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Does good ESG lead to better financial performances by firms? Machine learning and logistic regression models of public enterprises in Europe.

De Lucia, Caterina; Pazienza, Pasquale; Bartlett, Mark

Authors

Caterina De Lucia

Pasquale Pazienza



Abstract

The increasing awareness of climate change and human capital issues is shifting companies towards aspects other than traditional financial earnings. In particular, the changing behaviors towards sustainability issues of the global community and the availability of environmental, social and governance (ESG) indicators are attracting investors to socially responsible investment decisions. Furthermore, whereas the strategic importance of ESG metrics has been particularly studied for private enterprises, little attention have received public companies. To address this gap, the present work has three aims-1. To predict the accuracy of main financial indicators such as the expected Return of Equity (ROE) and Return of Assets (ROA) of public enterprises in Europe based on ESG indicators and other economic metrics; 2. To identify whether ESG initiatives affect the financial performance of public European enterprises; and 3. To discuss how ESG factors, based on the findings of aims #1 and #2, can contribute to the advancements of the current debate on Corporate Social Responsibility (CSR) policies and practices in public enterprises in Europe. To fulfil the above aims, we use a combined approach of machine learning (ML) techniques and inferential (i.e., ordered logistic regression) model. The former predicts the accuracy of ROE and ROA on several ESG and other economic metrics and fulfils aim #1. The latter is used to test whether any causal relationships between ESG investment decisions and ROA and ROE exist and, whether these relationships exist, to assess their magnitude. The inferential analysis fulfils aim #2. Main findings suggest that ML accurately predicts ROA and ROE and indicate, through the ordered logistic regression model, the existence of a positive relationship between ESG practices and the financial indicators. In addition, the existing relationship appears more evident when companies invest in environmental innovation, employment productivity and diversity and equal opportunity policies. As a result, to fulfil aim #3 useful policy insights are advised on these issues to strengthen CSR strategies and sustainable development practices in European public enterprises.

Citation

DE LUCIA, C., PAZIENZA, P. and BARTLETT, M. 2020. Does good ESG lead to better financial performances by firms? Machine learning and logistics regression models of public enterprises in Europe. Sustainability [online], 12(13), article ID 5317. Available from: https://doi.org/10.3390/su12135317

Journal Article Type Article
Acceptance Date Jun 26, 2020
Online Publication Date Jul 1, 2020
Publication Date Jul 1, 2020
Deposit Date Jul 30, 2020
Publicly Available Date Mar 29, 2024
Journal Sustainability
Electronic ISSN 2071-1050
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 12
Issue 13
Article Number 5317
DOI https://doi.org/10.3390/su12135317
Keywords ESG; Machine learning; Logistic regression; Return of equity; Return of assets; Public enterprise
Public URL https://rgu-repository.worktribe.com/output/954022

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