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Corporate Sustainability, Capital Markets, and ESG Performance

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Individual Behaviors and Technologies for Financial Innovations

Abstract

This chapter discusses associations between the financial profile of a firm and superior environmental, social, and governance (ESG) performance, considering firms from Brazil, Russia, India, China, and South Africa (the so-called BRICS countries). In particular, the study analyzes ESG performance in sensitive industries, i.e., those subject to systematic social taboos, moral debates, and political pressures and those that are more likely to cause social and environmental damage. We applied linear regressions with a data panel collected from 365 listed companies between 2010 and 2012. Our results suggest the market capitalization as the main predictor of ESG performance. In general, larger companies have higher levels of performance. We also found that companies in sensitive industries present superior environmental performance even when controlling for size and country. Our conclusions provide insights for future studies around ESG performance.

Portions of this chapter appeared in the 2017 paper “Sensitive industries produce better ESG performance: Evidence from emerging markets,” Journal of Cleaner Production, vol 150, pp135–147.

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Notes

  1. 1.

    While acknowledging the different terms that many practitioners and academics have coined, in this chapter, we use the terms corporate social responsibility and ESG interchangeably.

  2. 2.

    REIT is a company that owns, operates, or finances income-producing real estate. For a company to qualify as a REIT, it must meet certain regulatory guidelines. REITs often trade on major exchanges like other securities and provide investors with a liquid stake in real estate. More about REIT, please see Feng et al. (2011).

  3. 3.

    http://financial.thomsonreuters.com/en/products/data-analytics/company-data/esg-research-data.html, Sept. 2016.

  4. 4.

    In fixed effect (FE) models, the effect of each predictor variable (i.e., the slope) is assumed to be identical across all the groups, and the regression merely reports the average within-group effect. It is recommended to use FE in situations in which the interest is concentrated only in analyzing the impact of variables that vary across time. FE models focus the relationship between predictors and dependent variables within an entity, e.g., country, industry, company, or person. Each entity has its own individual characteristics that may or may not influence the predictor variables, e.g., whether a person is male or female can influence one’s opinion on a particular issue. When using FE, we assume that something within the entity/individual can affect or predispose the predictor or dependent variables, and we must control that. This is the logic behind the assumption of correlation between the entity’s error term and the predictors. FE removes the effect of these characteristics that do not vary across time, so that it is possible to evaluate the net effect of the predictors on the dependent variable. Furthermore, it is assumed that in the FE model, these characteristics that do not vary across time are unique to the individual/entity and are not correlated with other individual characteristics. It is assumed that each entity is different. Thus, the entity error term and the constant (which captures individual characteristics) should not be correlated with the others. Consequently, in cases where the error terms are correlated, FE models are inadequate, since the inferences may not be correct, which is the main reason for modeling this relation by the Hausman test. The FEs will not work well with the data that reflects minimal variation within the cluster. It is also recommended to control for time effects whenever unexpected variation, or special events, affects the dependent variable. In short, fixed-effect models are designed to analyze the causes of changes within an entity/individual (Angrist and Pischke 2009).

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Authors and Affiliations

  1. Centro Universitario Fecap, Sao Paulo, SP, Brazil

    Alexandre S. Garcia

  2. Sao Paulo School of Business Administration (FGV/EAESP), Sao Paulo, SP, Brazil

    Wesley Mendes-Da-Silva

  3. University of Texas at Austin, Austin, TX, USA

    Wesley Mendes-Da-Silva

  4. Department of Operations Management, Fundação Getulio Vargas at São Paulo (FGV/EAESP), Sao Paulo, Brazil

    Renato J. Orsato

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    Wesley Mendes-Da-Silva

  2. University of Texas at Austin, Austin, TX, USA

    Wesley Mendes-Da-Silva

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Garcia, A.S., Mendes-Da-Silva, W., Orsato, R.J. (2019). Corporate Sustainability, Capital Markets, and ESG Performance. In: Mendes-Da-Silva, W. (eds) Individual Behaviors and Technologies for Financial Innovations. Springer, Cham. https://doi.org/10.1007/978-3-319-91911-9_13

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