Understanding the drivers of China's cross-border capital flows is critical for maintaining financial stability and curbing financial risks in China. Cross-border flows are generally driven by both push and pull factors. Conventional wisdom holds that these can be best captured by interest rate differentials across countries. However, interest rate differentials are not the only driver of China's cross-border flows. Empirical studies suggest that speculation on potential price movements in bilateral exchange rates (i.e., currency speculation) is also an important motivation. In history, as both the interest rate and the RMB exchange rate are not fully market-driven in China, there may be other factors that have affected China's cross-border flows.
To shed light on this important issue, we focus on the role of the U.S. dollar index (DXY). Leveraging the time-varying parameter vector auto-regression (TVPVAR) method, we find that the DXY is the most critical factor in determining China's cross-border flows. This finding is robust to a variety of sample periods and model specifications. Why is the exchange rate more important than the interest rate？ And why is the multilateral dollar exchange rate more critical than the bilateral exchange rate of the RMB against the U.S. dollar？ We refer these questions as “the conundrum of China's cross-border capital flows.” To resolve this conundrum, we examine the channels through which the DXY affects capital flows and propose a novel framework to explain China's cross-border flows.
Our empirical results suggest that the DXY influences capital flows through two main channels. The first is via exchange rate expectations. For a long period, the RMB exchange rate was either pegged or crawling pegged to the U.S. dollar, resulting in the low flexibility of the RMB. In this condition, when factors other than China's economic fundamentals make the U.S. dollar appreciate, the RMB is expected to depreciate, which leads to the outflow of speculative capital. Similarly, when the U.S. dollar depreciates, the RMB is expected to appreciate, which attracts capital flows. Therefore, when the bilateral RMB exchange rate against the U.S. dollar cannot make timely adjustments based on fundamentals, the DXY becomes a leading indicator of RMB exchange rate expectations, thereby driving capital flows. The second channel is through risk appetite. Studies document that the U.S. dollar cycle is highly correlated with the global risk appetite and the DXY is becoming the best representation of global investors' risk appetite. As the world's most important financing currency, the value of the U.S. dollar affects the willingness and ability of major global financial institutions to provide liquidity through the balance sheet effect.
If the DXY drives China's cross-border capital flows, what drives the DXY？ Our results show that the China-U.S. interest rate differential increasingly explains and even leads the DXY. The China-U.S. interest rate differential first and foremost reflects the differentiation of the economic fundamentals of the two economies. As China's spillovers become stronger, however, the China-U.S. differential also drives and reflects economic differentiation between the U.S. and other major economies, including Europe and Japan. Accordingly, the China-U.S. interest rate differential could still explain and lead the DXY, despite the index not including the RMB.
Our most critical contributions are uncovering a novel factor that determines China's capital flows—the DXY—and showing that it is more important than interest rate differentials. However, we also find that China-U.S. interest rate differentials can explain the DXY. The explanation for these seemingly contradictory findings lies in the historical inflexibility of the RMB’s bilateral exchange rate, which does not fully reflect shifts in economic fundamentals in a timely and adequate manner. This lagging and insufficient response can be corrected through two channels. One channel is through capital flows driven by interest rate differentials, a traditional channel frequently highlighted in the literature and by policymakers. We emphasize a brand new and more critical channel: the exchange rate speculation channel arising from the lack of exchange rate flexibility.China's economy drives the DXY due to its increasing spillovers to Europe and Japan. The DXY in turn drives China's cross-border flows by affecting exchange rate expectations and global risk appetite. When changes in the bilateral exchange rate are lagging and insufficient, currency speculation and changes in risk appetite could lead to large and volatile capital flows. Therefore, increasing exchange rate flexibility would not only increase monetary policy independence but also significantly reduce the overshooting of capital flows.

As GDP can comprehensively reflect the economic condition of a country or a region, GDP predictions are carefully scrutinized by many institutions. However, because GDP is usually only calculated on a quarterly frequency and released after a delay of 3 weeks, classical forecasting models cannot provide accurate and timely GDP predictions. However, some macroeconomic variables that are highly correlated with GDP, such as industrial added value, import and export volumes, and the total retail sales of consumer goods, are released monthly with a much smaller delay. The incorporation of this monthly information into GDP prediction could therefore improve the timeliness of GDP forecasting, enable the correct evaluation of economic conditions, and facilitate the formulation of appropriate macroeconomic regulations. However, the incorporation of these monthly indicators into economic forecasting models will require the solution of key problems associated with these indicators' underlying data, namely its mixture of data frequencies, the ragged-edge behavior of real-time data, the presence of data revision, and the periodic absence of data.
