Machine learning approaches for explaining determinants of the debt financing in heavy-polluting enterprises

Boqiang Lin () and Rui Bai

Finance Research Letters, 2022, vol. 44, issue C

Abstract: Under the background of green credit policy, more and more attention has been paid to the debt financing of high-polluting enterprises. This paper collects 224 financial and non-financial indicators in 40 listed enterprises in the mining, steel, and power industries to investigate their relationship with those measurement indicators. This paper selects the XGBoost method for feature selection to sort out the top six indicators of the combination of subsets under the condition of high dimension. The screened indicators have a good effect in predicting long-term debt. Further explanation is given based on the Shapley additive explanation value.

Keywords: Machine learning approaches; Credit policy; Business indicator (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:44:y:2022:i:c:s1544612321001756

DOI: 10.1016/j.frl.2021.102094

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