The Region

Interview with Hilary Hoynes

Berkeley economist on food stamps, recessionary effects on labor market segments and the importance of poverty research

Douglas Clement | Editor, The Region

Published June 1, 2017

Hilary Hoynes
Hilary HoynesPhoto by Peter Tenzer

The War on Poverty was launched over half a century ago, with a host of programs intended to ease the plight of the poor. Food stamps, Medicare, Medicaid, Head Start and programs for job training, adult education and equal opportunity business lending were launched or strengthened. Long before that, the New Deal initiated Aid to Families with Dependent Children, guaranteed pensions, unemployment insurance, the Works Progress Administration and other programs—creating a “social safety net” to protect Americans from economic poverty and related disadvantages.

UC Berkeley’s Hilary Hoynes has devoted her career to understanding the impact of such efforts. How do they work in the real world? To what degree have they met their goals? Have they dulled incentives or had other harmful consequences? How could they be improved?

With careful technique, cutting-edge methods and ingenious use of natural experiments and big data, Hoynes has examined government nutrition programs, cash assistance policies, education efforts, work incentives and health care initiatives. She studies multiple angles of the same program or policy—demographic differentials, effects on housing and family structure, impacts on human capital accumulation, health and labor supply.

In recent years, she’s focused on analyses of how these safety nets perform during business cycles—to what extent do they soften the harm caused by economic downturns, and do they perform uniformly or are they less effective in deeper recessions? Do they help some demographic groups more than others?

To a degree, Hoynes says, she was destined to study the economics of poverty. Her mother worked at the University of Wisconsin's Institute for Research on Poverty; her father was an economic historian at Harvard; her grandfather, too, was an economics professor.

But her vocation is more than familial. “As others have said,” she observes, “a society should be judged, in part, by how it takes care of its most disadvantaged. To do a good job of that, we need to know what influences poverty.

But I also want to understand what poverty generates. … What does childhood poverty mean for a child’s life trajectory? To what extent are we in a world with an even playing field, with equal opportunity?”

Interview conducted March 22, 2017.

Later-life impact of the Food Stamp Program

Region: You’ve done a great deal of work on the nutritional status of low-income populations and the government programs that pertain to them. Your 2016 paper in the American Economic Review examines the relationship between early exposure to the national Food Stamp Program and outcomes later in life. Though it’s a massive program, little was known about its efficacy prior to your research.

What were your key findings about food stamp use and later outcomes? And how did the program’s gradual rollout across U.S. counties enable you to do the research?

Hoynes: Food stamps are a central part of the U.S. social safety net, and it’s a means-tested program—meaning that you have to have low income to participate. And, remarkably, it has remained fairly intact over the past 20, 30, 40 years while other parts of the safety net for low-income families have been restricted and reformed.1 Also, it’s federal—run out of the USDA—so it doesn’t vary a lot geographically. That’s helpful because it really provides a uniform floor across the United States. In very poor areas, even in states that don’t tend to provide a lot of assistance for the poor, food stamps create a kind of universal minimum across all places.

It does, however, create challenges for doing evaluation because it doesn’t vary much across space, and it also hasn’t varied much over time. It’s been quite challenging for researchers to use frontier methods for causal identification to evaluate what this program does. There are piles of research that study food stamps, of course. People do quite reasonable things to find control groups to compare to those who are on food stamps, but at the end of the day, for the most part, those people who are on food stamps are more disadvantaged. It’s difficult to use that observational data to learn something meaningful about food stamps.

Region: But you had sort of a natural experiment.

Hoynes: Right. Food stamps started under President Kennedy. His first executive action was to start some pilot programs for food stamps. He, famously, visited Appalachia when he was running for president and apparently was very influenced by the poverty and deprivation that he saw.

Those pilot programs eventually led to passage of the Food Stamp Act in 1964. But it wasn’t until 1974, 10 years later, that subsequent legislation compelled all areas to implement food stamps. In that 10-year interim, Congress essentially said to U.S. counties, “We’re going to appropriate these funds for this program. If you’re interested in implementing this program, please apply and we will fund them, subject to our appropriation.” Meanwhile, there had also been a very influential documentary called Hunger in America during this time.