To deal with the problems of absent data and ragged-edge data, we nowcast China's GDP based on Zheng and Wang's (2012, 2013) mixed-frequency dynamic factor model for year-on-year growth rates. Compared with mixed data sampling (MIDAS) and mixed-frequency vector autoregression (MFVAR) models, the mixed-frequency dynamic factor model accounts for missing data in addition to dealing with ragged-edge data, and thus makes full, accurate, and timely use of the data. In addition, a year-on-year growth rate model is more useful in China, as the National Bureau of Statistics announces only year-on-year growth rates for most macroeconomic indicators, and policymakers focus on year-on-year GDP growth rates. Moreover, as year-on-year growth rates are based on data for the same month or quarter each year, they can mitigate effects due to seasonality, which is not generally accounted for in official year-on-year economic growth data released in China (and is another reason why a year-on-year growth rate model is appropriate for China). Thus, once new data are released, we can immediately update our nowcasting result. This means that we can nowcast the quarterly GDP growth rate in real time using the most up-to-date data and thus provide a reliable and timely economic prediction for decision-makers. Our results also show that the mixed-frequency dynamic factor model provides more accurate predictions than the MIDAS and the MFVAR models.
In addition to developing GDP nowcasting, we derive some other important results. First, in contrast to GDP data, which are announced quarterly, in April, July, October, and January, with an approximately 3-week delay, we can estimate the quarterly GDP growth rate on a monthly basis. For example, we estimate the year-on-year growth rate of GDP from February to April, which is crucial information for decision-makers and for economic modeling. Second, in addition to determining the smoothed estimator of a common factor, we also obtain the smoothed estimator of the idiosyncratic factor. The sum of these factors is then used to derive a smoothed estimate of the monthly year-on-year growth rate of real GDP. Third, we circumvent the missing data problem, which is due to the restriction of statistical rules, the effect of the Spring Festival, and other factors, by estimating the missing data from the observations of other indicators, which affords a complete time series of data.
In summary, our GDP nowcasting method enables daily (rather than quarterly) forecasting of China's quarterly GDP growth rate, which means that we can incorporate the latest information about economic conditions into our forecasts. Thus, we can provide more timely and reliable economic predictions to policymakers. From the perspective of macroeconomic regulation, these economic predictions may allow policymakers to generate real-time updates of its judgments on current economic conditions and thereby formulate more timely and suitable macroeconomic policies. From the perspective of microeconomic decision-making, these economic predictions may enable enterprise managers to understand the current economic situation more clearly and in a timely fashion, and thereby to efficiently adjust investment plans and development strategies. Thus, we believe that our nowcasting-based economic predictions will be invaluable for developing more effective national-level macroeconomic control and enabling better market-level microeconomic decisions.

In the past 20 years, the rapid economic development and urbanization of major Chinese cities has led to rising house prices. According to the National Bureau of Statistics, the average cost of housing in 35 large and medium-size cities increased from 2,267 yuan per square meter in 2002 to 15,356 yuan per square meter in 2019. To curb excessive speculation in the property market and stabilize land prices, house prices, and price expectations, local governments began issuing a series of house purchase restriction policies in 2010. By the end of 2011, 46 cities had restriction policies on issues such as house quantity, household registration, and loan proportion. These policies were lifted in 2014 in most cities as the property markets stabilized.
However, the rapid increase in housing costs in 2015 and 2016 led to a new round of housing purchase restrictions in 60 cities by 2019. Although they differ in details, the prime goal of all of these policies is to curb rapidly rising house prices by restraining demand in the housing market. As a powerful tool for stabilizing and regulating the real estate market, these purchase restriction policies have had a great impact on real estate companies and even the real estate industry, which is a pillar of the Chinese economy. As a result, these housing market policies have attracted the attention of all parts of society.
Using a dataset of listed real estate companies from the 2008-2013 and 2015-2019 periods, this paper uses difference-in-differences (DID) models with an intensity index to empirically analyze the impact of the two rounds of housing purchase restriction policies on listed real estate companies and to identify the main channel of influence. As the real estate projects developed by listed real estate companies in different cities are different, the house purchase restrictions have different effects in different cities. To address the issue of intensity difference across real estate companies, this paper uses specific identification with accumulative intensity indexes.
First, this paper uses the proportion of listed real estate companies' sales in each city to construct an intensity index of house purchase restrictions, and then it uses an intensity DID model to determine whether either round of house purchase restrictions significantly reduces the market value of real estate companies. Then, this paper analyzes the heterogeneous effects of different house purchase restriction polices. It finds that in the first round, the most effective policies are those that control household registration, are applied to the whole city, and impose a two-house limit. In contrast, in the second round, policies applied to specific city districts and restrictions on resales are also effective.
