Using Evidence to Guide Employment Assistance Strategies During and After the Pandemic

Using Evidence to Guide Employment Assistance Strategies During and After the Pandemic

Mar 10, 2021
Guests George Putnam, Dana Rotz, and Naihobe Gonzalez discuss the current distressed economy and evidence-based ideas about how to help workers who have been negatively affected by the pandemic.

Guests George Putnam, Dana Rotz, and Naihobe Gonzalez discuss the current distressed economy and evidence-based ideas about how to help workers who have been negatively affected by the pandemic.

March 2021 marks the one-year anniversary of the World Health Organization officially declaring the coronavirus outbreak a pandemic. The disease we’ve come to know as COVID-19 has now infected more than 28 million Americans and led to at least half a million deaths in the United States. COVID-19 has also inflicted serious damage on the nation’s economy. In February, the number of unemployed persons was 10 million, up from 5.7 million a year earlier.

On this episode of On the Evidence, three guests discuss the current distressed economy and evidence-based ideas about how to help workers who have been negatively affected by the pandemic.

  • George Putnam is the labor market information director at the Illinois Department of Employment Security. He helps the Midwest Collaborative, a consortium of nine states that share current administrative data across sectors and develop insights to support reemployment and economic recovery.
  • Dana Rotz is a senior researcher at Mathematica who leads a team that is collaborating with the U.S. Department of Labor’s Chief Evaluation Office to produce short summaries of research related to pressing employment issues during the pandemic.
  • Naihobe Gonzalez is also a senior researcher at Mathematica. She coauthored a recent report for the U.S. Department of Education on findings from two experiments that allowed the use of Pell Grants to help displaced workers earn credentials that might quickly improve their job prospects.

Listen to the full episode.

View transcript


A larger kind of variety, or wider variety, of individuals have been affected by pandemic-related unemployment than maybe you would see in a typical recession. So I think we need to think critically about how the employment programs that have largely been developed to help disadvantaged workers might apply to the broader set of workers affected by the pandemic.


I’m J.B. Wogan from Mathematica and welcome back to On the Evidence, a show that examines what we know about today’s most urgent challenges and how we can make progress in addressing them. Before we start the show, I want to ask for a little favor. After two years of podcasting, we’re eager to learn more about who you are and how we can improve the show. Go to tinyurl/ontheevidence to take a short survey. After completing the survey, you’ll be given an option to provide an email address so you can be entered in a random drawing for an eGift card. Once again, the survey is at tinyurl/ontheevidence. I’ll also post the survey link on the text summary for this episode.

Today’s episode is about the current pandemic economy and evidence-based ideas about how to help people who have lost their jobs or experienced reduced hours and pay. My guests are George Putnam, Dana Rotz, and Naihobe Gonzalez.

George is the labor market information director at the Illinois Department of Employment Security and he helps the Midwest Collaborative, a consortium of nine states that share current administrative data across sectors and state lines to develop insights to support reemployment and economic recovery efforts.

Dana is a senior researcher at Mathematica. Of particular relevance for this conversation, she leads a team at Mathematica that is producing short summaries of research related to pressing employment issues during the pandemic.

Naihobe is also a senior researcher at Mathematica. She recently coauthored a report for the U.S. Department of Education on findings from two experiments that allowed the use of Pell Grants to help displaced workers earn credentials that might quickly improve a person’s job prospects. These experiments occurred after the Great Recession, when the economy was at the beginning of its slow recovery.

I hope you find this conversation useful.


So the first question is to the group. It's pretty broad, but when it comes to unemployment and underemployment, how does the current economic downturn compare to the recession that began back in 2007. And if you don't mind, you know, give some sense of what's similar and where do the comparisons break down. Maybe we’ll start with Dana, and then go to George and then Naihobe. Alright, Dana, you’re up.


There's this great book by Ken Rogoff and Carmen Reinhart about the financial crisis that caused the Great Recession, caused the recession that started in 2007, and it's called “This Time is Different,” but it's really all about why this time isn't different. It's really about how financial crises are, you know, pretty much, pretty similar over time, you know the 2007 financial crisis wasn't any fundamentally different from the ones that came before it.

