[Transcript] Left Out or Dropped Out? Continuing the Conversation on Men and Women in the Workforce


Fed Communities Staff

A male at a job site, a working mother, and a female standing outside an office.

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Jennifer Fernandez

Hello, welcome to day two of the Uneven Outcomes in the Labor Conference. My name is Jennifer Fernandez and I’m happy to join you today. This conference was organized by the community development staff from this Federal Reserve Board and the Federal Reserve Banks of Atlanta, Boston, Cleveland, Philadelphia, San Francisco, and St. Louis. Over the next three days, we hope to convene researchers, policymakers, and practitioners to examine disparities in labor market outcomes, explore policy solutions to address these inequities.

We aim to deepen your understanding of disparities in employment, labor force participation, income, and wealth, and to learn about their implications for economic growth, the health of communities and individual well-being. We do welcome questions throughout the session, so if you have any questions at all, just enter them into the Q&A function. The chat will be disabled. To get us started today, I’m excited that we are going to open with some remarks from President Susan M. Collins of the Federal Reserve Bank of Boston. Thank you.

Susan M. Collins

Thank you very much, Jennifer, and it is really great to be with you today and take part in this conference. And that’s true for a few reasons. First, the topic, persistent labor market disparities is important and timely. And second, the papers that are being presented are timely and they are really well done. And so in addition, I’ll just echo Raphael Bostic’s comments yesterday about how thrilled I am to be taking part in this collaboration among five reserve banks and the board of governors. So I’m just delighted to have the opportunity to provide today’s remarks to open the sessions. I want to start by underlining the importance of rigorously exploring persistently uneven labor market outcomes. Very appropriately the conference organizers have rooted this effort and the Fed’s mandate from Congress.

Of course, that’s typically summarized as maximum employment and price stability, the dual mandate, and of course the widely followed overall unemployment rate is typically the standard measure for how to look at the state of the overall US labor market. But underneath that, any single statistic, there are wide-ranging differences across geographies, demographic groups. And so no one statistic can adequately characterize the labor market because aggregate numbers mask the wide range of experiences across people, sectors, and places. So uneven labor market outcomes call for a full and focused exploration that’s motivated by our duty to pursue the Fed’s maximum employment mandate. For some people, communities and places, there are substantial and persistent gaps in economic outcomes.

And that includes, but of course isn’t limited to employment. This underutilization of the workforce adversely affects national productivity and prosperity. So I often describe our work at the Boston Fed as pursuing and supporting a vibrant economy that works for everyone, not just for some people. And that along with the Fed’s mandate, compels us to better understand the challenges contributing to higher unemployment and underemployment present in some areas and among some demographic groups and the long-run barriers to full participation in the labor market. The Federal Reserve needs to parse the labor market for another reason, to gauge the cyclical position of the economy, thereby allowing monetary policymakers to appropriately calibrate the stance of policy and to better understand and thus achieve the full employment portion of the dual mandate.

So regarding the labor market’s cyclical position, consider that during and after The Great Recession of 2007 to 2009, aggregate labor market participation fell significantly. To gauge the short-run state of the labor market, the interest rate setting federal open market committee needed to understand how much of this decline was cyclical and how much was structural. Undoubtedly many people dropped out of the labor force due to the cyclical situation. It was a poor job market, but structural factors, most notably the aging of the population also played a role. Disentangling the relative contribution and persistence of cyclical and structural factors was key to formulating and implementing an appropriate policy response. Understanding the behavior of labor force participation is important because when participation changes, the unemployment rate becomes an inadequate indicator of full employment.

And if participation increases in a tight labor market, labor supply expands and those higher levels of economic activity may not generate additional price pressures requiring tighter monetary policy. And higher levels of activity and participation can benefit those drawn into the labor market. We know that many structural factors impact participation. Examples include the long-running decline in job opportunities for less educated workers, which has particularly affected prime age men and the high cost and limited availability of quality child care, which tends to reduce participation among women with children, parents with children. As I travel around my District, New England and speak to a wide variety of stakeholders, I hear about the issues that impede participation in the workforce, which is a challenge not only for individuals but also for employers and communities.

And in this way, issues like child care can really affect the economy. Of course, monetary policy is not the right tool to address these types of structural labor market frictions. However, Fed economists can and do conduct rigorous really valuable research on structural issues and convene conferences like this one to discuss our own work and that of others and to learn from one another. These kinds of intellectual exchanges reflect, as I noted earlier, the Federal Reserve’s mandate to promote full employment. Last fall, The Annual Boston Fed Economic Conference focused on the question of how best to define and promote full employment, maximum sustained employment. I recommend those papers and the sessions to you as well. Presenters paid particular attention to barriers preventing many individuals from fully participating in the labor market.

Conference participants analyzed gaps in employment along racial and gender lines, discussed the effectiveness of job training programs, learned about new ways of measuring the gig economy and analyzed barriers to employment faced by individuals who had contact with the criminal justice system. Like that conference, today’s discussion brings together rigorous, thoughtful, creative researchers to explore policy-relevant issues in service to the public good. So convenings like these demonstrate the power of inquiry and also collaboration. Today’s session turns to dimensions of a particularly important facet of this work, the experiences of women and men in the workforce and the economic and cultural factors affecting individual decisions related to workforce engagement.

So I really want to thank today’s speakers for the research that they and their teams have conducted and will share with us on how some incentives and barriers drive differing labor force participation decisions and experiences for men and women. Each of the papers that we’ll hear about illuminates one or more ways gender differences in employment and participation can arise. And so I’d just like to mention a highlight or two. The Xu paper highlights how weak labor markets during economic downturns can actually increase participation for some workers. For example, a woman may enter the labor force in response to her spouse being laid off. The Buzard et al paper considers how stereotypes about parental availability can worsen gender inequality in the labor market. Because mothers are called much more frequently than fathers when issues arise for their child at school, women face an implicit barrier to labor force participation.

The Mengali et al paper considers factors behind declining participation by prime age men. While changing demographics explain little of this decline, increased caregiving by men plays some role. However, the authors interestingly find the largest contributor to the rise in male non-participation is skills mismatch. And the authors further document that these factors and the rise in non-participation generally are more pronounced for prime age Black men. The Gurkhi et al paper uses random variation generated in the administration of childcare subsidies to test whether such subsidies raise maternal employment and earnings. The results indicate that childcare subsidies have a positive and statistically significant effect on maternal employment.

The authors also find that differences in total earnings induced by the policies while not statistically significant, we’re in the same positive direction and about the same size as the employment effects. So that’s just a little sneak preview of the really great and very interesting research that we’ll hear about today. I think we’re in for quite a treat. So my thanks to all the organizers, the contributors, and the attendees. Thank you so much for being here as well. And now it’s my pleasure to turn the floor over to Richard Reeves, founder and president of the American Institute for Boys and Men and a long time thought leader at Brookings. Thank you so much.

