The State of the Social Safety Net in the Post-Welfare Reform Era

By Bitler, Marianne P.; Hoynes, Hilary W. | Brookings Papers on Economic Activity, Fall 2010 | Go to article overview

The State of the Social Safety Net in the Post-Welfare Reform Era


Bitler, Marianne P., Hoynes, Hilary W., Brookings Papers on Economic Activity


ABSTRACT The 1996 welfare reform led to sweeping changes to the central cash safety net program for families with children. Along with other changes, the reform imposed lifetime time limits for receipt of cash welfare, effectively ending its entitlement nature for these families. Despite dire predictions, previous research has shown that program caseloads declined and employment increased, with no detectible increase in poverty or worsening of child well-being. We reevaluate these results in light of the severe 2007-09 recession. In particular, we examine how welfare reform has altered the cyclicality of the response of caseloads and family well-being. We find that use of food stamps and noncash safety net program participation have become significantly more responsive to the economic cycle after welfare reform, rising more when unemployment increases. By contrast, we find no evidence that cash welfare for families with children is more responsive, and some evidence that it might be less so. We find some evidence that poverty increases more with increases in the unemployment rate after reform, and none that it increases less. We find no significant effects of reform on the cyclical responsiveness of food consumption, food insecurity, health insurance, household crowding, or health.

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The Personal Responsibility and Work Opportunity Reconciliation Act of 1996 made sweeping changes to the central cash safety net program in the United States. The Aid to Families with Dependent Children (AFDC) program had provided cash benefits to low-income, primarily single-parent families with children since 1935 and had come to be almost synonymous with "welfare." After 60 years with minimal changes, President Bill Clinton made good on his pledge to "end welfare as we know it," signing the 1996 legislation and thereby eliminating AFDC and replacing it with Temporary Assistance for Needy Families. TANF, or welfare as we know it now, imposes stringent work requirements, sanctions for noncompliance, and lifetime time limits for receipt of welfare. Importantly, the imposition of time limits effectively ended the entitlement nature of cash welfare for poor families with children.

In the wake of this landmark welfare reform legislation, a widespread concern was that the new policy would lead to increases in poverty and deprivation among disadvantaged families. Literally hundreds of studies evaluated the impacts of welfare reform on family and child well-being. A broad summary of that voluminous literature is that the reform led to a significant reduction in welfare participation and an increase in female employment, with little consistent evidence that it also led to an increase (or a decrease) in poverty or contributed materially to the observed decline in child poverty. (1) However, the literature also shows that the strong labor market of the late 1990s, along with the dramatic expansion of "in work" aid for low-income families with children through the Earned Income Tax Credit (EITC), may have softened the initial impact of welfare reform (Meyer and Rosenbaum 2001, Grogger 2003). Thus, at the end of the great expansion of the 1990s, cash welfare caseloads had fallen by more than 50 percent from their peak in 1994, to levels not seen since 1970. Between 1992 and 2000, the employment rate of single women with children increased by 15.3 percentage points, from 69.4 percent to 84.7 percent, and the child poverty rate declined by 6.1 percentage points, from 22.3 percent to 16.2 percent.

Of course, the expansion of the 1990s eventually ended. The nation entered a short recession in 2001, followed by a relatively weak expansion. Then, in December 2007, what has been called the Great Recession began, which was deeper and longer than any other postwar downturn to date. In this contraction and its aftermath, the national unemployment rate increased by more than 5 percentage points, from 5.0 percent in December 2007 to 10.1 percent in October 2009, exceeding the largest increase previously seen in the postwar era, that during the deep, back-to-back recessions of the early 1980s. Incomes are down, poverty is up, and participation in government assistance to families through use of unemployment benefits and food assistance has risen substantially. By contrast, TANF caseloads have remained relatively flat.