This resulted in gradual rollout of food stamps across the almost 3,200 U.S. counties.

Region: Matthew Gentzkow did something similar in research on TV viewing and children.

Hoynes: Exactly! The “rollout design” is one of the tools in our tool bag for doing evaluation. And, of course, we need to convince ourselves that that rollout was as good as random, that it wasn’t systematic, that certain areas had the rollout earlier than others. In our first paper on this, my co-author Diane Schanzenbach and I really dug into the nature of the rollout and the political economy behind it. At the end of the day, we were convinced that it was as good as random which places got food stamps earlier rather than later.

In our early work on this, we looked at more contemporaneous outcomes. For example, in work with Douglas Almond and Diane Schanzenbach, we compared women over time who gave birth in counties that had food stamps with those in counties that didn’t have food stamps. And we found that women in counties with food stamps had babies with higher birth weight, and we found lower incidence of the critical marker of low-birth weight at 2,500 grams.

That was our first evidence that health is an important outcome to analyze to see, overall, what our nonhealth safety net programs are doing.

In the paper in last year’s AER with Douglas Almond and Diane Schanzenbach, we took a long-term evaluation lens to this program. Food stamps rolled out in the ’60s and ’70s, so the cohorts affected, or not, in early or late childhood are in their early 50s today. This presented an opportunity to address a question that no one has ever looked at before in the context of food stamps: What are their long-run benefits?

Just to back up a little bit—the first generation of economic analysis of programs like cash welfare, food stamps, Medicaid, these kinds of programs measured the contemporaneous distortion effects of these programs. In optimal policy design, we’re thinking about trade-offs between the protection that a program provides and the distortion that takes place. It’s an equity-efficiency trade-off that underlies whether a program makes sense to have in place or maybe should be adjusted. As economists, our first generation of work is usually measuring the distortion or the efficiency loss.

What has taken much longer, I think, is to measure the protective effects, the benefits of the program. And some of those benefits take time to emerge.

Region: And labor market outcomes could be one of those long-term benefits.

Hoynes: Exactly. What we’re often interested in is, what are the impacts on the next generation? A lot of people are doing work of this type, trying to quantify the benefits of the social safety net. People are studying Medicaid, for example, and the Chetty et al. paper on “Moving to Opportunity” looks at the long-run benefits.

We had observational data on people in their 40s and 50s, and we knew where and when they were born and what sorts of family conditions they were born into. We could link that up with the data we have on the food stamp rollout in order to create a measure about, how old were you when the food stamp program was implemented?

Region: Then it wasn’t panel data? You don’t follow specific individuals over time?

Hoynes: Right. We couldn’t in our data know precisely which families were on food stamps, so it’s sort of an indirect estimate. But we know whether food stamps were implemented when these individuals were 2 or 4 or 14 or 20 years old. We essentially analyzed the data within that lens: How old were you when food stamps were rolled out in your county?

The headline finding was about health. We measured metabolic syndrome, which is essentially a range of conditions including high blood pressure, diabetes, heart disease and obesity. And we related the incidence of metabolic syndrome in adulthood to how old individuals were when the food stamps program was implemented in their county at birth. And we found that the more exposure to food stamps that a person had, the lower their risk of metabolic syndrome in adulthood.

In particular, the gains were greatest if the food stamps program was implemented before an individual was 3 or 4 years old. That period between in utero exposure—prebirth—to those first three or four years of life, was the age range where having more exposure to food stamps available led to a more dramatic reduction in the incidence of metabolic syndrome in adulthood.

Region: This sounds like an epigenetic influence, similar to Janet Currie’s research findings.

Hoynes: Exactly. It’s very much connected to Janet Currie’s work, but what’s interesting, what we maybe add to that work that Janet and colleagues have done, is that a lot of the work that Janet Currie really brought into economics focuses only on the in utero period. And we didn’t really know very much about the period after birth.