But this time, it really is different and fundamentally different because the, the recession, the current economic downturn, is not just about the economy. It's not caused by something fundamental in the economy, or in some economic factor. It's really all about public health.

And so, even if the unemployment rate looked the same, and the underemployment rate, you know, underemployment was the same. It's still fundamentally different because the cause is really different. But even if you ignore that, and you just focus on the economy, this recession is different from the Great Recession. The trend in unemployment has been different this time around than in the Great Recession and service needs are really different this time around. Moreover, the effect of this recession has been really very different across industries and groups of people and the types of industries and groups of people, and the uneven effect of the recession on different industries and groups of people has really been somewhat unique.


I can add a little bit to Dana’s comments, at least from an Illinois perspective. I would agree that, you know, this recession distinguished from prior recessions due in part to how dramatic and sudden it was, you know, in the first year of the 07-08 recession, and even in 01, there were about 150 to 200,000, unemployed folks, collecting UI benefits in Illinois. In the first three weeks of the current recession, it was over three quarters of a million. So, just to give you a sense of the volume.

In terms of the dynamic, the unemployment dynamic, what is distinctive about the current recession is the role of furloughs and temporary unemployment spells. And supply chain dislocations, and so at one level, what we're observing in the current recession is the persistence of repeated spells or discontinuous spells more so than in prior recessions. We haven't quite dug deeply into this phenomenon, but it's clear that that pattern is the case. The other point that I would make, Dana mentioned the trend in unemployment, and as we look past this first year, it was the case in the 07 recession that conditions actually deteriorated significantly in that second year. Whereas in the current recession, there's, there's all kinds of signs that there will be some continued healing, although perhaps somewhat modest, continued healing. And so we may find in the second year that a lot of the dramatic and sudden nature of the recession that separated itself in his first year kind of dissipates and in fact, the second year is less severe than than the prior recession.


And Naihobe, how about you? How are you thinking about this pandemic economy and how it compares to past recessions?


I come at this little bit from the perspective of education and training and I think one other kind of interesting contrast between what we're seeing now and previous recessions is that typically you see a sort of inverse relationship between unemployment rates and enrollment in post-secondary education. You know, as in periods of high unemployment, people have more of an incentive to go and get additional training. But with the data that we have so far, for places like the National Student Clearinghouse, it's pretty apparent that that's not the case currently. I think looking at first-time enrollment in the fall of 2020, enrollment was down overall in post-secondary institutions, but in particular in two-year colleges, and in particular, among those students, among older students, you know, older nontraditional students who might be going to community college to get certificates and and occupational training. So I think that's another interesting contrast that we're seeing this time around.


Okay, fantastic. And I appreciate that you've all teased a little bit to some research that you've done or data that you have that we'll take a deeper look at in a second. George, do you want to talk a little bit about the Midwest Collaborative and the specific data that you're seeing both in the region and, and in Illinois specifically? And, if you don't mind, it would be great to capture a sort of laymen's explanation of what the Midwest Collaborative is for our listeners.


Sure, let let me start there. So, the, the Midwest collaborative is a group of of nine states. Some of which are actually not in the Midwest, but of nine states that have identified the importance of going beyond just a sharing of data, but rather to develop analytical products that are are relevant to the particular economic times. And so we have been meeting for a couple of years now. And initially we had expected to be focusing on kind of post-secondary transitions into the workforce, with particular attention to regionalized issues. In fact, we met in Ohio in the beginning of March and within a couple of weeks, with the advent of of the pandemic, and the mitigations completely, not completely, but changed our research agenda to be looking at unemployment and to do so, from the perspective of what is most needed by the workforce boards.

As I mentioned, certainly the volume of what we saw in those first six weeks was significant, and the workforce boards were asking the questions, and this is across the country, you know, which local areas are being hit the hardest? What's the economic impact of that? And then third, what, which subgroups, if I am, in fact, to make decisions, strategic decisions around training, what can you tell me about subgroups that have been hit the hardest in my local area? And so that was really the framework.