Second, this paper analyzes the operating performance data of listed real estate companies and finds that purchase restrictions have no significant effect on most business performance indicators, with the exception of a negative impact on the solvency of enterprises in the first round. This suggests that purchase restrictions may increase the operating risk of real estate companies and have a negative impact on the development capability of enterprises in the second round. For the property market, this paper finds that the first round of purchase restrictions does not have a significant impact on urban property prices, but the second round significantly curbs the rise of house prices. Hence, the two rounds of policies have different impacts on the expectations of stock investors due to their different effects on the real estate market.
Finally, this paper analyzes the daily performance of real estate companies listed on the Shenzhen and Shanghai stock markets. Both rounds of purchase restrictions have significant negative impacts on the daily return rates and the monthly search indices of the real estate companies, showing that the effect of purchase restrictions on the value of listed real estate companies is mainly caused by investor expectation. These findings are of great significance for understanding the development of China's real estate market, specifically the effects of the current adjustments. They suggest that the two rounds of house purchase restrictions changed the market value of listed real estate companies by changing investors' expectations, reflecting the role of housing policies in stabilizing expectations. The aim of the real estate policy is to have a long-term influence on housing markets and investors' expectations by strengthening the attitude that “a house is for dwelling rather than for speculating.”

In recent years, global economic growth has slowed, and anti-dumping trade barriers have become increasingly common measures for trade protection. Uncertainty in the external environment of global economic development has intensified. According to China's Ministry of Commerce, in 2020, Chinese exports were subject to 132 trade remedy investigations in 28 countries (regions), involving approximately 13.1 billion U.S. dollars. At the same time, Chinese companies' cross-border M&A have been undergoing a rapid development trend. According to the UNCTAD World Investment Report 2020, China's foreign direct investment flow in 2019 was 136.91 billion U.S. dollars, the second highest in the world. It has ranked in the top three in the world for 8 consecutive years. Cross-border M&A have become the main form of foreign direct investment by Chinese companies. Therefore, whether the trade barriers encountered by China have led to the rapid growth of corporate cross-border M&A, and how companies should rationally identify and respond to the opportunities and risks of cross-border M&A brought about by trade barriers are urgent questions with both theoretical and policy implications.
Trade barriers have multiple effects on enterprises' foreign direct investment. Current theories suggest that cross-border capital flows are complete substitutes for international trade, and capital flows mainly come from trade barriers. Early research on Japanese samples shows that anti-dumping regulations promote multinational investment by Japanese companies in Europe and the United States, and companies use cross-border M&A to replace product exports, thereby saving transportation costs and tariff costs (Belderbos, 1997; Barrell and Pain, 1999). However, other studies find that strong trade barriers strongly control the foreign investment of enterprises. Given the various forms of internationalization available to enterprises from countries that are the target of trade frictions, the host country often adopts the “full caution” principle, making it possible for enterprises to cross trade through investment more difficult to achieve. Only multinational companies in developed countries tend to use cross-border M&A to circumvent anti-dumping policies. From the perspective of industry, technology-intensive industries are more likely to adopt cross-border M&A in response to anti-dumping regulations than labor-intensive industries.
Based on the Thomson Financial Mergers and Acquisitions (SDC) database, this paper uses a sample of Chinese companies' cross-border M&A and the World Bank's anti-dumping database to comprehensively examine the impact of anti-dumping regulations on cross-border M&A. This paper makes three innovations. First, the literature focuses on the macro levels of country and industry, and from this view there are few studies of how anti-dumping regulations affect enterprises' cross-border M&A. By constructing multi-level anti-dumping and cross-border indicators of M&A, this paper comprehensively considers the effectiveness and internal influence mechanisms of micro-enterprises' use of cross-border M&A as a response to anti-dumping regulations, and it effectively enriches and expands related fields. Second, this paper finds that contrary to the literature, anti-dumping regulations do not directly induce corporate cross-border M&A but have a significant cross-industry and cross-“host country” inhibitory effect. Third, there are few studies of the relationships between the scale, effectiveness, and type of cross-border M&A and the relationship between anti-dumping and cross-border M&A, and this paper shows that the dimensional indicators influence each other in complicated ways. As a result, this paper provides a foundation for further research on the incentive effects of trade barriers.

Economic theory demonstrates that a household increases its precautionary savings rate over time to cope with natural disasters and smooth consumption. However natural disasters such as earthquakes, floods, droughts, hurricanes, and insect plagues have different effects on households, and thus the empirical testing of combinations of different kinds of natural disasters will generate biased estimates.
