Most attempts to measure corporate wrongdoing rely on data and indices sold by environmental, social, and governance (ESG) data providers. Developed for investors and market players, ESG data have been widely used in academia, but so far, little research has been conducted to assess and overcome the limitations of ESG indices. In this article, we take a first step in this direction and propose using an M-quantile regression approach to develop an index of corporate wrongdoing, understood as firms' involvement in controversies over universal human rights. We apply our proposed methodology to a novel and unique hand-collected dataset of 380 large publicly-listed firms from both advanced and emerging economies, covering the period 2003–2012. We discuss the importance of these indices for managers and practitioners.
How bad is your company? Measuring corporate wrongdoing beyond the magic of ESG metrics
Fiaschi D.;Giuliani E.;Nieri F.;Salvati N.
2020-01-01
Abstract
Most attempts to measure corporate wrongdoing rely on data and indices sold by environmental, social, and governance (ESG) data providers. Developed for investors and market players, ESG data have been widely used in academia, but so far, little research has been conducted to assess and overcome the limitations of ESG indices. In this article, we take a first step in this direction and propose using an M-quantile regression approach to develop an index of corporate wrongdoing, understood as firms' involvement in controversies over universal human rights. We apply our proposed methodology to a novel and unique hand-collected dataset of 380 large publicly-listed firms from both advanced and emerging economies, covering the period 2003–2012. We discuss the importance of these indices for managers and practitioners.File | Dimensione | Formato | |
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