5篇！2024年中国境内高校学者发表的RFS论文

01. Local Effects of Global Capital Flows: A China Shock in the U.S. Housing Market

全球资本流动的本地效应：美国房地产市场中的中国冲击

刊发时间: MAR 2024

黎志敏

北京大学汇丰商学院

Leslie Sheng Shen

美国波士顿联邦储备银行

Calvin Zhang

美国费城联邦储备银行

This paper studies the real effects of foreign real estate capital inflows. Using transaction-level data, we document (i) a “China shock” in the U.S. housing market characterized by surging foreign Chinese housing purchases after 2008, and (ii) “home bias” in these purchases, as they concentrate in neighborhoods historically populated by ethnic Chinese. Exploiting their temporal and spatial variation, we find that these capital inflows raise local employment, with the effect transmitted through a housing net worth channel. However, they displace local lower-income residents.Our results show that real estate capital inflows can both stimulate the real economy and induce gentrification.

02. Disclosure of Bank-Specific Information and the Stability of Financial Systems 

银行特定信息的披露与金融系统的稳定性

刊发时间: APR 2024

戴亮

香港中文大学（深圳）

羅丹

香港中文大学

Ming Yang

伦敦大学学院

We find that disclosing bank-specific information reallocates systemic risk, but whether it mitigates systemic bank runs depends on the nature of information disclosed. Disclosure reveals banks’ resilience to adverse shocks and shifts systemic risk from weak to strong banks. Yet, only disclosure of banks’ exposure to systemic risk can mitigate systemic bank runs because it shifts systemic risk from more vulnerable banks to those less vulnerable. Disclosure of banks’ idiosyncratic shortfalls of funds does not differentiate such exposure, rendering the resultant reallocation of systemic risk ineffective in mitigating systemic runs.

03. Corporate Climate Risk: Measurements and Responses

企业气候风险：衡量和应对

刊发时间: JUN 2024

Qing Li

佛罗里达大学

单宏宇 

中欧国际商学院；福特汉姆大学

唐岳华

佛罗里达大学

姚文雄

佐治亚州立大学

This paper conducts a textual analysis of earnings call transcripts to quantify climate risk exposure at the firm level. We construct dictionaries that measure physical and transition climate risks separately and identify firms that proactively respond to climate risks. Our validation analysis shows that our measures capture firm-level variations in respective climate risk exposure. Firms facing high transition risk, especially those that do not proactively respond, have been valued at a discount in recent years as aggregate investor attention to climate-related issues has been increasing. We document differences in how firms respond through investment, green innovation, and employment when facing high climate risk exposure.

04. The Bright Side of Political Uncertainty: The Case of R&D

政治不确定性的光明面：研发案例

刊发时间: OCT 2024

Julian Atanassov

内布拉斯加大学

Brandon Julio

俄勒冈大学

冷铁成

哈尔滨工业大学

We use close gubernatorial elections as a quasi-natural experiment to document a positive effect of political uncertainty on firm-level R&D. This finding is in contrast to the existing literature documenting a negative impact of political uncertainty on capital investment. We examine potential mechanisms and find that our results are consistent with the growth option view of R&D investment. The effect is stronger for politically sensitive and high-tech industries.The results are robust to different proxies for political uncertainty shocks. As predicted by models of investment under uncertainty, the real effects of political uncertainty critically depend on the type of the investment. 

我们使用势均力敌的州长选举作为准自然实验来记录政治不确定性对公司层面研发的积极影响。这一发现与记录政治不确定性对资本投资的负面影响的现有文献形成鲜明对比。我们研究了可能的机制，发现我们的结果与研发投资的增长选择观点一致。这种影响对政治敏感和高科技行业的影响更大。结果对政治不确定性冲击的不同代理是稳健的。正如不确定性下投资模型所预测的那样，政治不确定性的真正影响在很大程度上取决于投资的类型。

05. The Technical Default Spread

技术性违约价差

刊发时间: NOV 2024

Emilio Bisetti

香港科技大学

李凯

北京大学汇丰商学院

Jun Yu

墨尔本大学

We study the quantitative impact of lender control rights on corporate investment, asset prices, and the aggregate economy. We build a general equilibrium model in which the breaching of a loan covenant (technical default) entails a switch in investment control rights from borrowers to lenders. Lenders optimally choose low-risk projects, thus mitigating borrowers’ risk-taking incentives and lowering the cost of equity. This mechanism generates strong macroeconomic effects and mitigates the financial accelerator. Consistent with our model, proximity to technical default in the data is associated with 4.12% lower returns and lower exposure to systematic risk.