Hilary Hoynes
Photo by Peter Tenzer

Lab studies on rats suggest that long-term benefits of nutritional interventions in utero seem to also result from interventions in the postnatal period. But we’ve never really had a good experiment to evaluate that in the real world. In a broader sense, I think what we contribute is the idea that early nutrition matters, but it isn’t just what you come into the world with at birth, but nutrition in early life also seems to have really important preventative effects in the long run.

Then we also looked at effects on human capital outcomes. We didn’t always have as sharp statistical precision as we had for the health outcome but, generally speaking, our analysis tends to show an improvement in human capital long term. And, in particular, leading to improvements in educational outcomes, but concentrated among women and not men. That is, we didn’t find statistically significant impacts for men. In short, we found that better nutrition in early childhood leads to human capital improvement and better outcomes in adulthood, but that finding was limited to women.

Predictors of food insecurity

Region: In another 2016 paper, you explore the differences between households that do and don’t report very low food security for their children. What does “very low food security” mean, and what did you learn about its predictors? Beyond low income, what are the correlates of childhood food insecurity?

Hoynes: The USDA defines food security (and conversely, insecurity) in a rather straightforward way. They ask a series of questions and count the number of affirmative answers to those questions, and depending on how many yeses you give, you get placed into different categories. The questions range from more moderate things with a higher incidence like, do you worry about running out of food before getting money for more? Or, did you cut the size of your meals or skip meals because there wasn’t enough money for food? And then it moves toward more extreme outcomes like, were your children ever hungry, but you just couldn’t afford more food? Questions like that.

There’s a first set of questions that are asked about the household, and then there’s a second set of, I think, 10 questions and then another eight questions specifically about the children. So you get two measures, the incidence of low food security and of very low food security. The incidence of very low food security among children is quite low—about 1 percent of kids.

But we know that food stamps and the other food nutrition programs very clearly lower the incidence of food insecurity. That’s something that most every study that examines the effect of food stamps finds. It’s a contemporaneous study, so unlike the one I was just describing, when we look at the long run, it’s taking folks who are currently receiving food stamps, using your best design you can to try to get some quasi-randomness there, and that seems to fairly consistently show that these food nutrition programs reduce food insecurity.

It’s a little bit more difficult to see whether or not food stamps lead to improvements of health in a contemporaneous way. That seems a bit less clear, but food insecurity is a standard measure that the USDA reports every year, and it’s a measure of deprivation that’s not income-based; it’s a little bit more qualitative, and it’s highly predictive of adverse outcomes. And as you would not be surprised to hear, probably the biggest predictor is household income. The lower your income, the higher your risk of food insecurity. It’s not that surprising, but it’s very apparent.

Region: But you found correlates beyond that.

Hoynes: Right. First, it is worth pointing out that our analysis is more descriptive as opposed to causal. But we found that holding income constant, a household was more likely to have very low food security if the household head was female or disabled. Also, having more children ages 13-18 led to higher rates of very low food security, suggesting that teenage children may put greater stress on a household’s ability to provide food security for them. We were rather surprised by the large predictive power of poor mental health—leading to much higher rates of food insecurity.

Region: It makes sense, though its importance hadn’t occurred to me.

Hoynes: Yes, it makes sense, and it seemed to be there independent of income. Quite interesting.

EITC and CTC

Region: With Jesse Rothstein, you studied two provisions of the federal tax code that are explicitly designed to transfer money to low-income families, the Earned Income Tax Credit (EITC) and Child Tax Credit (CTC). You evaluate the success of both programs in meeting three goals: redistributing to those in need, preserving work incentives and maintaining low costs.

Can you briefly describe the programs and how they measure up to those three goals?

Hoynes: In a broader sense, we’re thinking about the social safety net for low-income families, based on how much we spend on them and how many people were removed from poverty due to them. The two most important such programs are the Earned Income Tax Credit and food stamps. We’ve talked about food stamps, of course, and the EITC is the other thing I’ve been doing a lot of work on.

