Understanding CSR Champions: A Machine Learning Approach
Alona Bilokha, Mingying Cheng, Mengchuan Fu, Iftekhar Hasan
Annals of Operations Research,
forthcoming
Abstract
In this paper, we study champions of corporate social responsibility (CSR) performance among the U.S. publicly traded firms and their common characteristics by utilizing machine learning algorithms to identify predictors of firms’ CSR activity. We contribute to the CSR and leadership determinants literature by introducing the first comprehensive framework for analyzing the factors associated with corporate engagement with socially responsible behaviors by grouping all relevant predictors into four broad categories: corporate governance, managerial incentives, leadership, and firm characteristics. We find that strong corporate governance characteristics, as manifested in board member heterogeneity and managerial incentives, are the top predictors of CSR performance. Our results suggest policy implications for providing incentives and fostering characteristics conducive to firms “doing good.”
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Corporate Social Responsibility and Profit Shifting
Iftekhar Hasan, Panagiotis I. Karavitis, Pantelis Kazakis, Woon Sau Leung
European Accounting Review,
No. 1,
2025
Abstract
This paper examines the relation between corporate social responsibility (CSR) performance and tax–motivated income shifting. Using a profit–shifting measure estimated from multinational enterprises (MNEs) data, we find that parent firms with higher CSR scores shift significantly more profits to their low-tax foreign subsidiaries. Overall, our evidence suggests that MNEs engaging in CSR activities acquire legitimacy and moral capital that temper negative responses by stakeholders and thus have greater scope and chance to engage in unethical profit-shifting activities, consistent with the legitimacy theory.
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Discrimination in Universal Social Programs? A Nationwide Field Experiment on Access to Child Care
Henning Hermes, Philipp Lergetporer, Fabian Mierisch, Frauke Peter, Simon Wiederhold
IWH Discussion Papers,
No. 12,
2023
Abstract
Although explicit discrimination in access to social programs is typically prohibited, more subtle forms of discrimination prior to the formal application process may still exist. Unveiling this phenomenon, we provide the first causal evidence of discrimination against migrants seeking child care. We send emails from fictitious parents to > 18, 000 early child care centers across Germany, inquiring about slot availability and application procedures. Randomly varying names to signal migration background, we find that migrants receive 4.4 percentage points fewer responses. Replies to migrants contain fewer slot offers, provide less helpful content, and are less encouraging. Exploring mechanisms using three additional treatments, we show that discrimination is stronger against migrant boys. This finding suggests that anticipated higher effort required for migrants partly drives discrimination, which is also supported by additional survey and administrative data. Our results highlight that difficult-to-detect discrimination in the pre-application phase could hinder migrants’ access to universal social programs.
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