Richard Reeves

Thank you President Collins. I’m not sure if I’m supposed to go next or whether we introduce the panel, but I’ll take silence as a sense to proceeding. I think Jennifer is going to introduce the panel coming after me and then I’ll jump in. Is that right, Jennifer?

Jennifer Fernandez

Sure. Thank you. Yeah, great.

Richard Reeves

All right.

Jennifer Fernandez

So we got a little preview. So yeah, so we’ve titled today’s panel Left out or dropped out. Continuing the conversation on men and women in the workforce. And as we know, economic and cultural factors affect an individual’s decision on how to engage with the workforce. So today’s speakers are going to discuss research on how some incentives and barriers drive their differing labor force participation between men and women. The full bios for all of the speakers today are available on the conference website, and a link is available in the Q&A box on the screen. Today you are going to hear from the following speakers. So you already saw a little bit of Richard Reeves, president of the American Institute for Boys and Men, and he’s going to provide some framing for today’s topic. Following that, you’ll hear from Huanan Xu, associate professor at Indiana University of South Bend.

She’s going to present her research on labor market transitions over the business cycle gender differential in the United States from 2001 to 2020. Then you’ll hear from Evgeniya Duzhak, she’s the regional policy economist at the Federal Reserve Bank of San Francisco. She’ll present on her research Pulled Out or Pushed Out, why so many men no longer work. Next, you’ll hear from Leah Gjertson, junior researcher at the University of Chicago’s Chapin Hall. She’ll present her research on A natural experiment, evaluating the effects of subsidized childcare on mother’s employment.

And lastly, we’ll close out with Kristy Buzard, associate professor of economics at Syracuse University who will present her research on gender differences in demand for parental involvement. Chandra Childers, a senior policy and economic analyst at the Economic Policy Institute will discuss the research and moderate questions and answers to follow. During the session, of course, the views expressed are those of the presenters and not necessarily those of the Federal Reserve system or the Board of Governors of the Federal Reserve. And with that, I’ll hand it back over to Richard. Thank you.

Richard Reeves

Thank you Jennifer. And thanks again to President Collins. It’s a real honor to speak between President Collins and a star-studded scholarly panel that’s coming. As she suggested, you are in for a bit of a treat. So I’m just going to try and frame I think some of the key themes that are going to be discussed today. And for me, the big message here is everything connects. As President Collins made clear in her remarks, monetary policy, clearly connecting with employment opportunities, but any serious approach to improving outcomes and equality of outcome can’t treat families as separate from the labor market or men as separate from women or schools or other institutions, child care institutions as separate to workplaces. To the extent that any of these were separable in the past, they’re certainly not today. But it’s also clear that our mental models, our policies, and our norms have yet to catch up with this everything connects world.

And there’s a number of examples that I think will come out in this conversation. I’ll just mention a few here. The first is that the family is a labor market institution. And the labor market is a family institution. When we live in a world where in most two-parent households, both parents work, there’s obviously a strong connection between family life and economic life. And if we weren’t persuaded of that already, the work of the latest Nobel Prize winner on economics, Claudia Goldin shows very clearly the deep interconnections between employment and family life. If men aren’t working, that puts pressure on the family. And in fact, there’s some scholarship from folks like Heather Boucher, Isabel Sawhill showing that the only reason that middle-class families saw an income rise over recent decades is thanks to the increased earnings and employment of women, which is of course great news. But we do want to see more balance.

And in the papers you’re about to hear, you’ll hear more about this. And I was also struck like President Collins of the finding from Leila Bengali and her co-authors that about a quarter of the employment gap between millennial and Gen X prime-age men is because of caregiving. And I think that’s a striking finding and it’s a useful counterweight to the… Sometimes there’s the eye-rolling that goes along with discussions of men’s declining labor force participation. But also what jumps out to me was the confirmation of the strong relationship between marriage and male employment. The paper shows that 15% of unmarried men are not participating in labor force compared to only 7% of married men. And that the causal arrow increasingly evidence seems to suggest the causal arrow is going from marriage to work and not just the other way around, which is something I think is an interesting and important finding.

And if that’s true, the growing class gap in marriage rates that Melissa Carney and her excellent new book is something that labor market economists can’t avoid paying attention to. Number two in terms of connections is that health matters for employment and of course vice versa. So we see from the paper that most millennial men, that more millennial men are out of work because of disability than in previous generations. And of course behind that we know that more of the disability that’s being reported is related to mental health. And what that means is that the mental health challenges faced by both women and men are crucial to understanding labor market trends that was perhaps most painfully obvious in relation to the opioid crisis. But it’s also clear that the challenge strongly remains. And with my day job, new day job hat on here, I’d be remiss, me not to point out that the suicide rate is rising rapidly among young men and is four times higher among men than women.

And the policy has a role to play here too, of course. And it was something of a shock to discover in forthcoming work that the Affordable Care Act covers the screening of anxiety among girls and women without costs, but not among boys and men. But if we’re serious about male labor force participation, which we need to be, then we need to get more serious about male mental health. Number three, men and women are much more likely to be interdependent economically than one being dependent on the other. And the finding that women are becoming more attached to the labor market over the business cycle, which was updated and confirmed in the next paper from Huanan Xu is important. And as she points out, not in the end the challenge by the COVID-19 recession, but has a paper shows the stories even more interesting, it’s women with caring responsibilities and lower incomes who act most counter-cyclically.

So when there are two earners or potential earners in the household, the economic position of one influences the labor market decisions and opportunities of the other. And so the good news there is that the family plays an increasingly important role in ensuring against risks and creating opportunities. But the bad news is that in recent decades, it’s mostly been women helping to absorb some of the negative shocks of declining male job prospects. And the goal here is clearly for a more balanced insurance pool, if I can put it that way, but within the family. And that means among other things, there’s much more to do for men in terms of education and skills. Bengali et al’s paper does show very clearly that education level is becoming more important to explaining male labor force participation. And that’s really important to understand given what’s happening in particularly post-secondary education.

So we’ve seen there’s about 1.2 million fewer students now than there were in the peak in 2011, but among that 1.2 million decline, it’s important to know that 1 million is men and 0.2 million are women. And so the declining in college enrollment is extremely skewed towards men. And that matters if education matters for labor force participation. And again, as President Collins was at pains to point out, the intersections here are very important with race. And so it’s interesting to note that two-year colleges can play in a particularly important role in the employment of Black men. And all of this means that helping families and women and children means investing intentionally and specifically I think in men’s skill development. So technical high schools, apprenticeships, community college, vocational programs, all skew quite heavily male, both in demand and in the evaluations of their positive outcomes.