In terms of the patterns that we're seeing in the data, I think first, and foremost, are the patterns that have come to the fore in geography and we've looked at UI claimants as a percentage of employed persons by county. And in the first three weeks of COVID we saw very kind of concentrated impact in the southern rural counties, in fact, of Illinois, where between 10 to 15 percent of employed persons in a matter of weeks were all of a sudden collecting unemployment insurance benefits. And a little bit later on, but certainly within that, first six-week window, urban areas began emerging as sort of geographic hotspots. And Cook County was one, where nearly 10 percent of of its employed persons were collecting unemployment insurance benefits. And that continued to peak, kind of up until kind of a six to eight week period, so that the April, and May and towards the end of May, were really kind of peak in both so urban and rural areas.

During the summer months, there was healing, but one of the interesting things that we’ve observed is that once we moved past the summer and sort of into the fall, there was improvement in the southern regions. But Cook, the urban area, remains at 10 percent of all employed people, all the way through to now to January, and just as a point of comparison, prior to the pandemic, it was typical that maybe 2, maybe 3 percent of of employed persons would collect, were collecting benefits.

In terms of demographic groups, what what we've seen, and I think, most of the folks here are aware, is there is a real flip in terms of gender. Prior to COVID, about 70 percent of those collecting unemployment benefits were typically male. However, within the first three weeks, a majority became female, and actually remained the majority through November. And then what happened in November was kind of two things. One was, you had the beginning of seasonal layoffs, so predominantly in construction, which is male dominated. And then second, you had those early cohorts, which were predominantly female, transitioning to PUC, and so off of regular UI and onto the extended federal assistance. And so just to say that, even though we saw kind of that change in the gender composition, it did not mean that women were moving back into the workforce.


Is, does that reflect specific industries that are predominantly occupied by women that were harder hit?


Yeah. And so those were restaurants. Those were the medical field. Those were hotels. They were retail trade. Those were kind of the disposable income services industries that took the brunt of the hit upfront, that were predominantly impacted, the, the female work population.

In terms of the age, we also saw prior to COVID about 4 percent of claimants were less than 25 years old. Six weeks later, it was 12 percent. And it's actually persisted. And in the industry, where that is most apparent, J.B. is in retail trade. If you follow retail trade along, that youth impact is dramatic, and the third dimension where, where are we seeing quite quite an impact is among African American claimants, but that dynamic is a little bit different. Prior to COVID about 20 percent of claimants were African American, and six weeks later at the peak it was still about 20 percent. So the impact on African Americans actually happened after the peak. And presently, it's, it's almost 28 percent. It is 28 percent. And and the industry that's been driving that is temp help. So, the temp help impact was one of the more later impacted industries, and the African American claimant population, one of the later impacted subgroups.


Okay, that's, all of that is really fascinating. Naihobe, I think you had something you were going to add about another potential explanation for the gender breakdown?


Sure, and I think this is more based on anecdotal evidence. A lot of people have been writing about this recently, but that women have been also disproportionately impacted during this pandemic, in part, right, because, you know, like, some of the industries that have been most impacted are ones where women are highly represented but also, because, as everyone’s staying home, including, you know, school-age children, a lot of the responsibilities for caretaking have disproportionately fallen on women. So I think that could also be an important aspect to consider.


And some people have tried to unpack that by looking at the data by age and by gender and by industry. And I think overall while there's not conclusive evidence it does appear that that story about women, having to take home to care for children who are no longer in person at school is is supported by the data.


Okay, terrific. Dana, you're part of a team at Mathematica that conducts rapid literature reviews on timely research topics for the Department of labor, and including a recent short brief that reviews relevant programs and promising strategies for helping unemployed individuals return to work. Before we discuss findings from that review, I was hoping you could just go over, high level, what are some of those government policies and programs with some of those tools in the toolkit for organizations or agencies that want to help?


