives, they are not necessarily translating into greater productivity or prosperity for the economy as a whole. Having peaked in the 1950s, productivity growth fell dramatically in the U.S. from 2004 to 2008. The last five years have seen some of the lowest levels since the U.S. began collecting such statistics. This grant funds a project by John Van Reenen of MIT and Nicholas Bloom of Stanford to study how R&D investment in the U.S. affects the productivity growth rate. In previous work, Van Reenen and Bloom have identified how organizational innovations affect worker productivity. This grant funds an extension of that work as the team tries to isolate the role research and development plays in productivity by studying what they call “Ideas-TFP.” From a macroeconomic view, the team will examine trends in Ideas-TFP across countries and regions. At the meso level, they will concentrate on a few key sectors, such as medical and agricultural innovation. Focusing further on individual firms, they will compile private and public data about R&D spending as well as patenting and new product introductions. Of particular concern to the team will be constructing measures of market “dynamism” that reflect the rates at which jobs and firms are created or destroyed. The datasets compiled and shared by this project will also help other recent grantees, since estimating the returns on R&D is one of the animating and abiding goals for the Sloan Foundation’s subprogram on the Economic Analysis of Science and Technology.

This grant funds a suite of three research projects by Heidi Williams of MIT to estimate the returns on R&D investments. All three projects deal with how private and public interests diverge and to what extent that divergence is mitigated or created by the patent system. The first study asks how much “stealing” from previous innovations may increase private returns without necessarily increasing social returns. Working with Daron Acemoglu (MIT), Williams will measure “citations stolen” from patents that served as “prior art” for a given innovation. Because advances do not always come about due to new knowledge per se, but rather due to marginal or technical improvements on existing technologies, “follow-on innovations” can earn more private returns than warranted by the new social value they create. Williams will compare citation data between successful and unsuccessful patent applications to help quantify the extent to which progress depends on substituting new ideas for old ones, rather than the generation of completely new or disruptive capabilities. For the second study, Williams and co-authors Pat Kline (University of California, Berkeley), Nevianna Petkova (U.S. Office of Tax Analysis), and Owen Zidar (University of Chicago Booth School of Business) will merge data on U.S. patent applications with IRS tax records to investigate which firms and which workers profit from a patent. By carrying out event studies, the team will specifically trace how spillovers accrue to private parties other than the original inventors. The third study, with Eric Budish (Chicago Booth) and Ben Roin (MIT Sloan School of Management), seeks evidence to support the common but unproven assumption that patents increase innovation. What happens, for example, when the patent for a basic ingredient expires, but a “new use” is found during the unprotected period? Preliminary findings indicate a drop-off in for-profit (but not publicly funded) research on a drug once a generic competitor can enter the market. Williams and her collaborators will estimate the social value of “missing” research investments that private interests are not undertaking now, but would if incentive systems were different.

The Conversation U.S. (TCUS) is an independent and nonprofit news outlet that producing popular articles by academics about their research. Articles on the site are written and titled by researchers themselves, edited in cooperation with skilled journalists, and then published under a Creative Commons CC-BY license, allowing other publications like The Atlantic, Washington Post, and New York Times to republish them to their own readers. Since its founding in 2014, some 3,400 scholars from 525 universities have written for TCUS. Including republished articles, the number of “reads” has grown to more than six million per month. Funds from this grant provide two years of support to the Business and Economics desk at TCUS, allowing the continued publication of articles on timely topics in economics and finance. In addition to defraying operational costs, grant funds will support the hiring of a researcher responsible for identifying top professors whose academic work is timely and compelling enough for TCUS to turn into popular, authoritative, and important news.

This grant provides four years of renewed support to a postdoctoral fellowship program run by the National Bureau of Economic Research which supports talented young researchers interested in working on the economics of an aging workforce. Fellows receive a one-year stipend to carry out research at NBER’s office in Cambridge, Massachusetts, as well as limited funds for research-related purposes. In addition, fellows have the opportunity to participate in NBER’s weekly lunch seminars, NBER’s Summer Institute workshops on Aging and Labor Studies, relevant activities related to the larger NIA-NBER fellows program on Aging, and collaborative research and networking activities with a similar postdoctoral fellowship program at the Harvard Center for Population and Development Studies. Selection of the three fellows per year will be made by a panel of experts who are members of both the Aging and Labor Studies NBER programs. Nicole Maestas of Harvard University will chair the selection committee, which will include leading scholars in the fields of labor economics and the economics of aging. The committee’s decisions will be based on their evaluation of the fellows’ potential to make an important contribution to the understanding of the behavior of older workers and the functioning of labor markets for these workers.

