Alex Xi He
1. "Cutting the Innovation Engine: How Federal Funding Shocks Affect University Patenting, Entrepreneurship, and Publication." With Tania Babina, Sabrina Howell, Elisabeth Perlman, and Joseph Staudt. 2022. Forthcoming, Quarterly Journal of Economics.
Abstract: This paper studies how federal funding affects the innovation outputs of university researchers. We link person-level research grants from 22 universities to patent, publication, 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 pre-existing narrow field of study. Using an event-study design that controls for principal investigator fixed effects, 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, while the additional patents tend to be lower quality, less general, and more often privately assigned. Overall, the federal funding cuts push researchers away from more open research with greater impact on future knowledge, and towards more subsequently appropriated research. The level of funding explains the effects on publications, while the source of funding—federal vs. private—appears to play an important role in the effects on high-tech entrepreneurship and patents. Together with evidence from industry contracts, the results suggest that shifting university research funding from federal to private sources leads to more appropriation of intellectual property by corporate sponsors.
2. "Household Liquidity Constraints and Labor Market Outcomes: Evidence from a Danish Mortgage Reform." With Daniel le Maire. 2022. Forthcoming, Journal of Finance.
Abstract: This paper studies the causal effect of liquidity constraints on individual labor market outcomes by exploiting a mortgage reform in Denmark in 1992, which for the first time allowed homeowners to borrow against housing equity for non-housing purposes. We find that following the reform, liquidity-constrained homeowners extracted housing equity, increased debt levels, and had higher earnings growth and lower employment rates. In contrast, the reform had small and opposite effects on the earnings and employment rates of homeowners with high liquid asset holdings. The option to borrow against housing equity enables liquidity-constrained individuals to move to high-wage jobs and invest in valuable human and physical capital. The results imply that relaxing household liquidity constraints during recessions can create better job matches and potentially increase earnings and output in the longer run.
3. "A Theory of Intermediated Investment with Hyperbolic Discounting Investors." With Feng Gao and Ping He. 2018. Journal of Economic Theory 177.
Abstract: Financial intermediaries may reduce welfare losses caused by hyperbolic discounting investors, who may liquidate their investment prematurely when the liquidation cost is low. In a competitive equilibrium, sophisticated investors are offered contracts with perfect commitment, and first best results are achieved; naïve investors are attracted by contracts that offer seemingly attractive returns in the long run but introduce discontinuous penalties for early withdrawal. If the investor types are private information, naïve investors withdraw early and cross-subsidize sophisticated investors. When a secondary market for long-term contracts opens for trading, financial intermediaries are compelled to offer contracts that have more flexible withdrawal options with linear schemes, and the welfare of naïve investors is improved. Arbitrage-free linear contracts allow for a unique term structure for interest rates that includes a premium for naïveté. Solvency requirements may limit competition for contracts and result in positive profits; banks that have capital are able to compete more aggressively, which improves investor welfare.
1. "Artificial Intelligence, Firm Growth, and Product Innovation." With Tania Babina, Anastassia Fedyk, and James Hodson. 2022. Conditionally Accepted, Journal of Financial Economics.
Abstract: We study the use and economic impact of AI technologies. We propose a new measure of firm-level AI investments using worker resume data. Our measure reveals a stark increase in AI investments across sectors. AI-investing firms experience increased growth in sales, employment, and market valuations. This growth comes primarily through increased product innovation. Our results are robust to instrumenting AI investments using firms’ exposure to universities’ supply of AI graduates. AI-powered growth concentrates among ex-ante larger firms, leading to higher industry concentration. Our results highlight that new technologies like AI can contribute to growth and superstar firms through product innovation.
Abstract: This paper provides evidence from the US and Denmark that managers with a business degree (“business managers”) reduce their employees’ wages. Within five years of the appointment of a business manager, wages decline by 6% and the labor share by 5 percentage points in the US, and by 3% and 3 percentage points in Denmark. Firms appointing business managers are not on differential trends and do not enjoy higher output, investment, or employment growth thereafter. Using manager retirements and deaths and an IV strategy based on the diffusion of the practice of appointing business managers within industry, region and size quartile cells, we provide additional evidence that these are causal effects. We establish that the proximate cause of these (relative) wage effects are changes in rent-sharing practices following the appointment of business managers. Exploiting exogenous export demand shocks, we show that non-business managers share profits with their workers, whereas business managers do not. But consistent with our first set of results, these business managers show no greater ability to increase sales or profits in response to exporting opportunities. Finally, we use the influence of role models on college major choice to instrument for the decision to enroll in a business degree in Denmark and show that our estimates correspond to causal effects of practices and values acquired in business education—rather than the differential selection into business education of individuals unlikely to share rents with workers.
Abstract: This paper studies how managers affect worker wages and wage inequality. We use a manager-firm-worker matched dataset covering the entire population of Denmark from 1995 to 2011 to identify manager-specific wage premiums from worker and manager movements across firms. We document four findings. First, leveraging manager movements across firms and exogenous manager turnovers such as retirements and sudden deaths, we show that the identity of managers does matter for wages, and that manager-specific wage premiums are transferrable across firms. Second, variation in manager-specific wage premiums accounts for 34% of the between-firm wage inequality. Third, managers who pay higher wages are more likely to be replaced in the managerial labor market. In particular, mergers and acquisitions target high-paying managers and reduce wage premiums at their firms. Finally, the manager-specific component of firm wage premia is not correlated with firm productivity and seems to stem from managers’ traits and fairness views. Our results highlight the role of managers in understanding between-firm wage inequality and suggest that the managerial labor market tends to select low-paying managers and redistribute wealth from workers to shareholders.
Abstract: We study the shifts in U.S. firms’ workforce composition and organization associated with the use of AI technologies. To do so, we leverage a unique combination of worker resume and job postings datasets to measure firm-level AI investments and workforce composition variables, such as educational attainment, specialization, and hierarchy. We document that firms with higher initial shares of highly educated workers and STEM workers invest more in AI. As firms invest in AI, they tend to transition to more educated workforces, with higher shares of workers with undergraduate and graduate degrees, and more specialization in STEM fields and IT and analysis skills. Furthermore, AI investments are associated with a flattening of the firms’ hierarchical structure, with significant increases in the share of workers at the junior level and decreases in shares of workers in middle-management and senior roles. Overall, our results highlight that adoption of AI technologies are associated with significant reorganization of firms’ workforces.