ESG Confusion and Stock Returns: Tackling the Problem of Noise

Abstract

Existing measures of ESG (environmental, social, and governance) performance ESG ratings are noisy and, therefore, standard regression estimates of the effect of ESG performance on stock returns are biased. Addressing this as a classical errors-in-variables problem, we develop a noise-correction procedure in which we instrument ESG ratings with ratings of other ESG rating agencies. With this procedure, the median increase in the regression coefficients is a factor of 2.1. The results are similar when we use accounting profitability measures as outcome variables. In simulations, our noise-correction procedure outperforms alternative approaches such as simple averages or principal component analysis.