The EITC is the most important anti-poverty program for families with children in America. It removes the most children from poverty, and it’s organized as an in-work benefit rather than an out-of-work benefit.

Welfare, for instance, is an out-of-work benefit, meaning that it’s providing a floor that your income is not to fall below; you get your maximum benefit if you have no income, and benefits phase out as your income goes up. It redistributes income to the most disadvantaged, but does so in a way that discourages work. That’s just an inherent feature of out-of-work programs.

The whole idea of in-work programs like EITC is to respond to that and say, “Well, American voters would rather have a program that redistributes while encouraging work, not discouraging work.” The EITC operates as an earning subsidy on incomes up to about $14,000. For every dollar that you earn, if you’re a single mother with two children or a married couple with two children, for every dollar that you earn up to about $14,000, you get 40 cents added to that dollar through the EITC. It’s a quite powerful increase in your after-tax wage.

It still needs to phase out or everybody would get it, so there are some negative work incentives that are faced by higher-income workers at levels where the EITC phases out: between about $15,000 and $40,000—or $18,000 and $45,000, depending on your family size. And it’s phased out at a rate of about 21 cents on the dollar. So, if you earn an additional dollar, your EITC is reduced by 21 cents, a gradual phase-out.

Research shows that this program design has a dramatic effect on employment. When the EITC expands, you see more low-skilled workers, particularly single mothers, in the labor market. It has a very powerful effect on transitioning people from out-of-work to in-work. And in so doing, it lowers poverty rates, not just because you’re giving households a tax refund at the end of the year—and of course, if you give someone money, you’re going to reduce poverty—but just as important is the fact that by encouraging work, earnings go up in the household, and that also reduces poverty. It generates a roughly 2-for-1 reduction in poverty for every dollar of federal spending, and that’s very efficient.

Getting back to those goals you mentioned, the EITC encourages work and redistributes income. And the lowered cost is basically about economies of scale. It does redistribution within the tax code, rather than a sort of brick-and-mortar social welfare operation that is the model of the state-based social safety net.

Region: Where you have to set up a small bureaucracy just to implement it.

Hoynes: Right, where the government has to set up offices, clients have to go to those offices, staff have to be hired and trained to administer the program. The flip side of that is the less you spend on administration, the more the risk of noncompliance. The same thing is true in our income tax code more generally.

That’s the EITC. And just very quickly, the Child Tax Credit is very, very different. The government spends about the same amount on the two tax credits, but the CTC operates at higher incomes, very much through the middle and upper-middle classes. If you’re a married couple with two kids, you get the child tax credit at incomes up to $170,000 a year. So it is not a targeted program and does not have very positive redistributive features. It has important anti-poverty effects at the very bottom of the income distribution, but most of the spending on the CTC is accruing to the middle and upper-middle class.

There might be some fairness principles that justify the presence of a child tax credit, but it certainly doesn’t satisfy our goal of redistribution, and it doesn’t seem, per dollar spent, to be encouraging a lot of work. While they’re talked about together, the EITC and CTC are really very different programs.

Until I wrote that paper with Jesse, I had no idea how expensive the CTC was and no idea how far up in the income distribution it went. In my view, it’s not a very worthwhile use of resources.

Recessionary impacts on the labor market

Region: You mentioned some of your work on the Great Recession. You wrote a 2012 Journal of Economic Perspectives article looking at which demographic groups suffered most in the labor market during recessions.

What did you find? Which groups have been most affected by recent recessions, and did the Great Recession significantly differ from others in this respect?

Hoynes: This research with Doug Miller and Jessamyn Schaller looked at business cycle fluctuations back to the early ’80s. We had the big business cycle shock in the early ’80s, another in the early ’90s, the small one in the early 2000s and then the Great Recession. We basically looked at how a given labor market shock gets filtered through different demographic groups—by gender, by education, by race, ethnicity and age.

We discovered a very persistent finding that didn’t look different in the Great Recession: The groups that are most impacted by labor market fluctuations are low-education groups, young workers, minorities and men.