Our paper enters at this point. We seek to evaluate the impact of welfare reform on disadvantaged families in the Great Recession. It is well known that economic downturns adversely affect employment, income, and family well-being, and that they have larger negative impacts on those with less education and skill (Hoynes 2000, Hines, Hoynes, and Krueger 2001). Here we ask whether the impact of the economic cycle on disadvantaged families has changed with welfare reform. With welfare today providing less protection than before, are economic shocks causing more-adverse outcomes? We focus on the nonelderly and in particular on families with children. This is a natural choice given that our paper studies the effects of reform of the cash assistance system that is exclusively targeted to families with children. (2) In an effort to broadly capture the possible effects of reform, we look not only at use of cash welfare but also at family well-being measures and other aspects of the safety net. Outcomes we examine include poverty (both official and alternative measures), earnings and income, participation in food stamps, participation in Supplemental Security Income (SSI) and disability income, receipt of child support or alimony income, whether individuals live in public housing or get a rent subsidy, food consumption, food insecurity, health insurance coverage, health status, measures of crowding (such as "doubling up"), and the presence of single female-headed family units. We use both administrative data and household survey data to assemble a comprehensive picture of family well-being in the wake of welfare reform.

We begin in section I with a descriptive and expansive look at expansions and contractions from 1979 to the present. For each contraction or expansion, we report data on changes in spending on government assistance programs (cash welfare, unemployment insurance, and food assistance), in spending on the EITC, in family employment and poverty, in measures of housing stress, in health insurance coverage and access, and in family consumption. In so doing, we pay particular attention to how the changes during the recent recession compare with those during the early-1980s recessions. In section II we step back and provide a brief description of welfare and the safety net for low-income families more broadly, with a focus on recent important changes.

The descriptive approach of the paper's first two sections, although informative about the basic facts, does not allow us to identify the role that welfare reform has played in causing the observed changes in outcomes. We turn to this question in section III, where we present our core findings about how welfare reform has affected the relationship between the economic cycle and family well-being among the disadvantaged. To identify the impact of welfare, we take advantage of the rich variation across states in the timing and severity of economic cycles and welfare reform. Our econometric model is a basic state-year panel where we regress various family outcomes on the unemployment rate, a measure of welfare reform, and the interaction between the two. The estimated coefficient on the interaction term identifies how welfare reform has affected the impact of the cycle on family well-being.

This approach allows us to estimate how an increase in a state's unemployment rate affects outcomes among the disadvantaged, and how those impacts changed with the dramatic reform to welfare. We believe ours to be the first paper to address this issue. We utilize data from many sources in order to provide a comprehensive evaluation. We start with administrative data on participation in AFDC and TANF and on food stamp caseloads, to document the "first stage" of the policies. We then analyze data from 30 years of the March Current Population Survey Supplement (CPS), which allow us to examine impacts on various family and household measures of well-being, including earnings and income, poverty, living arrangements and housing stress, program participation beyond AFDC/TANF and food stamps, health insurance coverage, and health status. Finally, we present results for food consumption, using data from the Panel Study of Income Dynamics, and for food insecurity, using data from the food security supplements to the CPS.

In section IV we reexamine the effects of welfare reform and how welfare participation responds to the business cycle. First, we briefly touch on what is known about the response of public assistance and the safety net to the recession of 2001. Then we revisit the topic of reductions in welfare participation with reform, and in particular whether they have been driven by changes in eligibility (that is, by reduced access) or changes in take-up. We then go on to explore what is known about those single, nonworking women who before reform were at risk of being on welfare but are no longer on welfare (known as "disconnected women" in a growing literature). Section V concludes.

Using both administrative and survey data, we find that both food stamps and a broader measure of safety net participation (one that excludes cash welfare for families with children and Medicaid) have become more responsive to the economic cycle after welfare reform. Although always countercyclical, both of these measures increase more with unemployment after welfare reform. All measures of poverty (official and our own alternative measure) are also countercyclical, and the likelihood of having an income under 150 percent of the official poverty threshold is significantly more countercyclical after reform. By contrast, there is no evidence that cash welfare for families with children is more responsive after reform, and some evidence that it might be less so. We find that reform has had no significant effects on the cyclical responsiveness of food consumption, food insecurity, receipt of child support or alimony, receipt of SSI or disability insurance benefits, health insurance coverage, household crowding, or health.

I. The Business Cycle, the Safety Net, and Family Well-Being

In this section we examine the changes in government assistance and family outcomes that have occurred historically across expansions and contractions in the United States. Figure 1 traces our measure of the economic cycle--the unemployment rate--annually from 1962 to 2009. During the recent recession, which officially began in December 2007, the unemployment rate rose from 5 percent to a peak of 10.1 percent in October 2009. Although the recession officially ended in June 2009, the unemployment rate remains high, at 9.6 percent in September 2010 (seasonally adjusted). In terms of the annual averages shown in figure 1, unemployment in that recession increased from 4.6 percent in 2007 to 9.3 percent in 2009. In our analysis we compare results for the recent recession with those for the early 1980s, when two recessions in quick succession led to an increase in the annual unemployment rate from 5.8 percent in 1979 to 9.7 percent in 1982.

