The macroeconomic risk associated with climate change potentially results in a risk premium on asset prices. Using a sample of 11,468 Chinese quasi-municipal bonds from 2014-2021 in 267 cities, this research investigates the impact of climate risk on the credit spreads of quasi-municipal bonds. We employ principal component analysis (PCA) to construct a climate risk index and find that climate risk significantly increases credit spreads by increasing the local government fiscal gap and debt burden. The effect of climate risk is more remarkable for bonds that have shorter maturity and lower corporate ratings, issued by smaller city investment companies and corporations located in regions with stronger environmental regulation, stronger climate risk perception, and better green financial development. A significant relationship is also observed in the eastern regions but not the western regions. This study broadens the scope of quasi-municipal bond credit spread determinants from traditional financial to climate indicators.

There is increasing attention on information transfers along supply chain partners for firm (extreme) events. This growing literature finds spillover effects following certain types of firm events. Using data from credit rating actions of Chineselisted firms over the period between March 2007 and May 2020, we examine the spillover effects of supply chains by focusing on the market reactions of event firms to the action announcements. We find strong evidence of spillover effects driven by the market reactions of event firms, which are enhanced through information diffusion channels as supply chain partners receive more investor attention. Moreover, the effects are stronger when event firms’ market reactions are negative, event firms are nonstated-owned, the industry concentration of event firms is higher, or the suppliercustomer business relationship is closer. Overall, these findings highlight the role of investor attention in addition to network characteristics in supply chain spillovers.

This study examines the impact of social insurance contributions on corporate environmental investments. Adopting a quasi-natural experimental design based on the implementation of 2011 Social Insurance Law in China, we employ a difference-in-differences model and find that the increase in social insurance contributions prompts firms to increase their environmental investment. This effect is more pronounced for firms that exhibit higher labor intensity, and are located in regions with stricter environmental regulations, as well as those with politically connected CEOs. Our research provides valuable insights into the factors that influence firms’ environmental investment from the perspective of firm-government interaction.

This study examines how information friction shapes housing market outcomes in Beijing, China. Leveraging administrative micro-level housing resale transactions, we employ a boundary discontinuity design and difference-in-differences model to explore the consequences of prohibiting school-district-quality information disclosure in online listings. Our results show that the prohibition leads to a 2.55% reduction in transaction prices and a 22.99% increase in seller's time on the market for houses corresponding to key primary schools. The extended time on the market is primarily attributed to the heightened challenges that potential buyers face in finding their ideal dwellings.

The voluminous strategy research on the determinants of corporate scope is often premised on a well-established property rights regime, which contrasts with the weak property rights protection that still characterizes most countries today. We address this gap by applying property rights theory to theorize and empirically examine how the strengthening of the property rights regime affects corporate scope. Our analysis exploits the enactment of a property law that enhanced the formal protection of private properties in China as a quasi-experiment. We show that with a strengthened property rights regime, the horizontal relatedness among private firms’ businesses increases, but their vertical relatedness decreases, compared with state-owned firms. Further, these effects are less prominent for politically connected firms that are afforded informal protection of property rights. Our findings shed new light on the property rights regime as a critical determinant of firms’ horizontal and vertical scope.

We examine communication of political connections in corporate China, and show that politically inclined positive words—words in connotation of political sentiment—serve as a distinct and effective signaling device for corporate political connections. Using a large sample of corporate news, we find that news’ political sentiment, instead of orthodox political measures such as occurrences of political nouns and political entities, reflects executives’ political connections for private enterprises, and is related to rent-seeking benefits in government subsidy, tax refund, financing constraints and political risk. Our results demonstrate that political sentiment is an effective way to decode subtle corporate political connections in modern China’s “Mind Politics” environment that infiltrates into private corporations.

This work models the spillover of liquidity and volatility and their joint dynamics in the Chinese stock market. Methodologically, we implement a copula-based vector multiplicative error model for sectors. Utilizing intraday data from 2014 to 2022, our empirical analysis reveals strong interdependence between liquidity and volatility at the sectoral level. Moreover, different sectors dominate the transmission of liquidity and volatility shocks at different times. In normal times, sector volatilities transmit shocks notably (though not always dominantly), while in turbulent times, illiquidity is the key channel through which shocks spread. We also pay special attention to how two catastrophic events impacted the Chinese stock market: the 2015/16 stock market crash and the COVID-19 pandemic. Our ffndings are useful for policymakers monitoring and making policy at the sectoral level, as well as for institutional and private investors making investment decisions.

Investor sentiment has a crucial impact on stock market pricing. Based on prospect theory and partial least squares, we innovatively construct an investor sentiment indicator and verify the validity of the indicator. Compared with other sentiment indices, our investor sentiment index is more effective in in-sample and out-of-sample forecasting. At the same time, from a cross-sectional perspective, both the portfolio analysis and the Fama-Macbeth regression show that the partial least squares results are a better indicator of returns than other indices. The driving force of the sentiment index we construct comes from investors’ perceptions of forecast cash ffow, discount rate, and volatility.

China’s household wealth is growing rapidly and has become significant worldwide. While the government played an important role in economic growth and wealth accumulation, few research has explained why and how government expenditure redistributes household wealth in China. This study uses China Family Panel Studies (CFPS) household survey (2010-2018) and prefecture-level data to estimate the impact of government expenditure on household wealth, especially the value of housing asset. We find that the capitalization of government expenditure contributes an important part to housing value appreciation, which accounts for more than 50% of household wealth. Furthermore, the impact mechanism of government expenditure on households’ wealth has a substantial redistributive effect. Government expenditures greatly advance the net worth of households who own their houses, especially for households that own two or more houses, but contribute much less to those comprising rental tenants.

Based on the formation and evolution of systemic risk, this study proposes high and low volatility spillover networks and explores the characteristics of the evolution of systemic risk in Chinese financial market, and identifies the source of risk accumulation and risk outbreak, as well as the corresponding contagion mechanisms. Moreover, a new multiscale decomposition method (MVMD) is used to decompose high and low volatility into different time frequency components (short-term and long-term), and the corresponding network is constructed. Upon comparing topological characteristics on each layer from system and individual levels, our results reveal that high and low volatility spillover networks have different network characteristics and evolution behaviors. At the individual level, bond market is always the largest risk net-receivers in the high and low volatility networks, while the futures market and the currency market are respectively risk net-emitters in the high and low volatility networks. Additionally, compared with high volatility network, the low volatility network has greater predictive ability for financial risk. Finally, frequency analysis demonstrates that high-low volatility networks have different spillover intensity and network structure at different time frequencies. The above findings are beneficial for policy makers and investors to formulate appropriate strategies in different evolution of systemic risk and time frequency.