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Stewardship 2021: The Centrality Of Institutional Investor Regulation To Restoring A Fair And Sustainable American Economy, Leo E. Strine Jr. Oct 2020

Stewardship 2021: The Centrality Of Institutional Investor Regulation To Restoring A Fair And Sustainable American Economy, Leo E. Strine Jr.

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In this essay, which formed the basis for the luncheon keynote speech at the Rethinking Stewardship online conference presented by the Ira M. Millstein Center for Global Markets and Corporate Ownership at Columbia Law School and ECGI, the European Corporate Governance Institute, the essential, but not sufficient, role of regulation to promote more effective stewardship by institutional investors is discussed. To frame specific policy recommendations that align the responsibilities of institutional investors with the best interests of their human investors in sustainable wealth creation, environmental responsibility, the respectful treatment of stakeholders, and, in particular, the fair pay and treatment of …


Environmental Soft Law As A Governance Strategy, Cary Coglianese Oct 2020

Environmental Soft Law As A Governance Strategy, Cary Coglianese

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Soft law governance relies on nongovernmental institutions that establish and implement voluntary standards. Compared with traditional hard law solutions to societal and economic problems, soft law alternatives promise to be more politically feasible to establish and then easier to adapt in the face of changing circumstances. They may also seem more likely to be flexible in what they demand of targeted businesses and other entities. But can soft law actually work to solve major problems? This Article considers the value of soft law governance through the lens of three major voluntary, nongovernmental initiatives that address environmental concerns: (1) ISO 14001 …


Deploying Machine Learning For A Sustainable Future, Cary Coglianese May 2020

Deploying Machine Learning For A Sustainable Future, Cary Coglianese

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To meet the environmental challenges of a warming planet and an increasingly complex, high tech economy, government must become smarter about how it makes policies and deploys its limited resources. It specifically needs to build a robust capacity to analyze large volumes of environmental and economic data by using machine-learning algorithms to improve regulatory oversight, monitoring, and decision-making. Three challenges can be expected to drive the need for algorithmic environmental governance: more problems, less funding, and growing public demands. This paper explains why algorithmic governance will prove pivotal in meeting these challenges, but it also presents four likely obstacles that …