Figure 1 also depicts two measures of the poverty rate (the share of the population living in poverty), also on an annual basis. We view the poverty rate as a central measure of family well-being and thus rely on it heavily in our work. Official poverty status in the United States is determined by comparing total pre-tax family cash income with a poverty threshold, which varies by family size, number of children, and the presence or absence of elderly persons. (Thus, all persons in the same family have the same poverty status.) In 2009 the poverty threshold for a family of four (two adults, two children) was roughly $22,000. This measure of resources has numerous drawbacks. Notably, there is no geographic variation in the threshold, despite wide variation in costs and wages across regions, and the thresholds are based on outdated household budgeting rules of thumb, which fail to adjust for changes in many categories of expenses (such as shelter, clothing, work-related expenses, medical expenses, and utilities) and thus do not currently reflect actual needs. Also, the thresholds are updated annually by the consumer price index for all urban consumers (CPI-U), a measure of inflation that may not well capture changes in prices paid by disadvantaged families caused by changes in the basket of goods they consume. Further, family cash income is not a complete measure of family resources. It excludes noncash government transfers (such as food stamps, housing subsidies, and housing vouchers), certain subtractions from income (such as income and payroll taxes), and certain additions to income (such as the EITC) made through the tax system. These limitations in the official poverty definition have been noted by many, and a recent National Academy of Sciences (NAS) panel made recommendations for revisions (Citro and Michael 1995). Throughout the paper we make use, to the fullest extent possible, of an alternative poverty definition using a comprehensive post-tax, post-transfer income concept. Of particular relevance for our work is the measurement of noncash benefits, the EITC, and taxes. (3)

[FIGURE 1 OMITTED]

Figure 1 shows that poverty in the population as a whole declined substantially between the early 1960s and the mid-1970s, with shorter periods of increases and decreases since that time. In the recent recession the official poverty rate increased by 1.8 percentage points, from 12.5 percent in 2007 to 14.3 percent in 2009. The fact that unemployment did not improve in late 2009 and early 2010 suggests that poverty will likely increase further before it declines. The figure also plots, for the years for which data are available (1999-2008), an alternative poverty measure suggested by the NAS, which incorporates noncash transfers, taxes, out-of-pocket medical expenditure, and work-related deductions in income and includes consumption-based measures in the thresholds. Poverty by this measure is higher than by the official measure but follows a very similar trend. (4)

Given our focus on the effects of welfare reform on the nonelderly, we show in figure 2 the official poverty rate for children, as well as that for all nonelderly persons, from 1980 to 2009. In 2009, 15.1 percent of nonelderly persons, and 20.7 percent of children, were poor. The figure also plots the unemployment rate, with shading for years when contractions occurred, (5) and shows that poverty rates are countercyclical, rising in downturns and falling in expansions. These simple time series do not reveal any obvious evidence of a change in the cyclicality of poverty following welfare reform; that is, it does not appear that poverty more closely tracks the unemployment rate after 1996 than before. One can, however, see that the strong expansion of the late 1990s was associated with decreases in both the unemployment rate and poverty.

Table 1 provides more detail on economic circumstances and well-being in contractions and expansions, both before and after welfare reform. The contractions and expansions are the same as those depicted in figure 2. The first column reports changes during 1979-82, a period that includes the two back-to-back recessions. The next four columns report changes for the contractions of 1989-92, 2000-03, and 2007-09; in the last of these, a few measures (EITC spending, NAS alternative poverty, and food insecurity) are available only through 2008. The final three columns present changes during the three expansions depicted in figure 2: 1982-89, 1992-2000, and 2003-07. We view these tabulations as interesting and descriptive, but again it is difficult to reach conclusions about how cyclicality has changed because one cannot distinguish the cycle from the aggregate trend.