And many people see that as a bug, but I wonder if we shouldn’t instead see it as a feature. And next is of course, institutions that influence family life necessarily influence the labor market. Childcare is most obvious example of that and confirmed again by one of the papers. But I was really struck by the fact that elementary schools can be labor market institutions perhaps in different ways to the way we think that the obvious way is that they allow us to work while our children are in those schools and that actually start school start times and after school activities influence not only children of course, but their parents’ opportunities to engage in the labor market. But the finding from Buzard and her co-authors at schools are much more likely to call moms and dads was one that I responded to on a personal level because I had exactly that experience as the stay-at-home dad when my kids were in elementary school.

But nonetheless, even though I was first on the call list and I was a mile away from the school, it was very often my wife who would get the call if our kids were sick, even though she was sometimes in a business meeting on the other side of the world. And they eventually got the message and started calling me instead. But I think the point here is that gender norms can be reinforced or blunted by institutional practices in a whole range of settings, including education, but healthcare and of course in terms of the norms around caregiving and time off in the workplace providing leave changes absolutely nothing unless people take it. And that’s particularly issue among men and fathers. So a father-friendly workplace is a normative goal as well as a policy one. So norms matter a lot, but they don’t emerge out of thin air. They’re bolstered or reformed by institutions and policymakers need to take norms more seriously.

So the conclusion that I come to is that families, children, marriage, school, work, health, all of these are often treated as separate subjects by scholars and policymakers, but they are deeply and increasingly interconnected in the lived experience of real people, of us. Everything connects in real life but is too often disconnected in scholarship and policymaking. So there’s much more to do for example, in terms of reforming labor market institutions, which is I think one of the central discussions we’re having here. And as Claudia Goldin herself wrote in her book, though we’ve reached an unprecedented era of equality between men and women economically, in some ways we’re still living in the dark ages. She goes on, our work and care structures, our relics of a past when only men had both careers and families.

Our entire economy is trapped in an old way of functioning, hampered by primeval methods of dividing responsibility. So that’s perhaps a bit too pessimistic from Claudia Goldin. I think there are some signs of light and change here, but there’s clearly much more to do to bring about more equality of opportunities and to understand this interconnection between all of our opportunities, especially within families. But there’s also much more to do to deepen our understanding of these interconnections, which is what the work you’re about to hear about does so much to advance. And so with that, it’s my great pleasure to hand the baton, online baton on and to the first presenter in the panel session to talk about the differences between men and women labor market attachment. So my pleasure to introduce Huanan Xu.

Huanan Xu

Thank you very much. I would like to thank the conference organizers for hosting event and the chance to present my paper. The paper I’ll be talking about examining the gender differential in labor market transitions over the business cycle. The transition here measures the dynamic inflow and outflow among employment, unemployment and not in the labor force. I used the publicly available data from the current population survey and examine the gender differential in the United States over 20 years just before the COVID-19 pandemic hit the labor market. If you could go to the next slide, please. Several factors contribute to the gender gap in cyclical sensitivity. For example, female labor supply is more elastic to the relative return of market work. Men and women also differ in their attachment to the labor market. I’d like to first introduce several hypotheses that explain why there will be gender differential in cyclical sensitivity.

The first one is the sexual gender segregation hypothesis. Male workers are more likely to concentrate in cyclical affected industries and female workers tend to concentrate the industries providing relative protection and are not significantly affected by cyclical changes in output. The second hypothesis says that women served as a flexible reserve, they’re likely to be recruited in upturns and expelled in downturns. As a result, women’s employment moves pro-cyclically. Number three, the segmentation hypothesis indicates that women may be more likely to be employed in the secondary labor market and may likely experience marginal attachment. The added worker effect refers to an increased supply of women’s labor due to the decline in household earnings as a result of men’s unemployment.

Lastly, the substitution hypothesis suggests that female workers lower bargaining position makes them attractive workers to substitute for men during economic downturns. As a substitute for male workers, this hypothesis predicts counter cyclical trends for women’s employment as the economy condition becomes worse. In the past decades, we have observed gender differential in labor market performance in both developed and developing countries. In the US there have been sustained rises in female participation and systematic falls in male participation. This is likely due to the increased integration of women into the labor market because of their higher educational attainment and increasing presence in high skilled jobs. Next slide please. In this paper I use individual level CPS data to examine the gender gap in their labor market transitions in the United States, the data cover 20 years and are matched across adjacent months from January 21 to January 2020.

The outcome variable I’m looking at is the transition rate, which is constructed as the probability that a worker I in month T transits from one labor force status to another labor force status in the following month. The labor force status could be employed, unemployed or not in the labor force. I construct a state level business cycle measure to capture local demand at monthly frequency. This variable measures local business cycle conditions that are adjusted from the overall national economic condition. In the paper, I examine the gender differential in monthly flows among employment, unemployment, and non-participation. I also conduct a Heterogeneity test by different family and job characteristics and A Great Recession test to see whether there was any structural change brought by the 2007 Great Recession. Next slide please.

The first two columns in this table shows the baseline results for the transitions to employment over the business cycle. As indicated by the interaction term, women are more likely to transit into employment for each percentage point increase in the business cycle measure. This reflects the added worker defect that women tend to compensate household income as a second earner as the economy worsens. The result also provides evidence to the substitution hypothesis that women become attractive workers to substitute for men during economic downturns. Next slide. Then Columns three and four show the transitions to unemployment over the business cycle. Women are less likely to transit into unemployment for each percentage point increase in the business cycle measure. One reason may be that the sectoral segregation provides women with relatively protection in downturns. Next slide.

Columns five and six show the transitions to nodding the labor force over the business cycle. Again, from the interaction terms, we can see that women are less likely to leave the labor force for each percentage point increase in the state unemployment rate. This result suggests that female workers are becoming more strongly attached to the labor force than men are over the business cycle. If you could please go to the next slide. I repeat the baseline estimates here by family and drop characteristics to examine the heterogeneity in cyclical responses. The sample is divided by the number of children in the household, marital status, educational attainment, and major industries. Impacts are found strongest among women with relatively lower educational attainment. Women’s cyclical sensitivity is also greater when their first child enters the household and when the number of children in household increases to three or more.

Findings here speak to the flexible reserve hypothesis and the added worker effect, which suggests that female workers, especially those with lower human capital endowments, serve as a flexible reserve and their labor market behavior over the cycle depends on the organization of the family. Next slide. Finally here, another dummy variable indicating the post 2007 Great Recession period is added to the interaction term to test the structural change brought by The Great Recession. The result stands out here is the employment to nonparticipation transition. In the post Great Recession period, women were less likely to transit from employment to not in the labor force, which indicates a secular increase in women’s employment. So with the onset of The Great Recession, women demonstrated a stronger pattern in terms of not exceeding the labor market. Next slide.