Approximately 2.7 billion people worldwide live in areas that are considered seismic zones, but the economic literature inadequately depicts their consumption and saving patterns. This paper holds that earthquakes, unlike other natural disasters, threaten the lives of people who dwell in seismic zones, and thus trigger fear and anxiety in these people. Consequently, those who live in seismic zones may have different consumption and savings habits than those who live in non-seismic zones. This paper hypothesizes that the long-term effect of earthquakes results in residents living in a seismic zone exhibiting a “living in the moment” attitude, which affects their consumption and saving habits. Specifically, although the experience of earthquakes has no significant long-term effects on levels of household income, the earthquake-associated risk of death and psychological shock has significantly positive effects on hedonic consumption, which reduces rates of household saving.
This paper uses nationally representative household survey data from the National Bureau of Statistics of China that covers 18 provinces from 2002 to 2009 and conducts empirical tests to obtain the following conclusions. First, each experience of an earthquake (M_L ≥ 4.5) reduces the rate of household savings by 0.2 percent point . Second, the frequency of earthquakes experienced by household heads does not have significant long-term effects on levels of household disposable income, but does have significant positive effects on levels of household consumption. Third, an increase in the frequency of earthquakes experienced by household heads leads to an increase in household hedonic consumption (such as the consumption of cultural entertainment, non-essential health care, cosmetology, and luxury goods), but has no effect on non-hedonic consumption. Fourth, several robustness checks are carried out (e.g., controlling for the frequency of earthquakes when household heads were 7 years old and controlling for the experience of earthquakes with an M_L > 6) on subsamples that did not migrate from a seismic zone, and the above conclusions remain valid. Fifth, empirical evidence from migrant workers suggests that the endogeneity problem in the empirical models does not affect the conclusions.
This paper contributes to academic research and policymaking in China. In terms of academic research, this paper's first contribution is to the literature on the effect of earthquakes on household consumption and saving patterns, as it provides empirical evidence from urban China. It also provides evidence from economic research to the psychology literature, revealing the effect of the risk of earthquake-associated death on individual consumption behaviors; this has implications for the optimal location of companies that provide hedonic products or services. Second, this paper helps to explain the savings rates in China from the perspective of consumption behavior shaped by earthquakes.
In terms of policymaking, this paper's first contribution is to highlight a way to promote domestic consumption. China has a very high household savings rate compared with other developing and developed economies, and the Chinese government consistently endeavors to promote domestic consumption to boost economic growth. In recent years, the Chinese government has emphasized the need for reform on the demand side and on the supply side to better match both sides and thus improve economic growth. China has a huge domestic market, which serves as a substitute foreign market, and this suggests that improving domestic demand rather than export demand will be fruitful, especially as the China-US trade relationship is not healthy. Thus, this paper indicates that policies aimed at promoting domestic consumption should focus on reshaping consumption habits, i.e., encouraging spending on cultural entertainment, non-essential health care, and other hedonic consumption. Second, the coronavirus disease 2019 (COVID-19) pandemic is also a natural disaster, and it warrants more academic research. The conclusions from this paper suggest ways to determine the effects of the COVID-19 pandemic on household consumption and savings rates. The findings of this paper also suggest that new COVID-19-associated habits, such as mask-wearing and the frequent use of hand disinfectants, will have long-term effects on consumption habits and household savings rates.

Globally, the last four decades have been characterized by a continuous decline in the labor income share, which has attracted the attention of many scholars. However, using a sample of China's listed firms, we observe that China's labor income share did not decline significantly after the 2008 financial crisis and even showed an upward trend. We also observe surges in the rapid deepening of the financialization of nonfinancial firms in China during the same period. Intuitively, we find a positive link between firms' financialization and labor income share after the crisis. This raises the question of whether the newly emerging and rapidly spreading financialization of firms in China may be an important reason for the growth of labor income share after 2010. If so, what is the mechanism？ Is it sustainable？ These are the questions we try to answer.
Using a sample of China's listed firms from the 2007 to 2017 period, we investigate the relationship between the financialization of Chinese listed firms and their labor income share. We find that the financialization of Chinese listed firms has a positive effect on their labor share, which is inconsistent with the findings of a negative correlation between the two in studies using samples of firms in developed countries.
