Lin Shen

Artificial Intelligence and Quantity Traps (with Naveen Gondhi and Junyuan Zou) ​

We study an equilibrium model of academic publishing in which researchers choose the quality (and quantity) of papers, and journals screen submissions imperfectly. AI expands researchers’ productive frontier by increasing the routine capacity, but their deep attention capacity remains unchanged. As AI improves, researchers have stronger incentives to produce more papers, which leads to more congestion at journals. More congestion, in turn, increases the screening noise, which incentivizes authors to write more papers rather than investing in quality. This amplification mechanism leads to (i) more submissions, (ii) lower average quality, and (iii) under identifiable conditions, reduces the published knowledge. Interestingly, the model also highlights how heterogeneity across researchers (in career stage, time constraints, and institutional burdens) reshapes the composition of published work, favoring scalable production over deep contribution for some groups more than others.

Voluntary Data Sharing in Lending Competition (with John Kuong and Junyuan Zou)

Conventional wisdom holds that an incumbent bank would never voluntarily share proprietary borrower data with a competing lender. We study lending competition in which the incumbent owns data that generate informative signals about borrower quality and chooses how much to make portable to an entrant. When the data identify high-quality borrowers, sharing softens the entrant’s bidding after unfavorable signals more than it sharpens competition after favorable ones, so the incumbent shares voluntarily, especially for observably creditworthy borrowers. A utilitarian planner instead favors greater sharing for weak borrowers. The economic content of the data, and who controls it, jointly shape the welfare effects of open banking.

Policy Portfolio for Banks: Deposit Insurance and Liquidity Injection (with Chong Huang and Junyuan Zou)

Banking crises pose significant threats to our economy, leading to the implementation of policy measures such as deposit insurance and liquidity injection to strengthen financial stability and optimize resource allocation efficiency. This paper investigates the dynamic interplay between deposit insurance and liquidity injection. Facing uncertainty regarding bank health and depositor liquidity shocks, policymakers decide on liquidity injection based on withdrawals. While higher deposit insurance coverage can mitigate panic runs, it may undermine the effectiveness of liquidity injections. We demonstrate that liquidity injection overshadows deposit insurance. Consequently, the optimal policy portfolio entails zero deposit insurance, enhancing resource allocation efficiency but leading to more panic runs. 

Capital Flows in the Financial System and Supply of Credit, R&R at Journal of Finance

Runner-up for the Best Theory Paper on the Academic Job market in Finance 2019

This paper develops a model to study how capital flows in the financial system affect banks’ coordination problem in the credit supply process. The economy is susceptible to self-fulfilling credit freezes: banks abstain from lending when they fear that other banks will withhold lending, and the resultant credit contraction impedes economic growth. Capital flows across banks can alleviate the problem by enabling optimistic banks to borrow from pessimistic banks and extend more credit to the real economy. However, the equilibrium interest rate reveals public information about economic fundamentals and banks’ aggregate willingness to lend, increasing the fragility of the credit market. As a result, the economy can get stuck in an equilibrium where both interbank capital flows and the real credit supply freeze and they reinforce each other through a vicious feedback loop. Regulations addressing counterparty risks can help to maintain active capital flows in the financial system and stabilize the real credit market.

Corruption and Competition (with Franklin Allen and Jun “QJ” Qian)

This paper investigates how a central government can effectively curtail the corruption of local government officials. An interesting aspect of corruption is that its damaging effects on economic performance differ significantly across countries. We show that if a central government collects sufficient taxes, it can fight corruption by rewarding local government officials based on performance. Without sufficient budget, the central government can reduce corruption alternatively by encouraging competition among local government officials. We also provide empirical evidence that differences in taxing ability and the magnitude of competition among government officials can help explain the heterogeneous effects of corruption across countries.