To conclude over the business cycle, female workers are more likely to transit into employment and are less likely to transit into unemployment and nonparticipation as the economic condition becomes worse. The impacts are found strongest among women with relatively lower educational attainment and substantial child care responsibility. The Great Recession test indicates that there was a secular increase in women’s employment. Next slide. Finally, I’d like to discuss a little further about the pandemic recession. The sample period of this study does not cover the COVID-19 pandemic, but there has been involving literature showing that the most recent pandemic recession is very different than previous recessions and my result in a different gendered impact.

For example, due to the government mandated business closure policies, workers in non-essential industries such as leisure and hospitality were hit hardest by the pandemic recession. Also during the pandemic recession, women may be more disproportionately affected due to the increased child care growing demands and there being more concentrated in service-type jobs that cannot be performed remotely. I hope this study could provide implications for the comparison between The Great Recession, which is referred to as a man-cession and the pandemic recession, which is referred to as a she-cession. Thank you for your time. And with that, I would like to pass it over to our next speaker, Evgeniya Duzhak.

Evgeniya Duzhak

Thank you, Huanan. And thank you to organizers for giving us this opportunity to present our research and also to learn about the newest developments from our colleagues. Today I’m going to present the joint work with Leila Bengali, Mary Daly and Cindy Zhao. And I’m going to tell you why so many prime-age men no longer work. So let me start with the next slide. And the well-known fact that non-participation of prime-age men has been going up for decades. As a matter of fact, if men in 2023, so at the last point of this graph that you see, would non-participate at the same rate as man in 1960, the US labor force would get extra almost 5 million workers. That would be more than enough to alleviate labor market tightness that we see now. Furthermore, as we see on the next slide, prime age men’s non-participation has been getting consistently worse for each generation.

So what you see here are non-participation of silent generation and blue line, then baby boomers, which goes up, Gen X and then millennials. And we see that across their lifespan, each subsequent generation has higher non-participation rates. And for the first three lines, you almost see a parallel shift up. And interestingly, for millennial men, the line looks somewhat different. So if earlier generations non-participation gives us somewhat of a smirk going up, millennial men at least so far give us an impression of a more even smile. So that’s an interesting fact from millennial men. So this rising prime-age men non-participation rate has of course important consequences for the economy. In the short run, it tightens the labor market and in the long run it has negative consequences for the long-run economic growth. In this work, we want to understand what’s driving these gaps and we also see if there are any differences by race and ethnicity.

We look at number of factors on the next slide that will broadly characterize into pull and push factors. So pull factors are drawing prime age men out of the labor force by choice. For example, maybe it could be due to prolonged education or additional education, maybe it’s to take care of their family members. On the other hand, there are push factors that push men out of the labor force perhaps due to disability. So some health reasons or maybe because the skills that this man possess are not in high demand. So lack of jobs can push them out of the labor force. So with this pull and push factors, what we do is a regression analysis that allows us to estimate sensitivity of a decision to be not in the labor force to these different factors. So this approach allows us to distinguish the gaps that policymakers can address from those that might be unlikely targets of policy intervention.

So I’m going to tell you a little bit about each of those factors. And on the next slide I’m going to start with pull factors. So what you see here is the difference in non-participation rates between millennial and baby boomers prime age man. And you see it for each age from 25 to 42 because 42 are the oldest millennials that we have in the sample. The height of each bar tells you how much more millennial men non-participate relative to baby boomers. And the color of each bar tells you the reason that they indicated in their survey for why they non-participate. There are three main reasons that we see. First is schooling because they’re getting some education. Second is caretaking. And finally this other category, green bar is by and large due to disability, but it also includes those that indicate illness or other non-specific factors.

So what’s interesting in this plot, what we see is that if caretaking and disability have a constant impact on being out of the labor force across age span, schooling is more likely to impact younger millennials. And as a matter of fact, at younger ages, that explains almost a third of this gap. And it is schooling that gives millennial non-participation line in the previous slide, this atypical shape where millennial men non-participate at young ages at much higher rates and then it steeply declines and closes the gap with the Gen X men. So if it wasn’t for education, millennial line would’ve looked much more like previous generations line in terms of its shape. So this is a pull factor that temporarily draws men out of the labor force. However, when they do come back, they participate at higher rates and contribute to labor force at lower non participation rates.

Okay, so second factor is caretaking. And our analysis suggests that men that have children at home and another member of the family that is employed are more likely to non-participate. And this effect is getting somewhat stronger with each subsequent generation, which might actually indicate changing norms. Right? Next I’m going to talk about push factors. On the next slide is a disability. And here you see non-participation of prime-age men that indicated that disability is the reason for being out of the labor force. So what we see is that disability as a push factor increases with age for all generations. And of course there’s a somewhat of an increase in that reasoning across generations. We looked at generosity of disability insurance as one of the factors that can impact the decision to be out of the labor force. And we find that the impact is actually quite small.

It is significant, but it’s quite small. And finally, final factor that we consider on the next slide is a skill mismatch. And we know that economy is always evolving. Industry’s landscape had changed quite a bit over the past 50 years. Consequently, demand for skills have changed as well. We proxy for skills with educational attainment and here’s the motivational graph. We look at non-participation rates of two groups of men. Some are very educated, so they have college or more as their education and some are less educated with high school or less. So two ends of the spectrum. So few things jump up. First of all, those with less education, there are non-participation increases with age across all generations. Secondly, those with less education don’t participate at much higher rates. So that’s not surprising I guess for most of participants here.

Lastly, we see that the gaps for those with high school or less are much bigger between generations. So that means that a lot of these gaps that we see are actually due to men with less education. So what we do in our research, we interact education with employment share and goods producing industries and minimum wage gap. And we see that men with less education are more sensitive to changes in industry shares. And not surprisingly, also, they’re more likely to drop out of the labor force if minimum wage is too low. So that discourages them from participation.

So let me just conclude with the next slide, summarize our findings. We see that both pull and push factors contribute to increasing non-participation rates. We estimate the gap between baby boomers and millennial men to be about 1.6 million, 25 to 42-year-old men. Half of them are out of the labor force due to disability or illness, 20% due to schooling, 30% due to caretaking. And our regression analysis allowed us to estimate the sensitivity of not being not in the labor force due to these factors. And we find that skill mismatch and caretaking needs are the most sensitive and could perhaps be the targets of a policy intervention. So thank you for your attention and off to our next presenter, Leah. Thanks.