Sure, so yes, I'm part of the Clearinghouse for Labor Evaluation and Research or CLEAR project team, CLEAR is an initiative of the Chief Evaluation Office within the U.S. Department of labor and its mission is to make research on labor topics more accessible to practitioners, policy makers, researchers, and the public more broadly, so that it can inform their decisions about labor policies and programs. So partially in response to the COVID 19 pandemic, CLEAR has launched a series of rapid evidence reviews to quickly summarize research that can help government agencies, policymakers and other stakeholders make evidence-based decisions in response to the pressing labor issues that they face. We've conducted reviews of past emergency return-to-work strategies that might have lessons for the pandemic and are currently working on a review of research on employment programs and policies during the Great Recession.

We've really considered a very wide range of employment programs and policies, ranging everywhere from broad-scale of fiscal stimulus and other government programs that include infrastructure investments and fiscal relief, particularly the American Recovery and Reinvestment Act of 2009, or ARRA, which is a major stimulus package developed in response to the Great Recession. We've looked at the research on that. We've also looked at unemployment compensation and reemployment programs. So, how do the characteristics of unemployment insurance seem to affect individuals’ reemployment behavior, and then reemployment programs, which provide job search assistance and other help to get people who have lost their jobs back to work.

In addition, we've looked at a number of different programs that have helped individuals to develop their human capital and work skills so that they can enter into jobs that in the longer term and build their skills. Those include programs like transitional and subsidized employment, hiring subsidies and credits, career pathways and apprenticeship programs, self- employment and entrepreneurship programs, and other human capital development and training programs.


Okay, great. So there are a lot of strategies, policies, and programs that you've been reviewing and I imagine that all of them have some promise or else you wouldn't have taken a look in the first place, but in terms of which strategies might be most promising for our current context with the dual economic and public health crises, where, where does the evidence point, which, which might be the most important or promising for this current moment?


Sure, so there's a lot of evidence that job search assistance programs can have strong employment promoting effects. So, when I say job search assistance programs, I mean, individuals receiving assistants and training and job search techniques, including, for example, job search workshops or help preparing a resume or interview training. So the research really suggests that these programs help people return to work faster, but most disadvantaged job seekers need additional support to succeed in the labor market. Many job search assistance programs are relatively inexpensive. So, they're great to implement, and they tend to be cost effective, but they have pretty small effects—so small costs, but leading to small improvements in appointment. And the extent to which case workers can help the unemployed to find jobs depends on the number of available jobs in the area, and the skill set of the unemployed.

So, for instance, when there's more job seekers than jobs, we find that job search assistance programs can sometimes help the individuals who are more employable, who have higher skills, but not necessarily the most disadvantaged workers. To help those types of workers programs that build individual skills are generally needed as well as to have larger effects on unemployment and earnings. However, these programs can be much bigger investments for both workers and the government.

There's also a fair amount of evidence available on subsidized employment programs and hiring subsidies or credits. Subsidized employment programs are great because they provide job opportunities to unemployed individuals by using public funds to pay for all or part of their wages. So, they directly provide jobs to individuals, and they typically offer skill development and support services to help increase the employability of the long-term unemployed, so that they can obtain jobs in the regular labor market after the subsidized employment opportunity ends. But these types of programs are really useful for immediately raising employment earnings, because they give people jobs, but it's not clear yet, based on the research, whether they improve employment or earnings once workers lose access to their subsidized job and must find other employment.

Hiring subsidies and credits, on the other hand, exempt employers from taxes or social security contributions for new employees hired in order to incentivize the creation of jobs. Here research has generally found that hiring subsidies and credits can create jobs when used broadly to encourage hiring of all workers and they tend to be less successful though if they try to encourage the hiring of specific types of workers.

But what does that all really mean in the context of the current pandemic? That's hard to say, because none of our research, or very little of our research at least, has been conducted in a pandemic setting, and so I think we need to think really critically about how we can generalize those research findings to the current situation. Right now, obviously services that can be implemented without requiring face-to-face interaction are looking very promising and they're very desirable. We also need to think critically about the types of jobs and industries people might be interested in building their skills and work building their skills for and working in.

So, for example, there's a lot of research out there that, on health care careers and jobs in health care, and that being a particularly promising field to help individuals train for. But there's also some preliminary evidence right now that interest in health careers may have decreased because of the fact that jobs in health care are more likely than other jobs to expose you to COVID-19.