[FIGURE 2 OMITTED]

The first row of table 1 reports the change in the annual unemployment rate in each contraction and expansion. During the 2007-09 recession, the unemployment rate increased by 4.7 percentage points, compared with an increase of 3.9 percentage points between 1979 and 1982 and even smaller increases during the 1989-92 and 2000-03 contractions. The next panel documents how spending on the key cash and near-cash government assistance programs (the latter comprising food stamps, unemployment insurance, and the EITC) changed across cycles. Both food stamps and (especially) unemployment insurance show countercyclical spending. Of particular interest is the 68 percent increase in real food stamp spending per capita between 2007 and 2009. Expenditure for the EITC does not appear to follow a countercyclical pattern, although with major expansions in the program in 1986, 1990, and 1993, it is hard to distinguish any impact of the cycle (Eissa and Hoynes 2006).

Perhaps surprisingly, the data on cash welfare expenditure (AFDC and TANF) do not show a clear countercyclical pattern. Cash welfare payments per capita increased during the 1989-92 contraction (by 10 percent) but decreased during the contractions of 1979-82 (by 14 percent), 2000-03 (17 percent), and 2007-09 (2 percent). However, the more comprehensive TANF total assistance measure, which includes cash and noncash assistance, increased by 8 percent in the 2007-09 recession. (6) Less surprisingly, cash payments decreased during each of the three expansions. Previous research shows that some of the decreases in periods of contraction are the result of structural, policy-driven declines in expenditure (for example, expenditure was lower because of rules cutting eligibility in 1981 and because of welfare reform in the late 1990s) in excess of countercyclical increases in expenditure. This illustrates the limitations of this exercise: simple descriptive comparisons of expenditure across contractions and expansions are not definitive in identifying the effects of welfare reform on the responsiveness of the safety net.

We postpone until the next section a detailed discussion of welfare, other safety net programs, and the recent reforms. However, to provide a context for the material presented in the remaining panels of table 1, here we present a demographic profile of cash welfare recipients. In particular, table 2 reports characteristics of families with any cash welfare income (AFDC or general assistance) in 1995, on the eve of federal welfare reform. For comparison, we also present the same characteristics for all families with children in 1995 and for families receiving cash welfare at the end of the period, in 2009. (7) In 1995 almost 70 percent of heads of families with cash welfare income were unmarried single women, about 40 percent were non-Hispanic whites, 34 percent were non-Hispanic blacks, and 22 percent were Hispanic. (8) These figures changed little between 1995 and 2009. Compared with all families with children, the welfare population is more likely to be black or Hispanic, less educated, unmarried, and female headed, with the head out of the labor force. In addition, table 2 shows that most families receiving cash welfare also participate in other government programs: in 1995, 87 percent of these families received food stamps, and 33 percent lived in government-subsidized housing. (Not shown in the table is that 90 percent of the heads and 97 percent of the children were on Medicaid--or, for the children only, the State Children's Health Insurance Program--13 percent received cash assistance through the SSI program, and 65 percent participated in the free and reduced-price school meals program.)

Historically, families do not mix welfare and work (31 percent of recipients were working at the time of the 1995 survey, and 56 percent were out of the labor force), but the tabulations for 2009 suggest that combining welfare and work has increased somewhat since welfare reform. (9) Those who did work before welfare reform tended to work in poorly paid occupations (Burtless 1997). Also worth noting is that among a given entry cohort into welfare, a large share will be on welfare for a short time, but a large share of the current welfare caseload is made up of long-term recipients, who tend to be even less attached to the labor force than other recipients (see, for example, Bane and Ellwood 1994). Ellwood (1986) reports that 34 percent of first-time AFDC recipients had not worked in the previous 2 years, and l 8.4 percent of these new recipients had a disability that limited work.

With these facts in mind, we return to table 1, which also presents changes across contractions and expansions for a broad array of outcomes relevant for the welfare population. Data on most outcomes are not available for all time periods, and many are available only after welfare reform. All of the poverty measures are strongly countercyclical. For example, the official poverty rate for children increased by 5.5 percentage points in the 1979-82 recession, and by 2.7 percentage points between 2007 and 2009. Poverty declined in two of the three periods of expansion, the exception being the 2003-07 expansion, when child poverty increased by 0.4 percentage point. Extreme child poverty, defined as the share of children in families with income below 50 percent of the official poverty threshold, declined across all expansions. The NAS alternative poverty measure seems to fluctuate less with the cycle. (As noted above, the NAS alternative poverty measure is not yet available for 2009, so the statistic for the recent recession is of limited value.)