Leah Gjertson

Thank you. What a great paper. Hi everyone. I’m excited to be here today. I’m Leah Gjertson. I’ll be presenting a paper with my co-authors using a natural experiment to evaluate the effects of subsidized child care on mother’s employment. Next slide please. So our motivation here is really the availability and cost of child care is a key contributor to labor force participation for women with young children. The labor force participation rate, there’s a nine percentage point gap based on age of child, so between mothers with children under five, and then mothers with school-aged children. And that gap for employment based on child age does not exist for fathers. Although as we’ve heard from prior papers today, there’s a whole story to think about there too. But focusing on mothers here and thinking about the child care burden as far as their labor force participation, we have another factor here and those with young children know this already.

Child care is really expensive, it’s really expensive in the US right now. The average cost of child care per child exceeds 19% in median family income. So the reality is that many families are just priced out of market rate child care. So this study uses a natural experiment that occurred in Illinois to measure how the provision of subsidized child care impacts employment and wages of low-income mothers with young children. Next slide please. So just really briefly, the natural experiment that our study is using is there was a data system change that altered the child care subsidy eligibility periods for specific cohorts of program recipients, effectively granting them six months or more of additional subsidized child care without having to do anything. And the program, the additional child care was distributed based on the month that their recertification came due and the jurisdiction that they lived in within the state.

So this is the variation that we’re using for our analysis. Next slide please. So this study is using data from the… Administrative data from the Child Care Assistance program, administrative data from the Unemployment Insurance, UI wage data in Illinois, and then aggregate data from the American Community Survey. Our baseline sample consists of child care subsidy cases that were due for benefit recertification in 2014. And the treatment group is comprised of families that received this additional provision of program benefits by virtue of the month that they came due to reapply. And our control group is families who had the services as usual, like on-time recertification process. We use duration and difference-in-difference models to compute the causal effect of additional program eligibility on child care subsidy receipt, and then on mother’s employment and earnings over a three-year follow-up period. Next slide please.

So just a little about our sample so you can understand, to get some context for the data here. So our sample is 97% female who are about 20 on average, 28 years old with between one and two children with an average age of four to five years old. Mothers had about a 60% employment rate in a twelve-quarter pre-period with average quarterly earnings of about $2,300 in 2018. And the child care subsidy pre-period participation. So in the child care subsidy program is about 35%. Thank you. Next slide. So this first results chart is showing the duration estimate for length of participation in the child care program. The maroon line is our control group and the blue line is the treatment group that received the additional child care subsidies. As you can see, the treatment group experiences a longer duration in the child care program until about 20 months after our treatment intervention when that difference diminishes.

The sharper drops in the survival lines that you can see at six months, 12 months and 18 months represent the timelines of when families would’ve had to reapply to the program in order to stay engaged. That’s why you see those jumps. And that time of reapplication is a break point for when a share of families sees participation in the program. Next slide. So this slide is showing two findings at once. These are a difference-in-difference estimates for the effect of additional subsidized child care on mother’s employment for 12 quarters or three years after our treatment events, and we find a 2.5 percentage point or 4% increase in the probability of mother’s employment and that is statistically significant. And then when we look at earnings, we see about a 5% increase in annual parent earnings, but that effect is statistically insignificant in our models, but we’re seeing a similar direction as the probability of employment finding.

Next slide. So to summarize the results, so this study is examining a federal policy. The Child Care Subsidy program is funded at the federal level and administered by the state that aims to enable low-income single parents to engage in the labor market by making childcare more affordable. And we find that the additional time in the Child Care Subsidy program provided a crucial support to low income working mothers, many of whom would’ve been unable to afford market rate childcare. And specifically we see a five month increase in the median amount of time children spent on subsidized childcare. A 25% increase in the likelihood that their duration in the program exceeded six months and a 13% increase in the sense of margin likelihood of childcare subsidy received for parents. On the employment, the employment earnings, the most interesting ones for this conference, we see a 4% or 2.5 percentage point increase in the probability of parental employment and mother’s employment in our sample and a statistically insignificant increase in annual parent earnings.

So just stepping back and doing two sentences on implications, this really provided stability in the childcare arrangements for these low-income working mothers, which appears to have increased their parent employment. If we extrapolate this to a national gap in labor force participation and assume a constant treatment effect, it could imply that CCDF Child Care Development Fund childcare subsidies were available for all young children. It could reduce the gap in labor force participation between mothers and fathers of young children by 9%. Next slide please. And just taking a brief moment to acknowledge our data provider agency partners and the federal sponsor, which is the Administration for Children and Families, and affirm that the presentation today reflects the opinions of the authors and not of the institutions. And that concludes my presentation and I am so excited to hand the baton to Kristy Buzard.

Kristy Buzard

I’m going to tell you about some research that is pretty closely related to what Leah just told you about, just thinking on different margins about factors that are affecting women’s labor force participation. This is joint work with Laura Gee and Olga Stoddard, and I think that we have some interesting new results here that you’re going to find really interesting. So I don’t think I have to motivate this very strongly today. We know that there’s this persistent earning gaps between men and women, despite the fact that their roles have really been converging in the labor market. And we also know from the work of people like our recent Nobel laureate that… An important contributor to this is the fact that women and especially mothers are concentrated in more flexible jobs. So let me tell you, put some meat on the bones of this fact.

In our own survey we found that about twice as many mothers as fathers indicated that they’d consider child care interruptions when they choose their job. And that’s well over 50% for women. In others’ work, they find that women face more interruptions for household related issues during the workday and that this is associated with a pretty large decline in wages. There’s also some really recent work that I think is really interesting where they have men and women perform similar online tasks and they find that women earn less than men and that 50% of this gap is explained by interruptions for women who have children. And we also have of course the American Time Use Survey results that show us that women consistently spend about 50% more time than men in two parent heterosexual couples. So what we’re going to look at is a previously unexplored source for this inequality.

We know that inequality exists, but oftentimes there’s a tendency to attribute this to women making decisions about wanting to spend more time on care. And that may be going on, I’m sure it is for some people, but we are going to convince you, I hope that at least a significant portion of this inequality is coming from demands external to the parent’s decision making. So what we do is send emails from a fictitious parent to the vast majority of kindergarten through 12th grade school principals in the US. We make a very simple ask just we’re searching for schools for our child. Can you call one of us to discuss? And then we give contact information for both parents. We make sure to send an equal number from the male parent and the female parent so that we don’t have to worry about so much the effect of who sent the email.

