Jingnan (Jane) Liu

Jingnan (Jane) Liu

Ph.D. Candidate in Economics

University of Wisconsin-Madison

I am a Postdoctoral Associate at the MIT Sloan Initiative on the Digital Economy. My research focuses on the labor market and economic growth. I seek to understand (i) the inventor labor market and how it impacts economic growth and (ii) how technological progress impacts labor, innovation, and productivity.

I obtained my Ph.D. in Economics from the University of Wisconsin-Madison in 2024. I will join the Department of Economics at the University of Illinois Urbana-Champaign as an Assistant Professor in fall 2025.

  • Macroeconomics
  • Labor Economics
  • Economic Growth
  • Innovation
  • Firm Dynamics
  • Ph.D. in Economics, in progress

    University of Wisconsin-Madison

  • M.S. in Economics

    University of Wisconsin-Madison

  • B.A. in Economics

    Renmin University of China


Working Papers

Worker Mobility, Knowledge Diffusion, and Non-Compete Contracts
  • Job Market Paper

  • Abstract: This paper studies how endogenous worker mobility affects inter-firm knowledge diffusion, innovation, and economic growth. I propose a framework combining endogenous growth and on-the-job search. Firms grow knowledge by in-house innovation and by hiring workers from more productive firms. Knowledge is nonrival, leading to underinvestment in innovation. Non-compete contracts address this underinvestment by allowing innovating firms to enforce buyout payments when they lose workers. However, they discourage diffusion by deterring firm entry. Linking patent records to matched employer-employee administrative data at the U.S. Census Bureau, I document that inventors diffuse knowledge across firms and are compensated for knowledge diffusion. Constructing novel microdata, I find non-compete contracts are associated with increased innovation expenditure and decreased worker mobility. I calibrate my theoretical model to match the empirical results. Knowledge diffusion, through the channel of worker mobility, accounts for 4% of the aggregate growth rate and 9% of welfare. Optimal regulation of non-compete contracts balances the innovation-diffusion tradeoff.

Strategic Restraint: When do Human-Capital-Intensive Companies Choose (Not) to Use Noncompete Agreements?
  • with Martin Ganco, Haifeng Wang and Shotaro Yamaguchi

  • Paper, Accepted by Strategic Management Journal

  • Abstract: Extant work in strategic management has focused on the role of noncompete agreements (NCAs) – a form of restrictive legal lever used by firms when managing human capital – and conceptualized them as being advantageous to firms. Challenging this notion, we highlight a novel downside of using NCAs and show how their use by some firms creates differentiation opportunities for rival firms. We analyze a unique survey dataset to examine the heterogeneity in the firms’ actual use of NCAs conditional on industry and state. We find that the nonuse of NCAs is more common among firms that rely more heavily on talent and are also not the industry leaders, and such firms are more likely not to use NCAs with the goal of attracting skilled employees.

Signals and Human Capital in Admission Tournament
  • Field Paper

  • Abstract: This paper develops a structural model of pre-college educational investment in college admission tournaments. Students are heterogeneous in ability, family wealth, and preferences for colleges and can purchase tutoring services to improve their human capital and test scores. They also face borrowing constraints. The score distribution, admission thresholds, and college assignment are joint equilibrium outcomes. The model is estimated with Korean ELS: 2005 data and can be used to study Korea’s tutoring market with a wide range of policy candidates, including taxing private tutoring and reducing noise in admission. A tax lowers the overall spending on tutoring. The students from middle-income families are most responsive to the price change. Reduced signal noise incentivizes the tutoring expenditure of high-ability students and improves their chances of attending prestigious colleges.

Regional Policy Spillovers and Complementarity in the Great Lockdown
  • with Xiaodong Fan and Chao He

  • Paper

  • Abstract: Solving systematic problems, such as a pandemic, requires coordination across borders. Nevertheless, coordination is rarely implemented across nations and sometimes not even within the same country. One reason is that it is unclear whether regional policies reinforce or weaken one another due to opposing theoretical channels. If regional policies are complementary, then a joint implementation can achieve greater effects, and there exists the risk of coordination failures in the form of multiple equilibria. However, substitutability implies otherwise. We apply a new differencein- differences method developed by Callaway and Sant’Anna (2021), robust to heterogeneity in treatment effect dynamics, to study the effects of regional stay-at-home (SAH) orders on local and adjacent regions’ infection growth rates during the COVID- 19 pandemic in the United States. We find regional SAH orders to be complementary in reducing infection growth. Specifically, the policy spillover effect reduces the infection growth rate by 3.33 percentage points in the first three weeks of treatment with local implementation or 1.93 percentage points without local implementation, with an accumulative case reduction of 50.9 or 33.6 percent, with or without local implementation. Our results suggest the possibility of coordination failures and that regional lockdowns are best implemented jointly.

Work In Progress

Teachers' Labor Market and Student Outcomes
  • with Chao Fu, Christopher Taber and Matthew Wiswall

  • Abstract: We study how teacher personnel policies can affect the types of individuals who enter and stay in teaching and student outcomes. We develop and estimate a model of individuals' college major choices and life-cycle occupational choices jointly with an explicit formulation of an education production function. The model allows for rich heterogeneity in tastes and skills. We combine data from existing surveys, administrative data, and our own surveys to identify the model. We will use our estimated model to conduct a series of counterfactual policy experiments to examine the cost-effectiveness of various policies on the teachers’ labor market.


  • 32 Vassar Street, Cambridge, MA 02139
  • Office G766