Hilary Hoynes
Photo by Peter Tenzer

Before doing that project, I had predicted that the Great Recession would look different from the others. In particular, I was expecting that patterns would look different in terms of gender. In 1980, a much smaller share of women was regularly attached to the labor market, and we know one of the most important labor market features of the 21st century is the growth of women in the labor market. I naively thought that women in the Great Recession labor market would look a lot like men. But we found that they are not equally affected—in the Great Recession as in the 1980s recession, men are more impacted by the macro job losses than women.

After a closer look, it makes more sense. Women are participating in the labor market at much higher rates than they were in the early ’80s, but they tend to be concentrated in the same industries as they were before.

Region: Services, for example.

Hoynes: Right, they tend to work in services, and in state and local government, which have relatively stable employment trends. On the flip side, men have higher rates of participation in highly cyclical industries such as manufacturing and construction. I think that our finding is partly reflecting a story about industry.

We then moved on to analyzing how changes in the social safety net—like the growth of the EITC and the contraction of welfare through welfare reform—how those massive changes in the social safety net that particularly affect low-income families with children affected what happened to family incomes as we moved through the Great Recession. That was the question that sort of teed up several related papers that I’ve worked on with Marianne Bitler.

When you and I were discussing the EITC just now, we talked about its goals: redistribution and encouraging work. Well, the problem is that the social safety net is built around work. What happens when you don’t have work? What is the social safety net then? And, essentially, what we learned in the Great Recession is this: Welfare reform greatly reduced the social safety net that’s available to people who are not working and had irregular work in the past so they don’t have unemployment insurance.

What you see in the Great Recession is that extreme poverty—having income below 50 percent of the poverty threshold—was much more volatile than we would have expected from prior economic cycles. But less extreme poverty—income below 100 percent of the poverty threshold—seemed to be more protected by the social safety net in a way that was similar to prior experiences. So, while the poor are always going to be impacted more in recessions, lower skill levels are more vulnerable.

Our question was, to what extent is the experience of the poor during the Great Recession different from earlier recessions? Of course, the Great Recession led to historic increases in unemployment rates, but we can use the available data to ask, “How does a 1 percentage point increase in unemployment translate into increases in poverty in the Great Recession, and how does that compare to the same change in an earlier recession?” And the answer there was, an unemployment rate rise led to greater hardship for the very most disadvantaged in the Great Recession. Exploring what was happening to the social safety net and connecting the dots, we conclude that the greater vulnerability for the most disadvantaged in the Great Recession is due to welfare reform and the loss of cash welfare. The EITC could only help you if you’re working.

The Great Recession and child poverty

Region: In a more recent paper, you examine the impact of the Great Recession on child poverty and the extent to which the social safety net softened the recession’s adverse effects.

What did you discover about the recession’s impact on children, the degree of protection provided by the safety net and differences, if any, among demographic groups?

Hoynes: This work was with Marianne Bitler and Elira Kuka, and what we learned was really important in the Great Recession was the food stamps program. The fact that food stamps were stable was critical; actually, as part of President Obama’s stimulus package from 2009, the government temporarily increased the food stamp benefit. You can see that traced out in terms of mitigating the potential increases in poverty that we would have seen if that had not happened. We can see that food stamps really helped.

We also learned that what was really absent in terms of providing safety net protection was cash welfare. Cash welfare is funded at such a low level that it will never get a family all the way up to the poverty line. It’s funded at between 30 percent and 50 percent of the poverty line, so it was this extreme poverty group—defined as having income below 50 percent of poverty—that was really harmed.

For children, that’s the group that was most impacted by the labor market shock of the Great Recession, a failure of the social safety net that was particular to that recession. Children in “ordinary” poverty, or 100 percent poverty, situations were hurt by the Great Recession, but not to any greater extent than in prior economic fluctuations. The social safety net could always do better, but most segments of the poor at least did not do worse in the Great Recession than in earlier recessions. But the safety net clearly did worse than in prior recessions for children in extreme poverty.