And then we randomize the principles into five different treatments. So we have what we call a baseline treatment where we send no additional signal, we just make this simple ask. But then we have four additional treatments where we send a signal of parental availability. So there are four different messages, two each for the male parent, female parent. One saying that I have a lot of availability to discuss or I have limited availability for both genders. And we can combine these treatments along with our theoretical model to tease out some new results on the underlying reasons for why we might get this inequality in demands. So we’re looking at K through 12 schools and we really think of this as one source of external demand. School is one of many places where women might experience more demands than men. The graph that I have for you here is from our own survey of about 300 individuals who work often with families, children, and their parents.

And we asked them, “What proportion of the time would you contact the mother or the father first?” And what we found, it was a little bit surprising to us actually, is that there wasn’t any category of institutional worker here where they were going to call the father more often than the mom, right? So we think this is pretty widespread. We’re going to focus on schools because 40% of US households have a child in kindergarten through 12th grade. And then you think about all the ones that have preschool age children as well, and this is a really large portion of the population. So what do we find? Well first, luckily principles do respond to this request. About 20% of the principles we contact call at least one of the parents. Then our main question here was are they more likely to call the mothers? And the answer is yes.

We find that about the 12 out of that 20% call the mother versus only 8% calling the father. And this is moms getting called about 1.4 times more often than dads. Now interestingly, we ran some variations on our simple availability messages where we added in, for instance, saying the parents both work full-time or they both want to be involved equally in the decision. And we really found no real differences at all, which we found pretty surprising. So we can come back now and think about the sources of this inequality using our theoretical model. And the main thing that we can look at here really cleanly are the beliefs of these decision makers about the availability of the parents. And we find that decision makers absolutely do believe that mothers are more responsive and more available than fathers, but that only accounts for about half of the inequality that we see.

The rest go into a residual term that’s going to capture anything other than those beliefs that I’ve talked about. So any other kinds of beliefs, preferences, etc. So we can’t dig really into that too deeply, but we can tell you that gender norms seemed to be driving this. So first was some qualitative evidence from our survey. When educators said that they would call their mom first, we asked them why and they would say something like, “Mothers are more caring and nurturing, they’re more polite, they’re more excited to participate.” That’s on the qualitative side. On the quantitative side, we’ve just correlated this propensity to call the mother over the father with various proxies for gender norms. The one that we get the strongest results for is whether this is a religious school or not. We have this at the school level. So this is really precisely measured, but we see that our other measures at the county level don’t look quite as strong.

I think these are just a little bit noisier, but we see this across labor market outcomes, rural versus urban, religiosity again, and conservative political beliefs. The other thing that very clearly matters here are these availability signals that we send as well as who is sending the email. So verbal and nonverbal signals. Our messages definitely change who gets called, but there are some real limits to how much action parents might be able to get off of sending these kinds of message when they indeed have the opportunity to send this kind of message. So let me show you a graph here. There’s a lot going on. So let me explain. On the left-hand side, when the email is sent from the male parent and on the right-hand side, we have with the email being sent from the female parent. Going from left to right within each of those we’re going from messages that say that the male parent is really highly available over to the female parent being highly available.

And orange is for the mother is being called, blue is for the father. So we see that these messages of availability definitely push the response rates or the choice of which parent to call in the direction that you would expect. What is interesting here perhaps is that there’s significant asymmetry, right? If we look in the baseline message where we don’t say anything about availability, if the dad sends the email, the dad’s going to get called back about 80% of the time. At the same time, if the mother sends that simple message, it’s almost every single mother who’s getting a call back. If we just want to look at another one as an example, when we say that the father has a lot of ability, we see that when dad sends the email 13% of the time, they’re still going to call the mom. But if mom sends the email with that message, almost 40% of the time mom is going to get that call even though the message says, “Call this other person.”

So what are the implications here? We think that this is new evidence on gender inequality and that it’s pretty clear evidence that mothers are fielding more child-related requests, and these are coming externally to the choices that the mother makes. We think it’s probably a lower bound on the total demand gap in part because we are balanced on who sends these messages and that’s probably not terribly realistic, but we’ve seen there’s other forms of care that women are more heavily involved in. So this is likely to be maybe a canary in the coal mine situation. So if we think about what might you do here if you wanted to address these differences? I think it’s pretty clear and hearkens back to what others have said already, that to get rid of this inequality, systems need to change and social norms need to change. So what are some first steps in that direction?

So there are some things I think we’ve shown here that parents can do if they’re in a situation where they get to make the contact. That’s often not the case, but you can choose who does that initial outreach. You can send messages about availability and let me tell you, parents come up with some really interesting ways to try to get this balance that they’re looking for, including things like getting one child-related phone number and sharing that phone or phone number back and forth. I do know that we’ve heard a lot of stories from fathers who really want to be involved as Dr. Reeves shared, having a really hard time getting the schools to call them. We think about the institutions who are making these demands. We think the primary avenue for improvement here, maybe the lowest hanging fruit, is to think about making their contact systems more flexible. Most of them do list a primary contact and that really pushes us towards a hundred percent of the calls going to one parent or the other.

And what we’re seeing, what we’re hearing is that today’s parents often really want to share this work equally, they both want to be involved in their children’s lives and these kinds of older model of contact system is keeping them from being able to do that. But bottom line here, if we want parents to be able to share out the work of caring for their children equally, we have to make the workplaces and workplace policies more flexible for everybody. Thank you. I’m going to pass the baton again on over to Chandra Childers who will give us her perspectives on this whole interesting set of topics.

Chandra Childers

Thank you so much. And I really enjoyed the papers that everyone is discussing today. So we’ve just heard from our authors about the very interesting and very important work, and I want to discuss the overlap between the papers and highlight the facts that although each of these papers address different issues and different groups of workers, we know that in reality there’s a great deal of overlap across these issues and across groups. So as context for the way that I’m thinking about these papers collectively, consider an analysis of the worker shortage that was published by the US Chamber of Commerce last month. They found that there are more than 2 million more job openings than there are unemployed workers looking for jobs. And this doesn’t not even take into consideration the many barriers that workers and would be workers face when they want to work. And all of the papers that we have heard today that we discussed today, they have applications for this worker shortage.

The set of papers that our authors have just presented to make clear that gender, race, class, geography, and other demographic characteristics shape our labor market experiences and outcomes. They shape who has access to which jobs or to any jobs at all. For example, the pulled out or pushed out paper investigates declining labor force participation across generations. The authors find that each subsequent generation of prime age men, that’s men aged 25 to 54, that they have lower and lower labor force participation rates. The factors they focus on is whether prime age men are pulled out of the labor market to obtain greater education, job training, or to provide care for a family member or whether they are pushed out either by lack of skills, a skills mismatch or disability.

