An Empirical Analysis of the Impact of Carbon Disclosure on Firms' Market Value in a "Dual Carbon" Context

With the acceleration of global warming, climate change and environmental issues have become a hotspot of global concern. At present, it has become a global consensus to vigorously develop a green economy and achieve "carbon neutrality and carbon peak". In this context, as an important part of the national economy, listed companies should pay more attention to carbon emission and information disclosure to help achieve the goals of "carbon peak" and "carbon neutral". In this paper, we use a multiple linear regression model to explore the specific mechanism of the impact of carbon emission disclosure on enterprise market value. In constructing the model, we consider that factors such as asset size, operating profit margin, and cash flow ratio may affect the market value of enterprises, so we add control variables in the model and use t-test, F-test, and analysis of covariance to verify whether there is a significant difference between different groups. Descriptive statistics and Pearson's correlation coefficient were also carried out during data processing in order to observe whether there is a correlation between carbon emissions and company market value. By analysing the results of regression fitting, we find that under the background of "dual-carbon", the active disclosure of carbon emissions by enterprises can help enterprises to improve their transparency, thus enhancing the trust and recognition of consumers and investors, and thus positively affecting the market value of the enterprises, and the impact of the active disclosure of carbon emissions by enterprises with high carbon emissions is even more significant on their market value. market value is even more significant. This implies that companies should actively participate in emission reduction actions and demonstrate their action on environmental protection by proactively disclosing carbon emission information in their annual reports or CSR reports.