Assistant Professor, Strategy & Innovation Department, Boston University, 2019-present
Research Assistant Professor, Wagner Graduate School, New York University, 2018-2019
Nature (June 2022)
There is a well-documented gap in the observed number of scientific works produced by male and female scientists, with clear consequences for the retention and promotion of women in science. The gap might be a result of productivity differences, or it might be due to women's contributions not being acknowledged. This paper finds that at least part of this gap is due to the latter: women in research teams are significantly less likely to be credited with authorship than their male counterparts. The findings are consistent across three very different sources of data. Analysis of the first source - large scale administrative data on research teams, team scientific output, and attribution of credit - show that women are significantly less likely to be named on any given article or patent produced by their team relative to their peers. The gender gap in attribution is found across almost all scientific fields and career stages. The second source - an extensive survey of authors - similarly shows that women's scientific contributions are systematically less likely to be recognized. The third source - qualitative responses - suggests that the reason is that their work is often not known, not appreciated, or ignored. At least some of the observed gender gap in scientific output may not be due to differences in scientific contribution, but to differences in attribution.
Management Science Vol. 68, No. 5 (May 2022)
This paper examines the behavior of job seekers and recruiters in the labor market for software engineers. I obtained data from a recruiting platform where individuals can self-report their computer programming skills and recruiters can message individuals they wish to contact about job opportunities. I augment this dataset with measures of each individual's previous programming experience based on analysis of actual computer source code they wrote and shared within the open-source software community. This novel dataset reveals that candidates' self-reported technical skills are quantitatively one of the most important predictors of recruiter interest. Consistent with social psychology and behavioral economics studies, I also find female programmers with previous experience in a programming language are 11.07% less likely than their male counterparts to self-report knowledge of that programming language on their resume. Despite public pronouncements, however, recruiters do not appear more inclined toward recruiting female candidates who self-report knowing programming languages. Indeed, recruiters are predicted to be 6.47% less likely to message a woman than a man with comparable observable qualifications, even if those qualifications are very strong. Ultimately, a gender gap in the self-reported of skills on resumes exists, but recruiters do not appear to be adjusting their response to such signals in ways hypothesized by the statistical discrimination theory that could increase the representation of women among software engineering recruits.
Research Policy Vol. 50, No. 9 (November 2021)
Open source software transacts at a price of zero, which creates the potential for omission and misattribution in standard approaches to economic accounting. How large and pervasive are those issues in the digital economy? The study is the first to follow usage and upgrading of unpriced software over a long period of time. It finds evidence that software updates mislead analyses of sources of firm productivity, and it identifies several mechanisms that create issues for mismeasurement. To illustrate these mechanisms, this study closely examines one asset that plays a critical role in the digital economic activity, web server software. We analyze the largest dataset ever compiled on web server use in the United States, and link it to disaggregated information on over 200,000 medium to large companies in the US between 2001 and 2018. We find omission of economic value created by web server software is substantial in our sample, and indicates over $4.5 billion dollars of mismeasurement of server software across companies in the United States. This mismeasurement varies by firm age, geography, industry and size. We also find that dynamic behavior, such as improvements of server technology and entry of new products, further exacerbates mismeasurement.
Work in Progress
Journal of Law, Economics, & Organization - revise and resubmit, second round
Equity compensation grants for rank-and-file employees are common among venture-backed start-ups and are considered an ingrained part of their business culture. However, extremely little is known about start-up employee equity holders. This article takes a first step toward filling this gap. More than 1,000 U.S. employees with a college-level STEM degree participated in a survey experiment. Through the combination of natural language processing and machine learning techniques with conventional regression modeling, we examine employees' financial literacy regarding equity-based compensation and their willingness to forego cash compensation for start-up equity. The findings indicate that employees commonly respond to economically irrelevant signals and misinterpret other important financial signals. Thus, respondents demonstrated a greater demand for equity grants when the number of shares offered was relatively large, even though the ownership percentage was fixed. This tendency is associated with low level of financial literacy regarding equity-based compensation as measured by a three-item test developed in this study. The findings suggest that employees harbor a range of “market illusions” regarding start-up equity that can lead to inefficiencies in the labor market and that sophisticated employers can legally exploit. The study’s results raise serious questions about the protection of employees in their investor capacity in a market in which highly sophisticated repeat players—namely, venture capital and other private equity investors—interact with unorganized and uninformed retail investors.
Using Visa debit and credit card transactions in the U.S. from 2016 to 2019, we document the importance of customers in accounting for sales variation across merchants, across stores within retail chains, and over time for individual merchants and stores. Customers, as opposed to transactions per customer or dollar sales per transaction, consistently account for about 80% of sales variation. The top 5% of growing and shrinking merchants account for the bulk of customer reallocation in a given year. We then write down a simple growth model that incorporates both the ex- tensive and intensive margins by which firms can increase sales, and illustrates why the distinction could matter. In this context, we show that the extensive customer margin amplifies the role of large firms in sales and sales growth, but does not stimulate aggregate growth.
Money for Something: Braided Funding and the Structure and Output of Research Groups
In 2017, the federal government invested over $40 billion on university research; another $16 billion came from private sector sources. The expectation is that these investments will bear varied fruits, including outputs like more economic growth, more scientific advances, the training and development of future scientists, and a more diverse pipeline of STEM researchers; an expectation that is supported by the work of recent Nobel Laureate in Economics, Paul Romer. Yet volatility in federal funding, highlighted by a 35 day federal shutdown in early 2019, has resulted in an increased interest on the part of scientists in finding other sources of funding. Understanding the effect of such different funding streams on research outputs is thus of more than academic importance, particularly because there are likely to be tradeoffs, both in terms of the structure of research and in terms of research outputs. For example, federal funding is often intended to affect the structure of research, with explicit goals of training the next generation of scientists and promoting diversity; those goals are less salient for non-federal funding. On the output side, federally funded research may be more likely to emphasize producing purely scientific outputs, like publications, rather than commercial outputs, like patents. The contribution of this paper is to use new data to examine how different sources of financial support – which we refer to as "braided" funding – affect both the structure of scientific research and the subsequent outputs.
Serendipity in Science
[draft available on request]
- Nominated for SMS Annual Conference Best Paper Prize
- Nominated for SMS Annual Conference Research Methods Paper Prize
Price Shocks and Scientific Production
[draft available on request]
Book Chapters and Other Writing
Chapter in NBER book The Changing Frontier: Rethinking Science and Innovation Policy (2015), Adam Jaffe and Benjamin Jones, editors (p. 17 - 48)