We argue that the spillover effect of financialization on workers' wages and its inhibition of productivity is the explanation for our results. The results of our mediation analysis are as follows. Financialization has a positive spillover on employees' income (i.e., the profit spillover effect); however, it also inhibits labor productivity (i.e., the technology inhibitory effect). These two channels can help explain the positive relationship between financialization and labor share in China. Our analysis of heterogeneous samples shows that the positive effect of firms' financialization on labor share is especially dominant among firms from areas with higher minimum wage and more skilled workers.
Further analysis finds that the classic principal-agent framework fails to explain financialization in China. Instead, the role of financialization in promoting labor share stems from the excess returns in China's financial market. Financialization is a rational choice for firms when there are excess returns in the financial market, but it also damages productivity. Therefore, the positive relationship between financialization and labor share is unsustainable. In the long run, profit-oriented financialization in China may not only damage the actual income of workers but also damage the industrial foundation, and thus it may be referred to as a “sweet poison.”
We make three contributions to the literature. First, we extend the research on the relationship between financialization and labor income share to the micro level. Unlike others who have used samples of firms from developed countries, we, focusing on China, propose and identify a “profit spillover” effect and a “technology inhibition” effect of firms' financialization on labor income share. Second, previous studies of firms' financialization have paid insufficient attention to endogeneity problems. In this paper, we try to overcome this problem by using the frontier synthetic instrumental variable method and the event method to confirm the causal relationship between the financialization of firms and labor share. Third, breaking out of the classic principal-agent framework, we identify “another style” of firms financialization, which occurs when there are excess returns in the financial field. This insight not only helps to improve the understanding of firms' financialization but also has important practical value.
We conclude that the pulling effect of firms' financialization on China's labor income share is based on the specific condition of excess returns, so it is not only unsustainable, but it may also result in long-term damage. Thus, the economic trend “from the real to the virtual” caused by the rapid development of firms' financialization must be guarded against..

Savings and consumption are critical topics in household financial decision-making research. A suitable and reasonable balance of savings and consumption in a person's life, known as consumption smoothing, can enhance a person's utilities and happiness. Rapid developments in financial technology have decreased the costs of individual participation in financial markets, and thus increased the heterogeneity of participants. Financial literacy plays an increasingly important role in financial decision-making, as financial products are constantly being enriched.
There is no consensus on the impact of financial literacy on household savings rates. Lusardi (2008) and Jappelli and Padula (2013) argue that improvements in financial literacy may encourage families to engage in financial planning, avoid excessive consumption, and increase savings. In contrast, Jappelli and Padula (2017) and Song et al. (2019) argue that financial literacy promotes consumption. These contradictory results occur due to the researchers' focus on different aspects and characteristics of financial literacy, which play different roles in household savings.
We use data from the China Consumer Finance Status and Investor Education Survey conducted by the China Financial Research Center of Tsinghua University in 2010 and 2011 to examine the relationship between financial literacy and the household savings rate. We use instrumental variables to mitigate endogeneity concerns and explore the mechanism that links financial literacy to household savings, especially the role of financial planning and borrowing constraints.
We find that financial literacy plays a significant role in household decisions about savings and consumption, and that the relationship between financial literacy and the household savings rate has an inverted U-shape. Financial literacy is positively correlated with financial planning, but negatively correlated with borrowing constraints. When financial sophistication improves, households that engage in financial planning try to make sure the accessible of affluent asset. When financial literacy surpasses a certain threshold, the role of financial planning in restraining consumption is weakened and its role in asset allocation is enhanced. Higher financing capacity helps households reduce future risks, thus the savings rate gradually declines. We further reveal that the inverted U-shaped relationship between financial literacy and savings rates does not mean that households with high levels of financial literacy are more likely to have insufficient savings or engage in excessive consumption. We demonstrate that families with higher financial literacy are more likely to maintain stable savings, and have a low probability of living hand-to-mouth. When the family's financial literacy improves, the increase in financial planning is less likely to have the effect of reducing consumption and is more likely to increase the optimal allocation of assets. That is, the focus of such families' financial planning shifts from increasing the savings rate to the preservation and appreciation of savings.
We make two main contributions. First, we clarify the relationship between financial literacy and the household savings rate and identify the mechanism that links them. Rising levels of financial literacy not only enhance financial planning but also reduce borrowing constraints. The influence of these two factors on the household savings rate varies with the level of financial literacy, which explains the inverted U-shaped relationship between financial literacy and the household savings rate. Second, we identify the causes of different household savings rates. Households with low savings rate can be divided into two types. The first type consists of families with low levels of financial literacy. Such families lack financial awareness and have higher borrowing constraints, making it difficult for them to accumulate savings. The second type consists of households with higher levels of financial literacy. High-level households have more stable savings, better liquidity, and more diversified asset allocation. Accordingly, low savings rate in the first type of families require close attention. Distinguishing the causes of differences in the household savings rate is of great significance for improving residents' welfare and enhancing the pertinence of financial education policies.