Employment of single mothers exhibits a procyclical pattern, declining by 3.9 percentage points in the recent recession, compared with 1.9 percentage points in the 1979-82 contraction. This suggests a greater sensitivity to the cycle after welfare reform, which is consistent with an increase in rates of attachment to the labor market among potential welfare recipients. We also consider a more comprehensive measure of receipt of safety net benefits that includes a broad array of public assistance programs (but excludes AFDC/TANF, general assistance, and Medicaid). This broad safety net participation measure is very strongly countercyclical, increasing by a striking 4.5 percentage points in the recent contraction after declining in the 1992-2000 expansion by a similar amount. (10)

Mindful of the importance of looking at measures that capture well-being rather than resources, in the remainder of the table we present changes in consumption expenditure (in real 2009 dollars per capita from the Consumer Expenditure Survey), in food insecurity, in "doubling up" and homelessness, and in health insurance coverage and access. Our consumption measures are for individuals in the lowest 20 percent of consumer units by pre-tax income, and notably, changes in these measures do not show a consistent pattern across the contractions and expansions. Food insecurity, data for which are available only for the later period, shows an increase of 3.2 percentage points in the recent contraction; this is particularly striking given that the data are available only through 2008. (11)

The share of children living in a female-headed household and the share "doubling up" (living in households with two or more families, a measure of housing stress) also do not exhibit strong patterns across cycles. Curiously, homelessness, data for which are available only for the most recent period and for a sample of shelters, seems to have declined in the recent recession, although the number of homeless families increased. Delay of or failure to get medical care due to cost, a measure of health care access, rises in both contractions for which data are available; health insurance coverage, however, shows no clear cyclical trend.

To illustrate in more detail the degree of protection that cash welfare and food stamps provide in recessions, the top panel of figure 3 shows the total number of unemployed persons, the cash welfare (TANF) caseload, and the food stamp caseload by month from January 2007 to the present. We normalize all series to 1 in December 2007, the official start of the recent recession, and demarcate the official end of the recession in June 2009. (12) The figure shows that food stamp caseloads have expanded significantly with the recession whereas TANF caseloads have changed very little. The middle panel of figure 3 depicts the same three series (substituting AFDC for TANF) for the second of the two early-1980s recessions, which officially began in July 1981, and the bottom panel does the same for the recession that began in July 1990. These graphs suggest that cash welfare caseloads are less responsive to the economic cycle than are food stamp caseloads and that neither program responded much during the 1981-82 recession.

Finally, another way to assess the role of the safety net is to examine the sources of income for the disadvantaged during a contraction. The top panel of figure 4 shows the share of total income (which here includes both cash income and the value of food stamps) by source for all households in poverty in 1982 and 2008; the bottom panel provides the same information for households in extreme poverty (income below 50 percent of the official poverty threshold). (13) This figure clearly shows the declining role of cash welfare as a countercyclical income source for the poor and the increasing roles played by food stamps, earnings, and SSI. (14)

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]

Several important points emerge from this analysis. Overall, use of a broad measure of the safety net (excluding Medicaid and cash assistance for families with children), poverty, food insecurity, and health care access show strong countercyclical patterns. The nature of changes in demographic stress, homelessness, and consumption across the cycle is less clear. Unfortunately, many of the outcomes of interest exhibit either secular trends (for example, children living with single female family heads, percent uninsured) or policy-driven structural changes (for example, expansions in the EITC, welfare reform--induced reductions in use of cash welfare), or both. These other factors make it difficult to draw conclusions from table I (or figure 3) concerning cycles, the disadvantaged, and welfare reform, as it is hard to separate the role of the aggregate cycle from that of other factors affecting the trends in outcomes. To take just one example, it is well understood that, as alluded to above, AFDC caseloads declined in 1981 as a result of changes in the benefit reduction rate that reduced eligibility for many recipients (Moffitt 1992, U.S. General Accounting Office 1985). This obviously complicates the interpretation of figure 3 and table 1. Rebecca Blank expresses our concerns well:

Note that the back-to-back recessions in the early 1980s caused a mild uptick in caseloads, but this was quickly aborted when legislative changes in Reagan's first term ended AFDC eligibility for about 15 percent of the caseload.... This policy change makes it difficult to do any quick "eyeball" comparisons between the recession effects of the early 1980s and the early 1990s on caseloads. (Blank 2001. p. 87)

In sum, the data in table 1 provide a useful description of changes in well-being in the recent recession. However, to make more definitive conclusions about how the cyclicality of outcomes has changed after welfare reform, we defer to our regression results below, where we are able to separate out secular trends from the cycle.

