The Globalization of Corporate Environmental Disclosure: Accountability or Greenwashing?

Christopher  Marquis; Michael W. Toffel; Yanhua  Zhou

Article | Work In Progress (American Sociological Association blog) | March 22, 2016

The Globalization of Corporate Environmental Disclosure: Accountability or Greenwashing?

by Christopher Marquis, Michael W. Toffel and Yanhua Zhou

Abstract

This article is a layman summary of "Scrutiny, Norms, and Selective Disclosure: A Global Study of Greenwashing," published in Organization Science 27, no. 2 (March–April 2016): 483–504.

Keywords: reporting; environmental performance; civil society; Corporate Disclosure; Integrated Corporate Reporting; Corporate Social Responsibility and Impact; Civil Society or Community; Environmental Sustainability;

Format: Electronic

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Citation:

Marquis, Christopher, Michael W. Toffel, and Yanhua Zhou. "The Globalization of Corporate Environmental Disclosure: Accountability or Greenwashing?" Work In Progress (American Sociological Association blog) (March 22, 2016). (Reprinted as Environmental disclosure: corporate accountability or greenwashing?” LSE Business Review, June 9, 2016.)

The President of Harvard University is facing growing pressure from students, alumni, and other climate change activists that are urging the university to divest its multi-billion dollar endowment from fossil fuel companies. The case summarizes the arguments for and against Harvard divesting, examining past examples of Harvard’s investment decisions and the financial implications of divestment.

We study how a regulator can best allocate its limited inspection resources. We direct our analysis to a U.S. Occupational Safety and Health Administration (OSHA) inspection program that targeted dangerous establishments and allocated some inspections via random assignment. We find that inspections reduced serious injuries by an average of 9% over the following five years. We use new machine learning methods to estimate the effects of counterfactual targeting rules OSHA could have deployed. OSHA could have averted over twice as many injuries if its inspections had targeted the establishments where we predict inspections would avert the most injuries. The agency could have averted nearly as many additional injuries by targeting the establishments predicted to have the most injuries. Both of these targeting regimes would have generated over $1 billion in social value over the decade we examine. Our results demonstrate the promise, and limitations, of using machine learning to improve resource allocation. JEL Classifications: I18; L51; J38; J8.

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The Globalization of Corporate Environmental Disclosure: Accountability or Greenwashing?

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