Rapid economic growth has led to an increase in residents' wealth, and how people dispose of their wealth has become an increasingly important research topic. In recent years, the online celebrity economy has developed rapidly, and tipping live stream performers, a new wealth disposal method, has attracted attention. What motivates audiences to tip online celebrities？ What are the rules of audience tipping behavior？ This research is quite important, because a better understanding of tipping behavior is necessary to guide the healthy development of this industry. On the one hand, tipping plays an important role in the online celebrity economy, so exploring the influencing factors behind tipping is conducive to the sustainable development of the online celebrity economy. On the other hand, the online celebrity economy also appears some chaos, so the study of tipping behavior can provide theoretical support for the formulation of regulatory rules. However, a lack of data has limited research on this topic.
This study uses a unique dataset from five multiple-channel network (MCN) agencies to examine this issue. The dataset from these five MCN agencies consists of panel data from 2019 on the income and duration of each live stream of 41 online celebrities who play the same game. Two main findings are made. First, the entertainment accompany of online celebrities increases both the speed of accrual and the amount of the celebrities' income. In other words, longer live streams generate higher incomes. The intensity of tipping also increases with the length of the live stream. Thus, the entertainment accompany of online celebrities satisfies the spiritual needs of the audience, making the audience more likely to tip. In the analysis, the influence of the “star-making” activities of MCN agencies is eliminated by deleting the most popular online celebrities to test the robustness of the conclusion. Second, there is a significant positive correlation between head-tippers and non-head-tippers. That is, there is a herding effect in audiences' tipping behavior. To eliminate the concern of a false regression, the live experience of online celebrities is used as a heterogeneity test.
The findings partially explain the rapid development of the online celebrity industry; the interactions between celebrities and audiences and between audience members jointly promote the rapid growth of the online celebrity economy. As companionship encourages audience members to tip, celebrities can increase their income by increasing the duration of their live streams. Furthermore, the tipping of head tippers influences that of non-head tippers and vice versa, allowing the celebrities' income to continue to grow. Therefore, the online celebrity economy demonstrates characteristics of the “Matthew Effect.”
This study makes several contributions to the literature. First, it adopts a micro-research perspective on the factors that influence online tipping, which will contribute to future research on the online celebrity economy. Second, this study is one of the first to use the income data of online celebrities. The unique and rigorous dataset obtained from MCN agencies is not only the basis for credible conclusions, but it also provides a basic framework for future research on the online celebrity economy. Third, it separately examines the tipping behavior of head tippers and non-head tippers, verifying the existence of the herding effect. Finally, this study provides new empirical evidence for the Matthew Effect.
Due to the limited number and dimensions of cooperation samples, a detailed exploration of the online celebrity economy is not provided in this study, leaving some problems for future research. For example, the dataset does not include information on each audience member's tipping behavior, making it impossible to analyze audience members' motivations in detail. Furthermore, there are many types of online celebrities and this study does not consider the factors that affect the income of online celebrities in other fields. Finally, different platforms may have different share ratios and platform rules, creating strong heterogeneity in the relationships between viewers and streamers on different platforms. Although it does not address the above issues, this study begins the development of principles for understanding the new economic model represented by the online celebrity economy and provides a reference for institutions seeking to guide and regulate such economic activities, ensuring their healthy development.

The increasingly marketized labor market in China leads to more frequent job-hopping, imposing higher unemployment risk on employees. This trend makes unemployment insurance more and more important. Unemployment insurance is a crucial labor protection policy. It provides unemployed people with the means to meet their basic needs and keeps society fair and stable. Although unemployment insurance is a positive benefit for individual employees and society, how it affects employers is still unclear. We investigate the impact of unemployment insurance on firms' financial leverage.
Recent studies show that labor and leverage are closely related, but most of these studies focus on U.S. firms. The labor market in the U.S. is quite different from that in China. How labor factors affect firms' leverage in China is still unclear. In theory, unemployment insurance can have both positive and negative impacts on leverage. First, increases in unemployment insurance may lead to lower leverage. As higher unemployment insurance can compensate employees when they lose their jobs, the employees are less sensitive to unemployment risk, thus they require less risk premium and firms' labor costs are reduced. When firms have more free cash flows and revenue, they may use internal funding to replace debt financing and even repay debt, which leads to lower levels of leverage. We call this channel the “labor cost channel.” Second, higher unemployment insurance lead to fewer labor costs. Most labor costs are fixed costs, so lower labor costs result in lower operating leverage. The managers can choose higher financial leverage when the operating leverage decreases, thus leading to a positive relationship between unemployment insurance and financial leverage. We call this channel the “operating leverage channel”. Third, Agrawal and Matsa (2013) find that firms' conservative financial policies can partially eliminate employees' unemployment risk. When unemployment insurance increase, employees are more tolerant of unemployment risk, so firms can take higher leverage. We call this channel the “bargaining channel”.