II. The Elements of the Safety Net before and after Reform

Before discussing our regression results, we step back and provide some more background on welfare and welfare reform. Cash welfare is not the only government assistance program for low-income families with children. In our analysis of the impact of the cycle on disadvantaged families, we seek to understand how both cash welfare and the other elements of the safety net may have affected family well-being. Therefore, here we describe not only cash welfare and welfare reform but also, briefly, the other safety net programs and their recent reforms.

Table 3 presents an overview of participation and spending in the central cash and near-cash safety net programs for low-income families with children. The two primary programs are TANF (the cash welfare program that replaced AFDC as described above) and the food stamp program (now called the Supplemental Nutrition Assistance Program). The food stamp program is by far the larger of the two, especially since welfare reform: in 2009, 15 million families or single individuals received food stamps, at a cost of $50 billion (all dollar figures in this paragraph are in current dollars), compared with fewer than 2 million families receiving cash welfare, at a cost of $9 billion. The EITC provides tax-based aid for low-income working families with children, and in 2008, the most recent year for which data are available, 25 million families received the EITC, at a total tax cost of $51 billion. SSI is another cash welfare program, one that primarily serves poor elderly and disabled adults but is also received by disabled children in some poor families. Finally, unemployment compensation is obviously a critical element of the safety net and is the central income replacement program in recessions. This program differs from the others in that it is a social insurance program, with eligibility determined by work history and not conditioned on current income. Unemployment compensation consists of several different programs, including regular state benefits, state extended benefits (which generally kick in when a state's unemployment rate exceeds a preset threshold), and the federally financed emergency benefits program (which is currently in place and extends benefits well beyond the normal maximum period of receipt of 26 weeks). In 2009, on average, about 6 million persons in a given week received some form of unemployment compensation, at a cost of over $131 billion for the year).

Average monthly payments per recipient family in 2009 were $397 for TANF and $276 for food stamps. EITC credits in 2008 averaged $2,046 per year, or $171 per month. By contrast, regular state weekly unemployment compensation payments in the fourth quarter of 2009 averaged $308 per week ($1,335 per month). The final column in table 3 reports results from a recent Center for Budget and Policy Priorities study (Sherman 2009) on the number of children that each of these programs lifted out of poverty in 2005. The EITC leads, having lifted 2.6 million children out of poverty, followed by food stamps at 2.2 million, and then by SSI and TANF, which each removed about 1 million children from poverty. (15)

Our analysis focuses on cash welfare (TANF) and food stamps, but in our analysis of family income and poverty, we indirectly analyze the impacts of all the programs listed in table 3 as well as broader measures of any safety net use that encompass other programs, such as the free and reduced-price school lunch program and public housing and rental vouchers. (16)

II.A. Eligibility Rules, Benefits, and Recent Reforms far the Key Safety Net Programs

CASH WELFARE. At the national level, cash welfare for low-income families started with the AFDC program, created by the Social Security Act of 1935. The program was jointly funded by the state and federal governments (with a higher federal matching rate for lower-income states). States had authority to set benefit levels, but the federal government dictated most of the remaining eligibility and benefit rules. A family was eligible if it satisfied income and asset tests, and assistance was primarily limited to single women with children. (17) The benefits were structured in a manner typical for income support programs: if a family had no income, it received the maximum benefit or "guarantee." As the family's earnings (or allowable income) increased, the benefit was reduced by the benefit reduction rate or clawback rate, which created an implicit tax rate on earned income. Historically, this rate has varied between 67 and 100 percent, providing a strong disincentive for work (Moffitt 1983). This fact attracted little attention in the program's early decades, when very few mothers participated in the labor market. Over time, however, concerns about the work disincentive (and about the disincentive to form two-parent families) grew, and interest in reforming the program followed.

The modern era of welfare reform began in the early 1990s, when many states were granted waivers to modify their AFDC programs. (18) About half of the states implemented some sort of welfare waiver between 1992 and 1995. On the heels of this state experimentation, the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) was enacted in 1996, replacing AFDC with TANF. The key elements of reform in the state waivers and the TANF legislation included work requirements, lifetime time limits on the duration of welfare receipt, financial sanctions for failing to adhere to the work requirements or other rules, and enhanced earnings disregards. (19) These changes were designed to facilitate the transition from welfare to work and to reduce dependence on cash welfare. The time limits were an important provision in that they eliminated the entitlement nature of the program. States have considerable discretion in setting policies under TANF, but by federal law, programs must include work requirements and lifetime time limits of 5 years or less for the vast majority of recipients. (20) The character of federal funding also changed from an (uncapped) matching formula under AFDC to a (capped) block grant under TANF.