And one of the key findings that I want to highlight here is that some of the prime age men with low levels of education, that they’re increasingly over each successive generation going from the silent generation to boomers, to Gen X, to millennials, each are less and less likely to have the skills demanded by an economy that we have that’s already experiencing a shift in its industrial mix. They highlight, for example, the decline in well-paying manufacturing jobs that paid well without requiring high levels of skill. I think this was especially important. They highlight that for prime age Black men who are more likely to be pushed out of the labor market due to a skills mismatch, while prime age White men are more likely to be pulled out of the labor market as they are increasing their education or job training. So it’s really important to understand that while all of these factors impact men across the board, different factors impact different men.

And thinking about this in terms of policy, I think that that fact alone presents us with a lot of opportunities for policy intervention. And here I want to focus specifically in on some recent federal legislation, some recent policies. For example, the Bipartisan Infrastructure Law, the Inflation Reduction Act, the CHIPS and Science Act. These are policies that promise to increase these very types of jobs that had been in decline. And they include policy levers that policymakers can utilize to begin to address the declining labor force participation, especially among those populations that have low skill levels. And this can increase their skill levels. So there’s great support, for example, for registered apprenticeships and pre-apprenticeships.

And this is a critical component of the workforce development system and it allows workers to, as they say quote, earn as they learn, because they’re paid from day one while they’re trained to become the future workforce that we need. It allows workers to gain in-demand skills without having to incur student loan debt. It builds our pipeline of highly skilled workers and it ensures that employers have the workers that they need. So this creates a win-win situation. The report also found that the gap between the minimum wage and the average wage, where that gap was larger, that you had greater non-participation rate. And so there, the obvious policy there is raising minimum wages and index it to inflation and that will ensure that the wage keeps up with the cost of living. This can be done either at the federal level, we see our federal minimum wage where it’s been since 2009 or at the state level. We know that 30 states and DC have already implemented a higher minimum wage than the federal minimum wage.

And 19 of these states have indexed it for inflation. The remaining papers, again, highlighting a range of disparities in the labor market along the lines of race, class and other characteristics have a primary focus on gender inequities. And one provides this perfect example of the pernicious impact of historical gender norms that hold women back, even as the roles within the home and within the broader economy continues to evolve. So the data examining gender differences in the labor market. Transitions over the business cycle, it shows us that women are becoming more attached to the labor market as they increase their levels of education and gain more work experience. But another paper also examining the demand for parental involvement highlights ways that women continue to face challenges in the home and in the workplace when outdated gender norms about the proper role of women and men create obstacles for women as they’re doing this.

For example, when schools are confronted with issues concerning children, as you’ve heard in the presentations, they’re more likely to reach out to the mother than the father, requiring more time and potentially being more disruptive of the mother’s work relative to the father. The authors report that school personnel themselves say that if a child needs to be picked up from school, that they would be more likely to call the mother. They found that even when parents indicated that the father had more availability or the mother had less availability, there was a ceiling on the number of calls going to fathers but not to mothers. They highlight how this leads to also increased occupational sex segregation, which is a major factor in inequality to cross the labor market, including in the gender wage gap.

And women have to consider these potential disruptions and the demands on their time when they’re choosing jobs more often than men have to take this into consideration. And this also leads to crowding women sometimes into low wage jobs. Another paper looking at the impact of subsidized childcare on the employment and earnings of single mothers and finding that by subsidizing childcare for women who could not otherwise afford it, it increases their employment and it looks like it also may lead to wage increases. These papers suggest several ways that policy can help reduce these gender inequities. First and directly addressed in the papers is ensuring that families have access to high quality, affordable childcare and early education. And this is beyond just subsidizing childcare for low wage workers.

A lack of childcare is a key factor in the worker shortage that businesses are facing. And it’s keeping workers, particularly women, single parents out of the labor market. And it’s about providing that subsidized childcare for low wage workers. But it’s also about ensuring that there is the needed supply of childcare workers, especially after the pandemic. And this will require investing in these workers, raising their wages, improving the quality of these jobs. But because most families cannot afford to pay the cost of the childcare that would be required to give childcare workers a living wage, it will require public investment. It’s also important to make choices to make sure that women are able to make free choices about whether or not they want to leave the labor market when they have children and be stay-at-home parents or whether or not they want to balance work and family.

As the labor market transition paper showed, while women were more likely to move into the labor market as the economy declined, they were less likely to do so when they had small children. And I want to highlight one other policy here, and that is about paid family and medical leave and other flexible policies, but it’s crucial that these families, that all workers have access, both men and women, fathers and mothers. That they have it in equal amounts and that they’re all encouraged to take the leave and use the leave as a way of moving us back toward… I shouldn’t say back. Toward a place where the role of men in families is appreciated and we can begin to redefine those norms so that the role of men and their relationship with their children is appreciated.

So thank you. That’s my take on the set of papers that we were reading, and I would now like to invite our authors and our framer back to begin to address some of the questions that we have coming in from our audience. All right, fantastic. Okay, we have our first question. Our first question for Dr. Xu, could you please explain how you constructed the business cycle measure? What are the likely weaknesses of this measure and its implications on the findings of this study?

Huanan Xu

Thank you very much for this question. The business cycle measure is constructed as a state level measure. It is the difference between the state level unemployment rate and the national natural rate of unemployment. So the data are publicly available from Bureau of Labor statistics, and it is matched to my panel data set for the current population survey on basic monthly files for all individual workers on the state level and at a month’s frequency. Yes, of course there is likely weakness of this measure. It is not mentioned in my presentation, but there are several robustness tests following the… In the fall paper, I use an employment to population ratio. I use length period, unemployment rate, also a shift share type of unemployment rate instead of the current measure, which is mentioned in the presentation. All results are robust to different measures of the business cycle. Thank you.

Chandra Childers

Great, thank you. And then we have a question for Evgeniya. We’ve got for the labor force participation rate of older men, have you considered the role of gender role attitudes about occupations as a factor that they may be less likely to take a job in an occupation that is seen as women’s work?

Evgeniya Duzhak

That’s a very interesting question indeed. In our work, it would be difficult to measure this type of attitude to be honest. We do see though, is that yes, attitudes are changing across generations as we can measure, for example, with caregiving. So more and more men are taking on that role. However, we did not look at that particular factor that you asked, but we’ll think about it. That’s an interesting angle.

Chandra Childers

Also, any of these studies evaluate where the men might be. They look at incarceration rates, sorry, I cannot read here, how incarceration rate influence availability. And does the research provide information as to how and where men are earning wages when they do not participate in the labor market?

Evgeniya Duzhak

Well, I can answer about wages a little bit. So as we saw from our research, half of the men that indicated that they’re not in the labor force are so because of disability, well almost a half. And we know that they do get disability insurance. So that’s one little piece of information.

