How Bad Is Your Company? Measuring Corporate Wrongdoing Beyond the Magic of ESG Metrics

How bad is your company?

Davide Fiaschi, Elisa Giuliani, Federica Nieri, and Nicola Salvati address the gap in measuring corporate misconduct by proposing a comprehensive methodology going beyond usual issue-specific measures or ESG metrics

They introduce a M-quantile regression methodology to create an index of corporate wrongdoing, focusing on firms' involvement in human rights controversies accounting for media exposure, firm scale, and industry specifics.

The analysis is based on a dataset of 380 large publicly-listed firms from both advanced and emerging economies over the period 2003-2012 and shows:

• Variables such as firm's media exposure, home and host countries voices and accountability, firm size, and firm internationalisation are statistically significant in explaining corporate wrongdoing.
• Companies with higher media exposure tend to have higher wrongdoing indices, suggesting that visibility influences the reporting and perception of corporate misconduct.
• There is a high persistence in corporate wrongdoing at the extremes (innocent and evil firms), while firms in the middle category (ambivalent) display higher intergroup mobility.
• Mainstream conditional indices show significant divergence in their results with unconditional ones because of different treatments of factors such as media exposure, firm scale, and industry specifics.

The approach outlined in this article addresses the limitations of existing ESG metrics by focusing on transparency, replicability, and reliability and limiting temporal inconsistencies, over-aggregation, and arbitrary scoring methods.

The M-quantile regression approach, while innovative, may still face challenges in terms of data availability and the still subjective assessment human rights controversies.