ESG Confusion and Stock Returns: Tackling the Problem of Noise
72 Pages Posted: 12 Oct 2021 Last revised: 26 Jun 2023
Date Written: October 12, 2021
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. We address this as a classical errors-in-variables problem and 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 2.3. This relative increase is stable across horizons over which stock returns are measured. In simulations, our noise-correction procedure outperforms alternative approaches such as simple averages or principal component analysis.
Keywords: measurement error, instrumental variables, sustainable investing, ESG ratings
JEL Classification: C26, G12, Q56
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