This paper explores how the cost of risk management varies with firm characteristics, offering the first comparison between private, public, and family-owned firms. It exploits a natural experiment in highway procurement, which features diverse firms with common exposure to commodity risk. The Kansas government began to insure highway paving firms against oil price risk in 2006. The analysis compares Kansas to Iowa, which has an otherwise similar highway procurement system but never introduced such a policy. Using data from 1998 to 2012, I show that the policy reduced average bid sensitivity to oil price volatility. Private firms with high credit risk and low industry diversification exhibit the most risk pass-through, while public firms exhibit no pass-through. Family-owned firms do not have a higher than average cost of risk. Financial constraints and distress costs appear to best explain the cost of risk management, rather than risk aversion, information, or agency problems.

Venture capital, an important source of financing for potentially high-growth new businesses, is believed to suffer from information frictions. This paper quantifies the magnitude of these frictions among participants in new venture competitions. In a regression discontinuity design with data from 87 competitions, winning a round increases the chances of external financing by about 35%. Winning is most impactful for ventures that are ranked just above the cutoff but receive no cash prize, and judge ranks strongly predict venture success. The results indicate that these information problems in new venture finance are large, and competitions can help resolve them through certification.

Governments regularly subsidize new ventures to spur innovation. This paper conducts the first large-sample, quasi-experimental evaluation of R&D subsidies. I use data on ranked applicants to the US Department of Energy's SBIR grant program. An early-stage award approximately doubles the probability that a firm receives subsequent venture capital and has large, positive impacts on patenting and revenue. These effects are stronger for more financially constrained firms. Certification, where the award contains information about firm quality, likely does not explain the grant effect. Instead, the grants are useful because they fund technology prototyping.

This paper offers the first study of how changes in corporate R&D investment affect labor mobility. We show that increases in R&D spur employee departures to join start-ups’ founding teams. This appears to reflect employees taking the ideas, skills, or technologies created through the R&D process but not especially valuable to the R&D-investing firm to start-ups. The employee-founded start-ups tend to be outside the R&D-investing employer’s industry, suggesting that the underlying ideas would impose diversification costs on the R&D-investing firm. The start-ups are more likely to be VC backed, high tech, and high wage, pointing to substantial spillover benefits.

This paper examines how employee earnings respond to a one-time cash flow shock in the form of a government R&D grant. In a regression discontinuity design, we find that the grant immediately increases average annual employee-level earnings by 2.9%. This benefit accrues only to incumbent employees and rises with job tenure. The grant also affects firm growth, but the initial wage patterns do not appear to reflect growth or productivity. Instead, the evidence supports implicit equity financing within the firm, where employees initially accept lower wages from financially constrained firms and earn more when the firm has ability to pay.

When race is not directly observed, regulators and analysts commonly predict it using algorithms based on last name and address. In small business lending—where regulators assess fair lending law compliance using the Bayesian Improved Surname Geocoding (BISG) algorithm—we document large prediction errors among Black Americans. The errors bias measured racial disparities in loan approval rates downward by 43%, with greater bias for traditional vs. fintech lenders. Regulation using self-identified race would increase lending to Black borrowers, but also shift lending toward affluent areas because errors correlate with socioeconomics. Overall, using race proxies in policymaking and research presents challenges.

We study how private equity buyouts create value in higher education, a sector with opaque product quality and intense government subsidy. With novel data on 88 private equity deals involving 994 schools, we show that buyouts lead to higher tuition and per-student debt. Exploiting loan limit increases, we find that private equity-owned schools better capture government aid. After buyouts, we observe lower education inputs, graduation rates, loan repayment rates, and earnings among graduates. Neither school selection nor student body changes fully explain the results. The results indicate that in a subsidized industry, maximizing value may not improve consumer outcomes.

Amid an aging population and a growing role for private equity (PE) in the care of older adults, this paper studies how PE ownership affects U.S. nursing homes using patient-level Medicare data. We show that PE ownership leads to a patient cohort with lower health risk. However, after instrumenting for the patient-nursing home match, we find that PE ownership increases mortality by 11%. Declines in measures of patient well-being, nurse staffing, and compliance with care standards help to explain the mortality effect. Overall, we conclude that PE has nuanced effects with adverse outcomes for a subset of patients.

Process automation reduces racial disparities in credit access by enabling smaller loans, broadening banks' geographic reach, and removing human biases from decision making. We document these findings in the context of the Paycheck Protection Program (PPP), where private lenders faced no credit risk but decided which firms to serve. Black‐owned firms obtained PPP loans primarily from automated fintech lenders, especially in areas with high racial animus. After traditional banks automated their loan processing procedures, their PPP lending to Black‐owned firms increased. Our findings cannot be fully explained by racial differences in loan application behaviors, preexisting banking relationships, firm performance, or fraud rates.

This article studies how federal funding affects the innovation outputs of university researchers. We link person-level research grants from 22 universities to patents, publications, and career outcomes from the U.S. Census Bureau. We focus on the effects of large, idiosyncratic, and temporary cuts to federal funding in a researcher’s preexisting narrow field of study. Using an event study design, we document that these negative federal funding shocks reduce high-tech entrepreneurship and publications but increase patenting. The lost publications tend to be higher quality and more basic, whereas the additional patents tend to be lower quality, less general, and more often privately assigned. These federal funding cuts lead to an increase in private funding, which partially compensates for the decline in federal funding. Together with evidence from industry-university contracts, the results suggest that federal funding cuts shift university research funding from federal to private sources and lead to innovation outputs that are less openly accessible and more often appropriated by corporate funders.