Finally, I think there's a lot of research out there that's focused on disadvantaged workers and how to help disadvantaged workers find jobs. Disadvantaged workers have certainly been hit by the pandemic and they've been hit harder by the pandemic than other groups of workers. But I think what you see with this economic downturn related to the pandemic is that a larger kind of variety, or wider variety of individuals have been affected by pandemic-related unemployment than maybe you would see in a typical recession. So I think we need to think critically about how the employment programs that have largely been developed to help disadvantaged workers might apply to the broader set of workers affected by the pandemic.


So, Naihobe, I want to turn to you. Both both George and Dana have referenced a little bit the importance of moving people into occupations and industries that are in demand. That I think pertains directly to some of the research you recently did, which draws lessons from the time period after the last recession. From what I understand you examined how the use of Pell Grants could help displaced workers earn credentials that might quickly improve the students’ job prospects, but maybe you can do a little bit of table setting here. I think it'll take some explanation of exactly what you were studying what the experiments were. So, yeah. What were the policy solutions being tested? Who were they intended to help? And what did you find?


Just as background, most folks are probably familiar with Pell Grants being one of the major sources of financial aid for low-income students looking to complete post-secondary education. But the specific rules are part of what we were hoping to better understand because currently Pell Grants are available only to people who are either seeking their first undergraduate degree, or a credential program that last at least a typical semester or 15 weeks.

So, for a long time, and especially during the time of the Great Recession, there was this question of whether these eligibility rules might be restricting access to programs that build job skills for low-income adults who need a leg up in their labor market. And in particular, you know, thinking about folks, so maybe they might already have a bachelor’s degree, but perhaps they would like to get a certificate in in an area that's in greater demand in their field or help, like, stack their existing credentials, or people who don't have an undergraduate degree, but are interested in short-term programs that aren't long enough to qualify for a Pell Grant.

So things like, maybe like a welding program or a truck driving program that might help them find jobs quickly in the labor market. So based on the interest in this question, and the desire to find ways to help displaced workers earn credentials that could quickly improve job prospects. The U.S. Department of Education began pilots of two experiments in 2011. And these experiments occurred in 46 post-secondary schools that volunteered participate in the study. And the idea was to test both of these waivers of eligibility rules that I just described. So, students who participated had to be, they had to meet all of the income requirements for Pell. They also had to be un or underemployed and interested in enrolling in an eligible program.

And then, so the first experiment, it was looking to waive the requirement that a person couldn't seek an additional credential if they already had a bachelor's degree and receive Pell the same time. So that was the first pilot experiment. And it basically allowed income-eligible adults to get Pell funding for short-term programs even if they had a BA. What we found with this first, experiment was that and really this kind of speaks to both experiments, students in the first experiment were 17 percentage points more likely to complete a credential program if they were offered an experimental Pell grant, which is definitely a large impact on program completion.

And so the key question here is, you know, like, were those programs then able to help them in a labor market? We aren’t able yet to link their outcomes to earning and employment data. But we examined whether they were any more likely to complete programs and high demand occupations. So that's defined as applications that are in a new or emerging field, or projected to grow rapidly, or have a large number of openings in that state. And we also found that completion rates increased significantly by 11 percentage points.

And one thing to note, too, about our findings for this experiment was that students who identified as displaced workers based on their financial aid application, were particularly most impacted positively impacted by the receipt of the Pell Grant.

So, I'll say a little bit more about the second experiment, which tested a different waiver, which was on the program length. So, as I mentioned earlier, currently people are not eligible to receive health funding for programs that are any shorter than 15 weeks, and so that does leave out some short, short training programs. So, with that waiver, what we found was that, again, we found some pretty significant impacts on completion. Students who were offered an experimental Pell Grant to pay for very short-term occupational training programs were 9 percentage points more likely to complete a program that they were offered the Pell Grant. And also 8 percentage points more than a complete a program in a high demand field, specifically.

