More from the Author

• Case | HBS Case Collection | August 2019 (Revised September 2019)

  Fossil Fuel Divestment

  Michael W. Toffel and Sarah Gulick

  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.

  Keywords: divestment; Higher Education; Corporate Social Responsibility and Impact; Environmental Sustainability; Weather and Climate Change; Public Opinion; Education Industry;

  Citation:

  Toffel, Michael W., and Sarah Gulick. "Fossil Fuel Divestment." Harvard Business School Case 620-026, August 2019. (Revised September 2019.)  View Details

  CiteView DetailsEducatorsPurchase

  Related

• Working Paper | HBS Working Paper Series | 2019

  Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA

  Matthew S. Johnson, David I. Levine and Michael W. Toffel

  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.

  Keywords: Government Administration; Working Conditions; Safety; Quality; Production; Analysis; Resource Allocation; Manufacturing Industry; United States;

  Citation:

  Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." Harvard Business School Working Paper, No. 20-019, August 2019.  View Details

  CiteView DetailsSSRN Read Now

  Related

• Conference Presentation | 11 Aug 2019

  Sustainability Research at the Strategy‐Supply Chain Interface

  Michael W. Toffel

  Citation:

  Toffel, Michael W. "Sustainability Research at the Strategy‐Supply Chain Interface." Paper presented at the Academy of Management Annual Meeting, Boston, MA, August 11, 2019.  View Details

  CiteView Details Read Now

  Related