Using Chinese public firms' data from 2009 to 2019, we find that a 1% increase in unemployment insurance, on average, leads to a 0.021～0.38 percent point decrease in firms' financial leverage. Then, we test the labor cost channel. We find that unemployment insurance are negatively related to employees' wages, especially non-executive employees' wages. Lower employees' wages are associated with lower leverage, less debt financing, more internal financing, and a higher probability of repaying debt. These results are consistent with the labor cost channel. Further tests show that this effect is more pronounced in provinces with high unemployment rates because the employees in these areas are under larger unemployment risk; this effect is also more pronounced in SOEs because the overindebtedness problem is severe in SOEs. We also find that unemployment insurance have a significant negative impact on firms' long-term debt ratio but no impact on their short-term debt ratio.
We conduct several robustness checks. First, to address the potential endogeneity problem, we respectively use the Social Insurance Law enacted in 2011 and the Guidance on Adjusting Unemployment Insurance Standard enacted in 2017 as natural experiments and conduct both difference-in-differences estimations and instrumental variable regressions. All of the results are consistent with the main result. Then, we address the multicollinearity problem caused by the high correlation between unemploymentand minimum wages. Moreover, we try alternative specifications, address the potential impact of investment, and use alternative sample periods. The main result holds for all of these robustness tests.
We make the following contributions to the literature. First, we contribute to the understanding of Chinese labor and finance. The labor and finance literature has recently attracted scholarly attention, but few studies use Chinese data. We fill this gap. Second, we contribute to the research on Chinese unemployment insurance policies. Most current papers on unemployment insurance policies are from the perspectives of individuals, industries, or regions. In contrast, we investigate unemployment insurance from the firm's perspective. Third, our findings add to the literature on capital structure.
This paper has implications for policy makers. Our results suggest that higher unemployment insurancecan lower firms' leverage, indicating that more supportive unemployment insurance policies not only benefit employees but also firms and society.

Legal protection is an effective method for encouraging large shareholders to share benefits with small and medium shareholders. In countries where laws are incomplete, mandatory dividend policies offset the deficiencies of inadequate legal protection. Nevertheless, mandatory dividend policies have only been adopted in a few countries, including Brazil and Chile, and there are few studies of these regimes. Chinese regulatory departments have offered guidance to listed companies in terms of dividend payout since 2001. In that year, there was a significant increase in the number of companies paying dividends, but in many cases only meager dividends were paid in response to the regulatory policies. To increase the dividend payout ratio, in 2006, China's regulatory departments directly restricted dividend payout ratios and linked them to refinancing. The Decisions on Amending Some Provisions on Cash Dividends by Listed Companies (hereinafter referred to as the “Decisions”) was promulgated in 2008, and it made additional specifications to dividend payout modes. It is noteworthy that the Decisions highlighted the disclosure of information about dividend payouts. Thereafter, in 2012, the regulatory departments further improved the dividend rules, formulating fairly characteristic dividend payout regulatory rules, which are called semi-mandatory dividend policies in academic papers.
The implementation of semi-mandatory dividend policies has not resulted in the ideal division of dividends. The literature shows that semi-mandatory dividend policies may decrease the financial flexibility of growth companies and have adverse effects on these companies. Some studies suggest that semi-mandatory dividend policies have hardly any effect on “mean” companies' distribution of cash dividends, while forcing high growth companies that need refinancing to distribute cash dividends. As significant “negative incentives” for companies with high cash dividends, these dividend policies have even led to a certain decrease in the overall cash payout ratio. In addition, they have other unexpected adverse effects, for example tax costs. Most research focuses on regulatory costs and generally confirms the so-called regulatory “paradox.”
These studies of semi-mandatory dividend policies adopt the perspective of regulatory costs and ignore an important issue: semi-mandatory dividend policies may also create regulatory benefits. In our opinion, these policies constitute a mechanism of profit sharing between shareholders and are beneficial because they help investors to develop stable expectations about dividends and thus realize governance “premiums.”
