Governments are increasingly adopting behavioral science techniques for changing individual behavior in pursuit of policy objectives. The types of “nudge” interventions that governments are now adopting alter people’s decisions without coercion or significant changes to economic incentives. We calculated ratios of impact to cost for nudge interventions and for traditional policy tools, such as tax incentives and other financial inducements, and we found that nudge interventions often compare favorably with traditional interventions. We conclude that nudging is a valuable approach that should be used more often in conjunction with traditional policies, but more calculations are needed to determine the relative effectiveness of nudging.
Research in behavioral public finance has blossomed in recent years, producing diverse empirical and theoretical insights. This article develops a single framework with which to understand these advances. Rather than drawing out the consequences of specific psychological assumptions, the framework takes a reducedform approach to behavioral modeling. It emphasizes the difference between decision and experienced utility that underlies most behavioral models. We use this framework to examine the behavioral implications for canonical public finance problems involving the provision of social insurance, commodity taxation, and correcting externalities. We show how deeper principles undergird much work in this area and that many insights are not specific to a single psychological assumption.
In response, governments are increasingly interested in using behavioral insights as a supplement to or replacement for traditional economic levers, such as incentives, to shape the behavior of citizens and government personnel to promote public priorities. A number of governments around the world have formed nudge units: teams of behavioral science experts tasked with designing behavioral interventions that have the potential to encourage desirable behavior without restricting choice, testing those interventions rapidly and inexpensively, and then widely implementing the strategies that prove most effective. The United Kingdom established a nudge unit in 2010 and was soon followed by other countries, including Australia, Germany, The Netherlands, and Singapore, as well as the United States, where an Executive Order issued in September 2015 directed federal agencies to incorporate behavioral science into their programs (Obama, 2015). Of course, it is important to emphasize that behaviorally informed approaches can also be, and often have been, implemented by agencies without the use of designated nudge units. A key feature of behavioral strategies is that they aim to change "people's behavior in a predictable way without forbidding any options or significantly changing their economic incentives. To count as a mere nudge, [an] intervention must be easy and cheap to avoid. Nudges are not mandates"
Context: Millions of uninsured Americans ostensibly have insurance available to them—many at very low cost—but do not take it up. Traditional economic analysis is based on the premise that these are rational decisions, but it is hard to reconcile observed enrollment patterns with this view. The policy prescriptions that the traditional model generates may thus fail to achieve their goals. Behavioral economics, which integrates insights from psychology into economic analysis, identifies important deviations from the traditional assumptions of rationality and can thus improve our understanding of what drives health insurance take‐up and improved policy design. Methods: Rather than a systematic review of the coverage literature, this article is a primer for considering issues in health insurance coverage from a behavioral economics perspective, supplementing the standard model. We present relevant evidence on decision making and insurance take‐up and use it to develop a behavioral approach to both the policy problem posed by the lack of health insurance coverage and possible policy solutions to that problem. Findings: We found that evidence from behavioral economics can shed light on both the sources of low take‐up and the efficacy of different policy levers intended to expand coverage. We then applied these insights to policy design questions for public and private insurance coverage and to the implementation of the recently enacted health reform, focusing on the use of behavioral insights to maximize the value of spending on coverage. Conclusions: We concluded that the success of health insurance coverage reform depends crucially on understanding the behavioral barriers to take‐up. The take‐up process is likely governed by psychology as much as economics, and public resources can likely be used much more effectively with behaviorally informed policy design.
Labor market policies succeed or fail at least in part depending on how well they reflect or account for behavioral responses. Insights from behavioral economics, which allow for realistic deviations from standard economic assumptions about behavior, have consequences for the design and functioning of labor market policies. We review key implications of behavioral economics related to procrastination, difficulties in dealing with complexity, and potentially biased labor market expectations for the design of selected labor market policies including unemployment compensation, employment services and job search assistance, and job training.Keywords: Behavioral economics, Unemployment insurance, Job training, Job search JEL: D03, D04, J08, J24, J64, J65 Background and motivationThe Great Recession of 2007 to 2009 and its aftermath have been a trying period for American workers. The U.S. unemployment rate reached double digits in late 2009 for the first time in over a quarter of a century and has remained over 8 percent through mid-2012. Real compensation growth has all but stalled. The human costs of labor market turbulence have rarely been clearer, and the value of public policies, such as unemployment insurance and job training programs, that assist workers in managing that turbulence, gaining new skills, and navigating the labor market have rarely been more apparent. Similar problems of persistent joblessness have been apparent in most major economies in recent years.Even in the best of times, the United States' labor market is a dynamic and turbulent one with high rates of turnover (over five million separations and five million new hires in a typical month in normal times) but substantial frictions as well. As a result, labor market programs and regulations are key components of economic policy. Such policies help support the unemployed, provide education and training opportunities, and ensure the fairness, safety, and accessibility of the workplace. The challenge for policymakers in the United States and elsewhere is to design such policies so that they meet these goals as effectively and as efficiently as possible.Labor market policies succeed in meeting their objectives, however, only to the extent that they accurately account for how individuals actually make decisions about work and leisure, job search, and education and training. To a substantial extent such
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