Unemployment insurance is a lifesaver for many people when they lose their jobs. And when times get really bad in the US — in recessions and during the Covid-19 pandemic — Congress has extended the duration of unemployment benefits for millions of workers.
But is there a better way to structure unemployment insurance time? For some workers, benefits come too late after an economic downturn to prevent household financial crises; others need insurance payments just as Congress is debating what the benefit extensions will eventually become. To avoid ad hoc policymaking, the federal government could potentially set objective “triggers,” such as significant increases in the unemployment rate, that automatically extend unemployment benefits when recessions hit.
Now a study co-led by an MIT economist, based on extensive modeling, examines the effects of automated unemployment insurance policies. Unemployment insurance based on such factors won’t cost more — or less — than the packages Congress ultimately passes, the results suggest. But an automated system would provide more clarity to workers in times of economic stress.
“There is a cost to the way Congress does it, which is that people face uncertainty,” says Jonathan Gruber, an economics professor at MIT and co-author of a new paper detailing the study’s results. “Right now, Congress decides at the last minute, or waits a week or two after benefits expire to extend them. This kind of uncertainty is costly for people.”
In contrast, Gruber notes, “The advantage of automatic triggers is that you get to choose the uncertainty, and it actually wouldn’t cost much more than the existing system because Congress extends the benefits anyway.”
The paper, “Should we have automatic unemployment benefit duration triggers and how costly will they be?” appears in an annual publication of the American Economic Association, AEA: Works and works. Co-authors are Gabriel Chodorow-Reich, professor of economics at Harvard University; Peter Ganong, associate professor at the University of Chicago’s Harris School of Public Policy; and Gruber, who is the Ford Professor of Economics at MIT.
Unemployment insurance usually lasts 26 weeks; in theory, when unemployment exceeds certain thresholds, states will further extend benefits. On five occasions in the past 40 years, Congress has extended unemployment insurance nationally, with states administering the benefits.
To conduct the study, the researchers developed a model — they call it the UI Policy Simulator — examining the period from 1996 to 2019 by state. The researchers used data from the Bureau of Labor Statistics to simulate each state’s labor market and modeled the outcomes that would result from implementing multiple types of unemployment insurance policies.
For example, one set of simulations implemented what the researchers call a “Sahm trigger” (after economist Claudia Sahm) that would increase benefits following an increase in
unemployment rate that was 0.5 percentage points above its minimum three-month average over the previous 12 months. Another set of “levels” of simulations extended insurance by 13 weeks when unemployment reached 5.5 percent in a state, 26 weeks at 6.5 percent unemployment, 39 weeks at 7.5 percent unemployment, and 52 weeks at 8.5 percent unemployment. Yet another set of simulations modeled “hard” versus “soft” cuts based on how long benefits would be extended after the unemployment rate fell below the stimulus threshold.
Overall, the size of the benefits (and thus spending) that the model produced was very close to the size of the packages that Congress passed in the wake of the 2001 and 2007-09 recessions. Therefore, in theory, cost is not a big issue.
One wrinkle the modeling revealed is that such a system would take hold in labor markets that haven’t deteriorated as much, meaning an extension of benefits could be triggered in a state that then quickly falls below the cap. of unemployment.
“There’s a trade-off,” Gruber says. With a lower trigger threshold, “You can get people’s benefits a month earlier. On the other hand, you run the risk of having ‘false positives’, where you send people benefits when you think they are [the economy] it’s going to go south, and it doesn’t.”
Another factor to consider, as the authors write in the paper, “past behavior is no guarantee of future legislative performance.” Codifying an automated unemployment insurance system could help protect workers from a future congressional gridlock on the issue.
Can this type of policy become law? Gruber thinks this may require a change in the way the Congressional Budget Office (CBO) evaluates policy (ie, estimates its cost). Currently, CBO is required to weigh the cost of not having an integrated unemployment insurance policy—even though Congress has repeatedly enacted such measures in times of need. This approach makes an automated policy look like new government spending, which could make lawmakers less likely to support it.
“In a sense the reason we never get automatic triggers is because of the way our congressional scoring works,” Gruber says. However, he notes, “If Congress is going to do it anyway, it has zero cost from today’s perspective.” Gruber also notes: “I don’t want to [be critical] of the CBO. They are just following their mandate.”
The duration and amount of these benefits was recently a pressing issue during the first 18 months of the Covid-19 pandemic, as unemployment rose in the spring of 2020. Within the last year, US unemployment has fallen to the lowest levels not seen have been seen for decades. But at some point in the future, unemployment is likely to become a bigger concern again, suggesting to Gruber that any time would be a good time to consider this type of legislation.
“Hopefully we won’t forget that and we’ll be able to fix the system when we can,” Gruber says.
He adds: “That’s really what I think we can do in economics that is so valuable to the world: use the modeling tools we have to talk directly to policymakers about the things they care about.”
The research was supported, in part, by the Becker Friedman Institute of the University of Chicago, the Harvard Ferrante Fund, and the Alfred P. Sloan Foundation.