In the context of the commitment to peak carbon emissions by 2030, specific sectors in China should take responsibility to change their energy consumption patterns. In China and across the globe, the construction sector is a major source of carbon dioxide emissions, as well as an indicator of economic growth and structural transformation. In this study, we examine panel data for 30 provinces or regions from 2008 to 2019 to dissect which macro-factors contribute to growth in carbon emissions, and which will lead to carbon emission reductions. Derived by the entropy method, the Green Finance Index is a comprehensive environmental regulation index related to reduction in emissions in each province. It presents an N shape for construction emissions, and provinces are currently striving to cross the first inflection point, which will help to curb emissions. Judging from the combined effects of this and other structural factors, the Green Finance Index can promote the decarbonization of production by playing the role of guiding and screening capital allocation. Population expansion, income levels, and financial development initially stimulate demand for construction, but their effects eventually level off. This paper can serve as a reference for developing countries that are experiencing industrialization and urbanization processes and handling gas discharge pressure at the same time.

This article constructs a behavioral financial model that provides feedback on both historical prices and company fundamentals without considering asset liquidation to discuss the long-term impact of investor sentiment and feedback trading on asset price fluctuations. The research conclusion shows that the abnormal volatility of asset prices is captured by the value effect, the cognitive bias effect, the sentiment shock effect, and the trading inductive effect. The value effect is the volatility of asset prices that is completely determined by fundamental factors; the higher the degree of cyclical fluctuations in fundamental factors, the higher the volatility of prices. The bias effect refers to investors’ misreading of basic information and trends in asset prices; the greater the instability of emotional shocks, the greater the abnormal volatility of asset prices. The trading inductive effect is also called the Keynes effect, which reflects the role played by rational traders.