Chandra Childers

All right. Okay. So Richard, in the beginning you said that the family is a labor market intermediary. Can any of you talk about what we learned today about… Sorry, this is jumping. About what we’ve learned today about what we need to have in place to support families in allocating their labor market potential in the best way. And I think that can probably go to anyone in thinking about that.

Richard Reeves

I’ll say a couple of things on this. I think the first thing is that we tend to focus on the family side of childcare, how do we make workers, how do we make families more market friendly rather than thinking about how do we make markets more family friendly? And I think that the real work here is on the side of labor market institutions, and I think this is Claudia Goldin’s work too, that actually just creating careers, jobs, and most importantly career trajectories that are not so hostile to household production. I think that’s really where a lot of the energy has to go now, rather than us constantly trying to fit families into this quote, ideal worker model, we should instead be asking more of our labor market institutions. And also just while I’ve got the mic, it relates to the previous question, but our institute, the American Institute for Boys and Men, we’ve just published a paper on the declining share of men in mental health professions.

We have another one coming on education. But I think it is striking how as we have to some extent, we have to some extent desegregated historically male jobs. We are moving exactly the other way with historically female jobs. So teaching, social work, psychology are becoming dramatically more female over time. And I think that has all kinds of problems, not least in terms of the message it sends about what are the appropriate roles for men. It’s getting harder and harder to persuade men, but those are jobs for them because they are becoming more and more female dominated. And I don’t think we’re paying enough attention to the segregation, gender segregation of the labor market that’s going on.

Chandra Childers

Thank you. Did anyone else want to respond about supporting families in allocating labor?

Kristy Buzard

So I can add a little bit here. It’s mostly just based on anecdotal conversations that we’ve had as we presented this work about the external demands. But I have to second what Dr. Reeves was saying about the flexibility, making work more family friendly. The way that the parental demands are coming and just how hard men have to work to be equally involved in their child’s education is one more thing that pushes. Well, if we are going to have… We don’t have a lot of flexible jobs in the economy, the flexible jobs in the economy tend to be lower paid. So we need one high earner and that’s typically for a bunch of reasons going to be the man. So until we can find a way to make more jobs more flexible and actually change the availability of men, it’s going to be hard to change the norm about who you should call as your knee-jerk.

Chandra Childers

All right. Leah, with child care being so expensive, where would the money come from to subsidize child care into the future indefinitely? Is there a political appetite for this in any party or any level of government?

Leah Gjertson

Chandra, that is quite the question. I’ll say it feels about more than several levels above my pay grade, but I think there is an interesting thing to say here with current federal investments for child care. So my paper focused on child care development fund subsidies, which is a current federal mechanism. It’s been ongoing for a while that flows from the feds to the states. In the pandemic with the American Recovery Act, a large investment, I think 40 billion went to states to fund child care. That money ended last year. And so we’re starting to see a lot of ripple effects as those monies were used to shore up the child care system and providers throughout the states. So the political appetite and where that would come from, it’s outside of my purview. But I think we can look at the recent pandemic era investment as what it looks like when you do put more money in.

It’s too soon for all of us here, like the researcher folks to document what happened yet. But there was a recent example of a big investment in the child care field and then adding only that. The other piece, and this is from other work I’m doing, and Chandra, you alluded to it in your comments too, a big constraining factor here is the child care workforce. So there’s like, can parents afford it? But there has to be enough slots for the children. And the recruitment and retention of workers in the child care industry is a big limiting factor right now.

Chandra Childers

Yeah. There’s another related question here. During World War II, there was a push by the federal government to provide child care for women working in factories. Would a program similar to this alleviate some of these issues? And I’ll put that out there for anyone, not just to you.

Leah Gjertson

I’ll say one thing. I don’t feel super qualified to answer this question, but it is… I mean, it was true that they did physical place-based child care options sponsored by the government. Most of what is operating now, at least from the federal to state level is that the voucher child care subsidy operates as a voucher-based system. So families get a voucher that they can take to any provider who will take the subsidy and lacks the brick-and-mortar child care. So that would be, we have done that before in the US, it’s not really representing what’s happening now, at least outside the local level. It could be an option. Not commenting at all on where the appetite for that might come from and where the funding dollars come from. But I’d be very interested if any of the other panelists have reactions to that question.

Kristy Buzard

I would just tag onto that and the intersection between your work and our work is that a real concern is that you’ve got to have the child care there. But even once the child care is there, caring for children is a really complicated thing that involves a lot of surprises and… You can’t control when a kid gets sick. And if the daycare that you have is across town and you’re on public transportation and you have a 15-minute break, the improvements that we would have by getting the child care locations close to where the low income parents are working would be really important here because all child care is not created equal, right? Where it is, how robust it is, what kind of options you have for dealing with emergencies, what kind of backups you can have, all are going to play into whether people are able to actually take advantage of it.

Chandra Childers

Yeah. And I’ll add to that, I mean, I don’t have an answer, but talking about the complexity of child care, I know some of the work I’ve done in the past, it’s looked at women moving into the trades. Well, if you’re in construction, you’ve got to be at that work site before many child care places are open. And again, as I did indicate in my remarks, it’s not just about subsidized child care for low-income workers, it’s about making sure that everyone has access. And I’ll add not just child care, elder care, a lot of the things that are keeping people out of the labor market, it’s not just child care, but it definitely is a system that we really do need to think more about. And I think business could be a big part of the answer to that because the demands of business might address that appetite bit a little bit more.

Does this information take into account people who have been justice involved or people who may have a criminal background? I’m not sure if that goes with the child care bit, but I think there’s another one. Were there any characteristics of the non-participation members that could be directly connected to employer practices beyond recommendations for child care subsidies, concern that many employers hiring practices continue to screen out potential talent despite upskilling and educational efforts? I think I’ve probably butchered that question to the point where… Yeah. So employer practices in the hiring process. Okay. All right. So that looks like that’s about… Well, and we’re also about at time, the questions that we have. So I think we can bring our Q&A to an end, and I can turn this back over to Jennifer.

Jennifer Fernandez

Thank you so much for that. And thank you everyone for participating and for your questions from the audience. On behalf of the organizing committee, I just want to acknowledge all of our participants for their time and insights shared during today’s discussion. Please join us tomorrow at the same time to continue the conversation on uneven outcomes in the labor market. We’re going to focus on firm level characteristics and worker outcomes. We’ll open the day with remarks from Michelle Bowman, member of the Board of Governors of the Federal Reserve Board, and we’ll continue with the new federal research on geographic inequality and labor market indicators. Registration links and a full agenda for each day are available on our conference website. We look forward to seeing you all tomorrow. Thank you.