We employ a time-varying parameter vector autoregression (TVP-VAR) joint connectedness approach to study the dynamic risk spillover effects between cryptocurrencies and China’s financial market, further exploring the impact of cryptocurrencies on China’s financial market. Our results show that there is asymmetric risk transmission between cryptocurrencies and China’s financial market, and the risk spillover effect is very weak. Specifically, the spillover of cryptocurrencies to China’s financial market is significantly stronger than the spillover of China’s financial market to cryptocurrencies. Cryptocurrencies have a stronger spillover effect to China’s exchange rate and gold. The net spillover effect of cryptocurrencies is weakening over time. Overall, the return spillover impact of cryptocurrencies on China’s financial market is greater than the volatility spillover impact, and the degree of impact of different cryptocurrencies is heterogeneous. This study provides some reference and guidance for cross-market investment portfolios and the regulation of China’s financial market.

This paper aims to empirically explore the cyclical attributes of dynamic correlation shifts between the stock and real estate market, and the factors that influence this correlation during different periods of the economic cycle. Our research uncovers a significant structural shift in the correlation towards the end of 2012. By taking into account macroeconomic growth, regulatory policies, financial market conditions, and developments within both the stock and real estate markets, we investigate the time-varying characteristics of these factors' influence. The results highlight the pronounced cyclical asymmetry of these influential factors. Currently, the wealth effect in China's stock and real estate markets has significantly diminished, and the credit-price effect has vanished. A marked seesaw relationship is evident between the two markets. This outcome supports that various restrictions imposed on the real estate market have reduced its investment appeal.

本文的研究目的是探究数字加密货币与中国金融市场之间的关系， 并采用小波分析和溢出指数法等方法进行量化分析。经过深入研究，本文得出 以下主要结论。第一，数字加密货币和中国金融市场对外界事件的冲击反应具 有显著特征，并存在着显著的相关性和长期依赖性。不仅数字加密货币对中国 金融市场波动产生影响，中国金融市场的波动也会影响数字加密货币价格的波 动。第二，从静态和动态角度衡量溢出效应发现，数字加密货币和中国金融市 场之间存在溢出效应。在静态情况下，溢出效应并不明显，而动态情况下溢出 效应较为明显，尤其在极端经济事件中，数字加密货币与中国金融市场之间的 溢出关系会呈现极端风险溢出现象。第三，本文还考察了突发事件和政策不确 定性对总溢出关系的影响。结果显示，地缘政治风险、贸易摩擦以及美国经济 政策不确定性会加剧比特币对中国金融市场的影响，而中国经济政策不确定性 则会缓和数字加密货币对中国金融市场的影响。这些结论有助于金融机构和投 资者更好地理解和应对数字加密货币对金融市场的影响，同时也为相关政府部 门制定监管政策提供了重要参考。

The growth of digital economy and sustainable development of environment are important issues related to high-quality economic development in the new era. This paper selects the yearly data of China from 2007 to 2021, constructs the China’s Environmental Performance Index, and establishes the TVP-VAR model to investigate the dynamic time-varying relationship between digital economy growth, CO2 emissions, and sustainable development of environment in short, medium and long-term. The results show that the relationships among them are time-varying at all terms. Specifically, in first, the growth of the digital economy exerts a negative impulse on CO2 emissions, and the short-term effect is greater than the long-term effect. Secondly, there exist positive impulses between the growth of the digital economy and sustainable development of environment. And CO2 emissions has a negative impact on sustainable development of environment. Thirdly, they have same influencing tendencies at certain time points, but different impact degrees. The impact of the digital economy development on environmental sustainable development has significantly increased since the COVID-19 outbreak. Therefore, the development of digital economy can effectively reduce CO2 emissions and promote the sustainable development of the environment.

本文首先通过构建 DSGE 模型，分是否存在零利率下限约束两种情况探讨了供给和需求冲击对于宏观经济波动的影响。结果发现与不存在零利率下限约束的情况相比，当面临零利率下限约束时，由于“费雪效应”的存在会从两方面改变供给和需求冲击对一国产出、消费、劳动、通胀率和实际利率等经济变量波动的影响：一是会改变对一些变量影响的方向，二是从影响的程度来看，零利率下限约束存续的期限越长经济变量波动的幅度也越剧烈。随后我们分析了我国零利率下限约束的特征事实，认为我国自 2004 年以来先后经历了一个受零利率下限约束和不受零利率下限约束的时段，并应用时变参数模型对比分析了上述两个时段内供求冲击下我国产出等经济变量的动态响应轨迹，结果基本证实了上述理论分析的结论。最后，基于本文的分析我们也对当前国内外环境下我国以供给侧改革为主线的宏观经济政策调整提出了相关的政策建议。

This paper investigates the impact of the COVID-19 pandemic on the volatility spillover and dependence structure among the major developed and emerging stock markets. The TVP-VAR connectedness decomposition approach and R-vine copula are implemented in this research. The results of the TVP-VAR connectedness decomposition approach reveal that the volatility spillover among the major developed and emerging stock markets has been significantly strengthened by the outbreak of the COVID-19 pandemic, although it has gradually faded over time. In addition, during the pandemic, the UK, German, French and Canadian stock markets are the spillover transmitters, while the Japanese, Chinese Hong Kong, Chinese and Indian stock markets are the receivers. It is also found that the US and Brazilian stock markets have undergone role shifts after the outbreak of the COVID-19 pandemic. The results of the R-vine copula model indicate that during the pandemic, the Canadian, French, and Chinese Hong Kong stock markets are the most important financial centre in the American, European, and Asian stock markets, respectively. Furthermore, the effect of the extreme risk contagion has been strengthened by the pandemic, particularly the downside risk contagion.