With the help of the time-varying parameter vector autoregression with stochastic volatility (TVP-SV-VAR) model and the Bayesian dynamic conditional correlational autoregressive conditional heteroscedasticity (Bayesian DCC-GARCH) model, this study analyzes the interaction mechanism and dynamic correlation among financial leverage, house price, and consumer expenditure (the survey data are collected from China’s National Bureau of Statistics from January 2000 to December 2019; the data on financial leverage and consumer expenditure are from the Wind economic database, and the price of commercial housing was calculated based on the sales volume and area of commercial housing on the official website of China’s National Bureau of Statistics). Empirical results show that an increase in financial leverage significantly increases house prices and reduces consumer expenditure, that a rise in house prices inhibits financial leverage and weakens consumer expenditure, and that an increase in consumer expenditure raises financial leverage and stimulates a rise in house prices. In addition, house price and consumer expenditure are most relevant, followed by financial leverage and consumer expenditure, and then by financial leverage and house price. Therefore, systematic analysis of dynamic correlation among the three variables has important practical significance for formulating appropriate financial policies to stabilize house prices and promote the growth of consumer expenditures. Specially, financial leverage is an important factor to hold back soaring house prices and shrinking consumer expenditure. Therefore, monetary and macroprudential policies should be used to deal with financial leverage variables in order to achieve a balanced and sustainable development of the macroeconomy in China.

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China currently is the world's largest energy consumer and carbon dioxide emitter. How to effectively control carbon dioxide emissions and promote sustainable development is indispensable for achieving the “double carbon” goal, promoting comprehensive economic transformation and upgrading, and contributing to high‐quality economic development. There is no doubt that a large amount of financial resources need to be invested in the process of encouraging sustainable development. Therefore, what is the relationship among financial development, carbon dioxide emissions and sustainable development? Can financial development facilitate sustainable development? In order to answer these two key questions, this article uses entropy weight method, fixed effect model, and panel vector autoregressive (PVAR) model to deeply explore the static and dynamic relationship among financial development, carbon dioxide emissions and sustainable development with the panel data of 30 provinces in China from 2005 to 2021. The research results show that financial development is conducive to forwarding sustainable development, and the negative impact of carbon dioxide emissions on sustainable development is also significant at present. That means financial development and carbon dioxide emissions have important impact on sustainable development. The further empirical results of PVAR model show that there are significant differences in the impact of financial development and carbon dioxide emissions on sustainable development in different periods of time. Therefore, the government should take timely measures according to the different roles played by financial development and carbon dioxide emissions at different stages to promote sustainable development.

This paper explores the dynamic relationship among bank credit, house prices and carbon dioxide emissions in China by systematically analyzing related data from January 2000 to December 2019 with the help of the time-varying parameter vector autoregression with stochastic volatility (TVP-SV-VAR) model and the Bayesian DCC-GARCH model. Empirical results show the expansion of bank credit significantly drives up house prices and increases carbon dioxide emissions in mosttimes. The rise in house prices inhibits the expansion of bank credit but increases carbon dioxide emissions and aggravates environment pollution, and that the increase in carbon dioxide is helpful to stimulate bank credit expansion and house price rise. In addition, bank credit and house prices are most relevant, followed by bank credit and carbon dioxide emissions, then by house prices and carbon dioxide emissions. Therefore, we believe that in order to stabilize skyrocketing house prices, restrain carbon dioxide emissions, and secure a stable and healthy macro-economy, the government should strengthen management of bank credit, and effectively control its total volume.