This paper uses the new regulatory policies in 2008 as a natural experiment. It evaluates the economic consequences of semi-mandatory dividend policies from the perspective of their governance effects. It finds that these policies significantly reduce the equity costs of corporations, which is inconsistent with the findings in the literature that the policies result in a regulatory “paradox.” Further analyses show that the effect of semi-mandatory dividend policies is stronger in companies with substantial agency conflicts. In addition, this paper examines the limitations of semi-mandatory dividend policies. It finds that the governance effects of semi-mandatory dividends are not evident in companies with low-quality accounting information or companies that are subject to strong financing constraints.
The contributions of this paper are as follows. First, the economic consequences of semi-mandatory dividend policies are evaluated from the perspective of governance “premiums”, which enriches the literature about these policies. Second, this paper assesses the effects of semi-mandatory dividend policies on equity costs using the difference-in-differences method, making the findings of this paper robust. Third, the findings of this paper may be used as references for modifying and improving the regulatory policies for semi-mandatory dividend payouts.

Due to asymmetric information, trading costs, buy and sell constraints, lack of short-sales mechanisms, and exogenous shocks, the effects of market frictions on stock returns are more serious in China's A-share stock market than in developed foreign stock markets. Therefore, it is reasonable to ask how market frictions affect the pricing effect of idiosyncratic risks in China. In practice, answering this question would support the improvement and development of the capital market in China and help investors construct reasonable investment strategies. The question also suggests a new theoretical perspective: using market frictions to explain market anomalies (e.g., the idiosyncratic volatility puzzle and idiosyncratic skewness premium).
Many studies of non-Chinese markets (e.g., Mitton and Vorkink, 2007; Barberis and Huang, 2008; Bali and Cakici, 2008) use risk preferences and liquidity to explain the idiosyncratic volatility puzzle. However, studies show that there is a negative relationship between idiosyncratic risk and stock return in the Chinese stock market. Heterogeneous belief (e.g., Zuo et al., 2011; Long et al., 2018), gambling preferences (Zheng et al., 2013), and limited arbitrage (Yu et al., 2017; Gu et al., 2018) contribute to this negative relationship (puzzle). However, studies of both foreign and domestic markets ignore the effects of market friction.
We attempt to investigate the pricing effects of various dimensions of market friction and explore the mechanism through which pricing factor affects idiosyncratic risk. Our samples are drawn from the main board of China's A-share stock market for the 2001 to 2015 period. We first introduce continuous and discrete market friction variables to represent the dimensions of information asymmetry, trading costs, price shocks, price limit constraints, short-selling constraints, future trading constraints, and exogenous shocks. Second, the idiosyncratic volatility and idiosyncratic skewness variables are derived from a three-factor regression and five-factor regression, respectively. Then, they are used in a Fama-MacBeth cross-sectional regression to test the pricing effects and how these effects influence idiosyncratic risk premiums. We try to discuss the effects of the market friction factors on idiosyncratic risk premiums via liquidity channels. Finally, we use a weighted market friction index in a robustness test of the empirical results and conduct a portfolio analysis to infer the characteristics of idiosyncratic risk premiums under different market frictions.
Empirical studies indicate that the idiosyncratic risk factors, including idiosyncratic volatility, idiosyncratic skewness, and market frictions, have significant premiums. Market frictions enhance idiosyncratic volatility via decreased liquidity in the form of trading time, trading frequency, trading number, trading demand, and trading speed. Market frictions weakly influence idiosyncratic skewness. We also find that the absolute returns of portfolio strategies based on idiosyncratic risk factors outweigh those of CAPM, the three-factor model, and the five-factor model. Furthermore, the returns of portfolio strategies based on idiosyncratic risk factors are impacted by market frictions, which confirms the findings of the regressions.
We make two contributions to the literature. First, we partially explain the effect of market frictions on idiosyncratic volatility and to identify the driving mechanisms as stock liquidity (trading time cost, trading frequency, trading hours, trading inclination, and trading speed), although the effect of the market frictions on idiosyncratic skewness is relatively weak. Second, we find that portfolios constructed using idiosyncratic risk variables have higher absolute returns than the CAPM, three-factor, and five-factor portfolios. As a result of market frictions, the absolute return of a portfolio based on idiosyncratic volatility shrinks. The findings indicate that market liquidity is indispensable to avoid market crashes when managing systematic and contagious risks from international markets. It is also necessary to control for the spread of liquidity, and we should be cautious in assessing the individual stock risks incurred by the overflow of liquidity. In particular, it is necessary to develop policies for directional liquidity injection and for differentiating capital costs. Additionally, our work can be extended to study abnormal types of market friction, such as global public health crises and climate-related shocks.