So, to put this into context, these are these studies where the first of their kind to test the effects of expanding eligibility for Pell. And even compared to other studies, just looking at the overall effects of financial aid, these are pretty large impacts. Another thing that's helpful to know is what kinds of programs are we talking about. In experiment one, where it was people who already had an undergraduate degree, most of the programs that they completed were in the health care field, so, programs, for example, like, for registered nurses.

In the second experiment, where it was more about completing a very short-term programs, most of the programs that people completed were in the fields of transportation and materials moving, and in particular, truck and commercial vehicle operation. You can think of those as, you know, shorter programs, for example, in in the health care field and might be something to help people become a nurse’s aid, for example.

So, the kind of overall takeaway really for for this study is that certainly it seems like providing financial aid to low-income adults who are un or underemployed is very effective in helping them complete occupational programs. But the big question mark is whether the labor market returns, you know, would offset the cost of expanding this eligibility. On average, students in the study who received a Pell Grant, received about 1800 dollars. These programs are generally short term and so therefore their costs are also lower. But there's still I think a lot of open questions about whether programs that are high demand might also lead to higher wages. And so I think here, we, there's some, there's some emerging evidence that suggests that certificates from certain short occupational training programs can be very attractive to employers. But the benefits of these short programs do seem to vary with the field of study. Dana touched on earlier how certain programs in health care in particular can have high returns, and so there's other fields like that, where it seems like, there's a greater benefit to these programs.

But the benefits can also vary according to local labor market conditions, and even individual characteristics, like gender and race and ethnicity. So, going forward, I think the question really would be is expanding Pell Grant eligibility something that Congress should consider? Because it would require new legislation to do. And we would really hope to be able to learn more I think about the labor market returns before we can really say. We estimated that if Congress were to, for example, expand Pell Grant eligibility to the very short courses that could add about as much as 500 million dollars more to federal financial aid expenditures. And so, although we're seeing, you know, really large impacts on program completion, you know, that needs to be weighed against, the labor market returns, so that people who actually get, who actually go on to obtain those credentials.


So one thing I wanted to ask was was sort of an equity question, both from a public health perspective, and an economic perspective, the pandemic is harming some groups of Americans more than others. I just quickly looked up earlier this week, the unemployment rates for certain groups and it's higher, the unemployment rate is higher among Black Americans and Latino or Hispanic individuals as well as people with disabilities. So, I wanted to ask, is there evidence or does the evidence point to specific reemployment strategies that are effective and equitable targeting those who are bearing the brunt of this pandemic’s effects or impacts. I mean, both both public health and economic, because you've got people who are, more people are getting sick, more people are dying, and more people who are suffering unemployment or under employment effects.


I think this is very much still an open question. We know what tends to work. Sometimes we know what tends to work for individual program participants. Sometimes we know what tends to improve kind of the overall unemployment rate in the economy, and overall output in the economy, but there's really very little research on how programs might differently affect individuals based on race and ethnicity or gender, age, and other characteristics. Another thing that I think is very much a concern is that when you implement something like change in UI structure or fiscal stimulus, discriminatory hiring behaviors could actually result in minority communities failing to benefit from strategies that improve outcomes for others and improve outcomes to the overall economy. So I think much more research is really needed to probe into how to help the most vulnerable groups, and in particular, the groups that are really bearing the brunt of of the pandemic right now.


Naihobe, I did wonder, since your study is looking at students with low incomes, I did not see a breakdown of the demographic features or characteristics of those students, but I was wondering if they disproportionately help students of color, or or any specific demographic groups you'd want to call out here.


Yes, well. The demographic data for the study came from the FAFSA, the federal application for financial aid, which does not collect race/ethnicity. So we didn't have that information. We did have information around age and gender. Also things like, you know, whether the person was the displaced worker, whether they were homeless, whether they were a veteran. So we did try to look at whether the financial aid offer was effective for different groups of students based on what we could observe about them from the FAFSA.