Region: The poorest of the poor.

Hoynes: Exactly, the poorest of the poor. Essentially, what we’ve done in our social safety net for families with children is move resources from the poorest of the poor to those just above that group—from the nonworking poor to the working poor.

We could have a long discussion about the social value of a dollar in one place or another, but it’s very clear that the poorest of the poor are seeing the effects of that.

Distributional effects of Head Start participation

Region: Early childhood education has long been a priority for the Minneapolis Fed, so I was particularly interested in your 2014 paper on cognitive and noncognitive outcomes of Head Start attendance. Focusing on 3-year-old children, you found large gains in vocabulary, literacy and numeracy, gains that were particularly large for those who started at the bottom of the distribution.

Could you elaborate on your findings and, particularly, on the considerable variation across subgroups—such as Spanish speakers whose cognitive gains tend to persist longer than other groups?

You and your co-authors write that these results “are largely consistent with a compensatory theory of education.” Could you explain what you mean by that?

Hoynes: As you know from the Fed’s emphasis on this question, many studies that look at the effects of Head Start (and, to some extent, of programs like Perry Preschool and others) have found that increases in cognitive test scores for children in the years they’re in Head Start seem to fade out once they enter school.

In this study with Marianne Bitler and Thad Domina, we wanted to figure out: Is that overall fadeout obscuring longer-term gains for some groups? Does the overall mean mask gains by particular segments of the population?

In unrelated research on welfare reform and labor supply, I’ve found that standard statistical methods that look only at mean results can mask large gains for some groups and declines for others. In other words, the mean effect misses the fact that if you look more carefully at the complete data distribution, you can find big effects that are positive for some and negative for others. But because it kind of averages out, the overall mean shows little impact. It just turns out that way.

We went into this paper kind of looking for a similar story. Is it possible that this fadeout is masking the fact that there are gains for some groups that somehow, in the global mean, seem to disappear?

It turns out that the story isn’t quite that simple; but we did discover that, yes, Head Start increases cognitive test scores, but those global mean results mask the fact that the gains are very concentrated at the bottom of the skill distribution. The test scores at the bottom of the distribution went up by a lot; whereas, test scores in the middle and the top of the distribution didn’t go up by very much.

That is the compensatory theory of education. The question is, when you provide an intervention, does it improve outcomes? Does it reduce inequality in those outcomes? Does it improve outcomes more at the bottom of the distribution, or is it going to improve outcomes for kids who come in with skills that you can then leverage and build on? Our results seem to suggest that the assessment shows that the outcomes go up the most at the bottom of the distribution, and that suggests that it’s compensatory, in the language of education theory.

Fast forward in this Head Start impact study, and observe kids through grade 1. We found that overall, the fadeout occurs throughout the distribution for the full population. But by looking across groups based on maternal education, race, ethnicity and other characteristics, we uncovered this finding of much larger gains for a specific group: kids who enter Head Start as English language learners—that is, English is not the primarily language at home. And in this experiment, that turned out to mostly be Spanish speakers because of the population in the experiment. These results were contemporaneous when the kids are still in Head Start, but they also persisted through transition to elementary school. Fadeout didn’t occur.

Kids who speak Spanish at home gain a lot more from Head Start participation because of early literacy and the importance of early literacy. Maybe that just makes sense prima facie, particularly given that they’re being assessed in these tests in English, so learning English is clearly going to improve their assessments, but it also seems to be a group for which those gains are more persistent.

In the fadeout literature, this is a positive finding: Gains are at the bottom, but for the population as a whole, they fade out. But for English language learners, gains seem to be a little bit more persistent. This has really been interesting as a new area for me to work in. That’s the only paper I’ve done on early childhood education; I learned a lot in the process.

Why does poverty research matter?

Region: You gave a talk at UC Davis in 2011 about why poverty research matters. Why does it matter?

Hoynes: Why does poverty research matter? Good question! Well, in my view—and as others have said, of course—a society should be judged, in part, by how it takes care of its most disadvantaged, its most vulnerable. To do a good job of that, we need to know what influences poverty. Most of my research looks at that question.

