Corporate environmental protection investment is crucial for reducing pollution levels and controlling harmful substance emissions. We examine the relationship between corporate environmental protection investment and debt financing costs, utilizing a sample of A-share listed companies in China from 2011 to 2020. We find that debt financing costs are negatively related to corporate environmental protection investment. Green technology innovation and ESG performance are the main channels. Environmental regulations, air quality, and green finance impact the interplay between corporate environmental protection investment and debt financing costs. Moreover, our heterogeneity analysis underscores that enterprises facing looser financing constraints and low levels of pollution are more likely to mitigate debt financing costs by investing in environmental protection. The conclusion provides policy implications for guiding enterprises to consider environmental investment as a long-term strategy and provides a theoretical foundation for the government to enhance its guiding role.

This study extends the proximal support vector machine (PSVM) to the ordinal regression problems by proposing a proximal ordinal support vector regression (POSVR) based on the fixed margin strategy. The proposed POSVR is applied to the multi-class classification problems with ordered discrete outcome events under the assumption that the ordered classes can be separated by a group of parallel decision hyperplanes. POSVR can be transformed into a linear equation system and solved conveniently. The experimental results on the benchmark datasets and a real-world recovery rate dataset of US corporate bonds demonstrate that POSVR achieves better performance in terms of cross-validation outputs on the training set and out-of-sample prediction on the testing set. It implies that the proposed POSVR is a promising technique for credit risk modeling and other areas in ordinal regression problems.