And generally speaking, we found that the impacts work consistent across all of these groups. The one thing that did stick out was in the first experiment for folks who already had a BA. The effects were especially larger among those who were displaced workers and therefore had the greatest employment needs. So, unfortunately, I think they're, I mean, just to kind of echo a little bit of what Dana said, I think there are a lot of open questions still I think folks rightly pointed out that there's also questions about, if you were to now offer financial aid for these very short term programs, and also raises a lot of questions about program quality and making sure that folks who are going to these programs who might be particularly low income minority workers, that they're getting a quality program that is going to help them actually have better labor market outcomes and so how do you build that in, not just in terms of, like, as a research question, but how do you build that in also into the policy? So, that everyone is, is actually investing in something that is actually going to help those workers who need to help most.


Okay, perfect. Well. Dana, and Naihobe you both have teased to my last question by pointing out that there are unanswered questions, or or some limits to the evidence we have now. This show is called On the Evidence and we like to talk about what we know, but it's also worth talking about what we don't know yet. Talk about any gaps and knowledge that are relevant to this conversation. Is there any data or evidence about potential solutions that you wish you have, but just aren't available yet. And also, what questions do you hope future research might answer?


So, one major challenge I think that we run into a lot in trying to use the evidence that's out there is that we know which programs work and which programs don't seem to work. But it's really hard to know why that is. And seemingly similar programs can have pretty different effects on on workers. So I think we really need to get under the hood of successful programs and find out what drives their success. That's going to help us know how to further improve programs and will better prepare us to adapt programs to unexpected issues and crises.


Yeah, I I would say. An important gap, and maybe this is some of what Dana's getting at, in terms of what, what is not known. Is I think there's a lot more work that needs to be done on the whole area of wage replacement. So, there's certainly a body of work that's looked at pre-separation wage as it relates to the average weekly benefit amount and a lot of discussion around whether that incentivizes or not, reemployment, but I would say as well kind of linking it to that next piece, which is the, the reemployment wage. So, you have then kind of a a linkage between the pre-separation wage, the, the weekly benefit amount, and then the reemployment wage, and where I think that's important is that that then speaks to the economic health of the workforce board area, the health of the labor market in that area. So are individuals moving to the same wage level or are we seeing that the reemployment wage is of a sufficiently different level that it actually contributes to the economic health of the local workforce board area, and that economy and that labor market?


And Naihobe, we’ll wrap up this conversation with your thoughts. Based on the Pell Grant experiments you studied, what do we still to learn about effectively supporting people as they look to get back into the labor force?


I think it's, definitely an area that needs further exploration are the labor market returns to various occupational types of training programs. So to understand which types of credentials you know actually help people get jobs and and earn higher wages, and, is is that true for different types of of workers?

And in thinking about whether there should be an expansion to federal financial aid for these types of programs, in addition to that, I think it's worth noting that the Pell study that I described, it took place in schools that volunteered for the study and so I think there are also some questions that if this were to become federal policy that suddenly all schools could now receive financial aid to offer these very short-term occupational training programs, you know, like you want to make sure that that wouldn't necessarily, for example, like, discourage people from maybe completing longer term programs that, you know, generally have been documented to have higher labor market returns. So I think there's just some questions about whether we would see the same types of large significant impacts if we were to actually make it a broad federal policy.


Thanks again to my guests, Naihobe Gonzalez, Dana Rotz, and George Putnam. On the episode page, I will list links to the data and research we discussed. I’ll also list them on the show notes section of the Mathematica blog that we post with this episode.

As always, thank you for listening to another episode of On the Evidence, the Mathematica podcast. Subscribe to the show wherever you get podcasts. You can also keep up with the latest episodes as well as other interesting work from Mathematica by following us on Twitter. I’m at JBWogan. Mathematica is at MathematicaNow.


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Show notes

Learn more about the Midwest Collaborative.

Read a rapid evidence review for the Clearinghouse for Labor Evaluation and Research at the U.S. Department of Labor that summarizes the evidence on relevant programs and promising strategies for helping unemployed individuals engage in job search activities and return to work.

Learn more about Mathematica’s evaluation for U.S. Department of Education experiments that allowed the use of Pell Grants for short-term occupational training programs.

About the Author

J.B. Wogan

J.B. Wogan

Senior Strategic Communications Specialist
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