But I also want to understand what poverty generates. What does it mean to grow up poor? What does childhood poverty mean for a child’s life trajectory? To what extent are we in a world with an even playing field, with equal opportunity?

I also think a lot about these questions with another lens—of bringing more of this kind of evidence about what programs work and don’t work into policymaking. I’m currently on the Federal Commission on Evidence-Based Policymaking, something that came out of a bill that was sponsored by Speaker Paul Ryan of Wisconsin and Senator Patty Murray from Washington. It was one of the few bipartisan bills to come out of Congress last year.

Following its enactment, President Obama set up a bipartisan commission that includes economists as well as people who work in law and privacy. We’ve been meeting to come up with recommendations about how to make data more available, both to facilitate research (not only on poverty) and to think about how to bring more rigorous study of what works and doesn’t work into the policymaking process. It’s what I do as a researcher: studying what interventions are really effective. But it’s also been an interesting experience to think about how to bring that into policymaking.

Region: In that photo on your [office] wall, I see you right next to President Obama. Is that the commission?

Hoynes: Not the commission, but a meeting in the White House on the future of work. Pure luck to be sitting next to him in that meeting. It just happened. And, yes, that was pretty cool.

Endnote

1 Editor’s note: In 2008, the Food Stamp Program was renamed the Supplemental Nutrition Assistance Program (SNAP).

More About Hilary Hoynes

Current Positions

Professor of Economics and Public Policy, Haas Distinguished Chair in Economic Disparities, University of California Berkeley, since 2013; Assistant Professor, Department of Economics, 1992-2000

Visiting Scholar, Russell Sage Foundation, Fall 2017

Previous Positions

Professor, Department of Economics, University of California Davis, 2005-13; Associate Professor, 2000-05

Visiting Professor, University College London, August 2006-July 2007

Visiting Scholar, LEAP Center, Department of Economics, Harvard University, 2012

Professional Affiliations

Member, Federal Commission for Evidence-Based Policy Making, July 2016-September 2017

Member, National Academy of Sciences, Committee on Building an Agenda to Reduce the Number of Children in Poverty by Half in 10 Years, April 2017-April 2019

Member, Board of Directors, California Budget and Policy Center, 2016-present

Chair, ESRC Research Centre Scientific Advisory Board, Institute for Fiscal Studies, London, 2015-present

Member, Executive Committee, American Economic Association, April 2016-present

Mentoring Steering Committee, CSWEP, American Economic Association, 2015-present

Member, Advisory Board, Arnold Foundation, Transformative research on the minimum wage, 2015-present

Member, Advisory Board, Stanford Institute for Economic Policy Research, Stanford University, 2014-present

Faculty Affiliate, Institute for Research on Labor and Employment, UC Berkeley, 2014-present

Member, Nominations Committee, NBER Public Economics Group, 2014-present

Faculty Affiliate, Health Services and Policy Analysis Ph.D. Program, UC Berkeley School of Public Health, 2013-present

Member, Advisory Committee, National Science Foundation, Directorate for the Social, Behavioral, and Economic Sciences, 2012-13

Member, National Advisory Committee, Robert Wood Johnson Foundation Scholars in Health Policy Research Program, September 2011-13

Co-editor, American Economic Review, January 2011-December 2016

Co-editor, American Economic Journal: Economic Policy, 2007-10

Honors and Awards

Carolyn Shaw Bell Award, Committee on Status of Women in the Economics Profession, American Economic Association, 2014

Tom Mayer Distinguished Teaching Award, University of California Davis, 2007

Sloan Foundation Research Fellowship, 1997-99

Publications

Author of numerous studies on poverty, inequality, food and nutrition programs, and the effects of government tax and transfer programs on low-income families.

Education

Stanford University, Ph.D., economics, 1992

Colby College, B.A., economics/mathematics, 1983

For further background, visit https://www.econ.berkeley.edu/faculty/4704.

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