Unemployment Insurance (UI) is a significant part of the social insurance safety net in the United States and around the world. The experience of COVID-19 illustrates the critical role that UI can play in the face of enormous aggregate shocks. It also highlights an issue that has been a perennial focus of UI policy: how the duration of benefits should depend on the state of the economy.

UI benefits in the United States are currently set to 26 weeks in most states. Extended benefits (EB) begin if a state’s insured or total unemployment rate exceeds legislated thresholds, with additional duration of 13 or 20 weeks. The current EB system has two potential shortcomings. First, the stringency of the trigger thresholds (including allowing states to opt out of the less stringent triggers) means that the system rarely actually triggers. Second, the additional 13 or 20 weeks may provide inadequate coverage during severe recessions. In response, Congress has enacted temporary additional extensions during each recession over the past 40 years, with extensions on 5 separate occasions ranging from 6 to 53 weeks.

For decades, economists have recommended replacing a system where extended durations of UI benefits are decided by legislative fiat to a more systematic linkage between benefit durations and economic conditions. However, the actual design of such automatic extensions has not been the subject of much previous analysis. In this paper, the authors develop a simulation model to analyze the tradeoffs inherent in different extension policies, and they reach three conclusions:

  • Policies designed to trigger immediately at the onset or even before a recession starts result in benefit extensions that occur in less sick labor markets than the historical average for benefit extensions. 
  • Ad hoc extensions in past recessions compare favorably ex post to common proposals for automatic triggers, with one important disclaimer:  Past behavior is no guarantee of future legislative performance and there may be other benefits to automating policy. 
  • Finally, compared to ex post policy, the cost of more systematic policy is close to zero.

More on this topic

Research Briefs·May 23, 2024

Can You Erase the Mark of a Criminal Record? Labor Market Impacts of Criminal Record Remediation

Amanda Y. Agan,  Andrew Garin, Dmitri K. Koustas, Alexandre Mas, and Crystal Yang
Removing a previously obtained criminal record does not improve labor market outcomes, on average, with the notable exception of participation in gig work through online platforms.
Topics: Economic Mobility & Poverty, Employment & Wages
Research Briefs·Apr 23, 2024

Early Predictors of Racial Disparities in Criminal Justice Involvement

Andrew Jordan, Ezra Karger, and Derek Neal
Detailed measures of early academic achievement and socioeconomic status are powerful predictors of future criminal justice involvement; however, while reforms that improve school quality and neighborhood environments are likely to reduce future racial disparities in criminal justice involvement, such improvements...
Topics: Early Childhood Education, Economic Mobility & Poverty, Higher Education & Workforce Training
Research Briefs·Apr 18, 2024

Does Nothing Stop a Bullet Like a Job? The Effects of Income on Crime

Jens Ludwig and Kevin Schnepel
Policies that reduce economic desperation reduce property crime (and hence overall crime rates) but have little effect on violent crime.
Topics: Economic Mobility & Poverty