Good Regulation and Public Policies Evaluation: selected literature
The United States Department of Justice (2020)
Justice Department Releases Report On Modernizing The Administrative Procedure Act
The Justice Department released a report today on the need for Congress to update and improve the Administrative Procedure Act (APA), the 74-year-old statute setting forth the procedures agencies must follow when regulating individuals, businesses, non-profits, and state and local government entities. The report, entitled Modernizing the Administrative Procedure Act, discusses how the administrative state has developed in ways not foreseen by the APA in 1946, how the APA might be legislatively improved, and how this Administration’s improvements to agencies’ regulatory processes could inform modernizing the APA. The Justice Department, which significantly shaped the original APA, hopes that the ideas and insights discussed in the report will encourage and inform much needed action by Congress to modernize the APA. The report released today is based on a summit held at the Justice Department on December 6, 2019. The summit brought together leading regulatory practitioners, policymakers, and scholars to discuss how best to reform the APA, which remains largely unchanged since its enactment in 1946. These experts offered a variety of ideas, from a variety of perspectives, on how Congress could reform the APA so that regulation better serves the needs of the American people. “This report aims to disseminate the many good ideas for modernizing the APA offered by participants in the summit,” said Deputy Attorney General Jeff Rosen. “The Justice Department is eager to build on the many improvements the Trump Administration has already made to the regulatory process by working with leaders in Congress to modernize the APA.” “This important report contributes to the ongoing dialogue about how to make the American administrative system less burdensome, more accountable to the people, and more respectful of the rights of Americans,” said Paul Ray, Administrator of the White House Office of Information and Regulatory Affairs. “It follows on a number of critical reforms by President Trump and is essential reading for anyone who shares a commitment to vindicating the principles of limited, accountable government and the rule of law in today’s world.”
Big Data and Regulation (selected literature)
Coglianese C. (2020)
Deploying Machine Learning for a Sustainable Future
To meet the environmental challenges of a warming planet and an increasingly complex, high techeconomy, 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 environmental agencies will need to surmount if they are to take full advantage of big data and predictive analytics. First, agencies must invest in upgrading their information technology infrastructure to take advantage of computational advances. Relatively modest technology investments, if made wisely, could support the use of algorithmic tools that could yield substantial savings in other administrative costs. Second, agencies will need to confront emerging concerns about privacy, fairness, and transparency associated with its reliance on Big Data and algorithmic analyses. Third, government agencies will need to strengthen their human capital so that they have the personnel who understand how to use machine learning responsibly. Finally, to work well, algorithms will need clearly defined objectives. Environmental officials will need to continue to engage with elected officials, members of the public, environmental groups, and industry representatives to forge clarity and consistency over how various risk and regulatory objectives should be specified in machine learning tools. Overall, with thoughtful planning, adequate resources, and responsible management, governments should be able to overcome the obstacles that stand in the way of the use of artificial intelligence to improve environmental sustainability. If policy makers and the public will recognize the need for smarter governance, they can then start to tackle obstacles that stand in its way and better position society for a more sustainable future.
Regulation and Covid-19
Zhoudan Xie (2020)
Regulation during COVID-19 News Sentiment Improved, While Uncertainty Remains
Scholars have identified various regulatory barriers hampering responses to the COVID-19 pandemic. For example, the regulatory approval required for drugs and medical devices has created “bottlenecks” for expanding the capacity of virus testing, ambiguous and often changing regulations “have served as hindrances” to the increasing use of telehealth, and patients have limited access to mobile narcotic treatment due to regulatory bans. Do these criticisms reflect the public’s opinion toward regulation, and how did average public sentiment evolve with the spread of COVID-19? This article explores these questions by presenting a text-based sentiment analysis of news articles related to COVID-19 and regulation. The analysis shows that the expression about regulation in the COVID-related news was negative in most days during the beginning of the virus outbreak, but it started to improve in mid-March. The improvement may suggest increased public confidence in regulatory responses to the pandemic, as the government started to take the virus more seriously and regulatory agencies started to issue temporary relaxations of regulations. However, the level of uncertainty expressed in the news shows no signs of diminishing, indicating persistent uncertainty surrounding regulation in the time of COVID-19. Further topic modeling of news articles suggests that sentiment and uncertainty vary across different regulatory issues. News covering quarantine and reopening, legislation (other than the stimulus bill), and testing and treatment revealed the most negative sentiment, and uncertainty was relatively high regarding testing and treatment, workplace safety, banking and lending, and oil prices.