To make sound decisions about potential changes to Social Security, Medicare, and other retirement programs, policymakers need reliable, objective predictions based on the best available data on how reforms would likely affect retiree income and benefits, labor market activities, taxpayer burdens, and program costs and solvency. The predictions are often provided by DYNASIM, the Urban Institute’s well-respected microsimulation model. This grant funds a project by the Urban Institute to expand and improve the DYNASIM model. DYNASIM is a more ambitious tool than nearly every policy evaluation model in use today. It attempts to predict a wider range of outcomes than do most models developed by CBO or the analytical offices of Cabinet agencies. For example, a raise in the early and full retirement ages would almost certainly affect retirement ages, earnings, savings patterns, and the distribution of incomes of those 60 to 74 years in age. It may also influence marriage rates and living arrangements, and could indirectly affect the health status and health insurance coverage of some older Americans. Simple models often focus on just one or two of these outcomes. DYNASIM’s predictions, however, attempt to capture all these indirect effects. With this grant, the Urban Institute will develop further the predictive capabilities of DYNASIM so that the model can be used to produce credible and detailed predictions of the impact of government policy reforms that affect the nation’s elderly. The programs of interest include Social Security, including its Disability Insurance (SSDI), Medicare, tax policies that affect retirement saving, and important components of Medicaid. The grant will examine how reforms in one or more of these programs will affect old-age labor supply, the prevalence of old-age poverty, the distribution of income in old age, out-of-pocket spending on health care in old age, and tax burdens of the elderly. The DYNASIM model will also produce predictions of the effects of these policy changes on both the elderly and the nonelderly. In addition to providing for the needed improvements, the grant includes funds to maintain DYNASIM during the project period, such as by incorporating the latest economic and demographic assumptions used by Social Security and updating tax and other policy parameters. In addition, the Urban Institute team will use some funds to train additional DYNASIM analysts, to ensure the sustainability of the model, and to find ways to provide access to other researchers, so that it can continue to provide the research and policy community with the best information on the effects of retirement policy reforms after the grant period ends.

The Science and Entertainment Exchange was launched by the National Academy of Sciences in 2008 to pair members of the science community with the entertainment industry. The Exchange works to ensure accuracy when science is used in film, tries to seed new ideas within the film and television industry by exposing them to new content, and acts as a resource of professional science advice, including to Sloan’s myriad film partners. This grant funds a series of activities by the Exchange to bolster scientific representation in Hollywood films and television, increase the diversity of its science consultants, and strengthen ties with the Sloan Film program. Grant funds will support the Exchange as it provides science consultants to the film and television community and to Sloan filmmakers on some 300 television and film projects per year. Additional funds will support efforts to increase the number of women and underrepresented minorities in the Exchange’s scientist database and on efforts to include Sloan-supported filmmakers in their Exchange events and outreach.

This grant provides funds to Film Independent (FIND) to organize and host the 2017 Sloan Film Summit, the major convening of all Sloan film grantees held every three years. The summit offers a rare opportunity for interaction and networking between students, faculty, and administrators from the Foundation’s six film schools; filmmakers and staff from the five screenplay development and film festival partners; and Sloan grantees at Museum of the Moving Image (MoMI), Coolidge Corner Theatre, and the Science and Entertainment Exchange. 150 Sloan grantees are expected to attend. The three-day summit will open with a Friday night film screening on the theme of women and science, followed by an opening dinner. Saturday morning will feature Sloan award recipient updates as well as case studies with filmmakers and scientist collaborators. In the afternoon, there will be a networking lunch that connects filmmakers with scientists, followed by an industry connect program allowing filmmakers to meet with agents, casting directors, distributors, and other industry representatives. During this time, representatives from all of Sloan’s film partners will meet with Sloan program staff to share experiences and discuss best practices. Later, breakout sessions involving the latest in virtual reality will be followed by a special evening event. Sunday will open with a science and storytelling keynote from a prominent member of the film or television industry. After the keynote, there will be staged readings of excerpts from Sloan-winning screenplays for an industry audience. The summit will conclude with a showcase of Sloan-supported feature films, including one completed feature and sneak previews of upcoming features. Grant funds support administrative costs associated with hosting the event, along with associated publicity and outreach in print and social media.