An advantage for identifying the effects of these recent reforms is that both the timing and the type of welfare reform varied considerably across states in the 1990s. Some states reformed their programs through waivers, in advance of the 1996 law. Other states reformed their programs later, when required by PRWORA, with the last state implementing TANF in January 1998. Under PRWORA, states continue to vary in their length of time limits, types of sanctions, and so on. For example, Gilbert Crouse (1999) reports that before PRWORA, 15 states had waivers approved with time limits on receipt, 19 had waivers approved that enhanced their earnings disregards, and 28 had waivers approved that included sanctions for noncompliance. Although PRWORA imposed time limits for federally funded welfare on all states, some states use their own funds to pay benefits beyond the federal time limit. This state variation in the timing and severity of reform has been widely exploited in empirical studies of welfare reform (see reviews in Blank 2002 and Grogger and Karoly 2005), and we will make use of this variation as well.

TANF provides benefits only to families with quite low incomes, and eligibility cutoffs and benefit levels leave recipients substantially below the poverty line. Before welfare reform, under AFDC, the median state provided benefits to families with income up to 70 percent of the poverty guideline, and the median state's benefit level for a family of three was about 36 percent of the 1996 poverty guideline (U.S. House of Representatives 1996). (21) Benefits varied widely across states; for example, in 1996 maximum benefits for a family of three were $120 per month in Mississippi and $607 per month in California. As part of their welfare reforms, to improve financial incentives to make the transition from welfare to work, many states decreased the implicit tax rate on earned income within the TANF program, allowing individuals to have much higher earnings before losing all their welfare benefits. Despite these expansions in the amount of earned income that families could keep while on welfare, total benefits remain low.

FOOD STAMPS. The Supplemental Nutrition Assistance Program, like TANF, is a means-tested program (eligible families and individuals must satisfy income and asset tests) in which benefits are subject to a ceiling and reduced with earned income. The similarities end there, however. First, the food stamp program is a federal program, with all funding (except for 50 percent of administrative costs) provided by the federal government. Second, unlike virtually all other cash assistance programs, food stamps are not limited to certain targeted groups such as families with children, the elderly, and the disabled. Third, the benefit reduction rate is relatively low (30 cents per dollar earned), and the income eligibility threshold is relatively high (130 percent of the poverty guideline). The lower benefit reduction rate means that the food stamp program serves not only the nonworking poor (those receiving cash welfare) but also the working poor. Recipients are allowed to use their benefits to buy a wide array of food items (although not prepared foods), and studies show that the behavioral response to food stamps is similar to the response to cash (Fraker and others 1992, Hoynes and Schanzenbach 2009, Ohls and others 1992). Food stamp benefits today are disbursed with debit cards rather than paper vouchers as in the past.

Unlike cash welfare, the food stamp program has remained relatively unchanged over time. The income eligibility cutoff and benefits are adjusted for changes in prices each year, and the actual benefit formula (and thus the implicit tax rate) has changed very little over time. However, important limitations to the program were introduced under PRWORA: legal immigrants were deemed ineligible, and most childless, jobless adults between 18 and 50 could receive only 3 months of food stamps in any 3-year period. (22) The 2002 farm bill reinstated benefits for legal immigrants, and the 2009 federal stimulus bill temporarily suspended the 3-month limit for childless, jobless adults. The stimulus bill also provided a temporary increase in maximum benefits of roughly $25 per month, at a cost of $6 billion in 2009 (Pavetti and Rosenbaum 2010).

Since welfare reform (and perhaps even before it), the food stamp program is unambiguously the key safety net program and the only one that is "universal" (that is, based only on economic need) and that has a fully funded entitlement. Caseloads and benefits adjust automatically with demand (increasing in recessions), and costs are uncapped.

UNEMPLOYMENT INSURANCE. As already noted, unemployment insurance is a social insurance program that provides temporary and partial earnings replacement for involuntarily unemployed individuals with a recent employment history. As a social insurance program, unemployment insurance is not means tested, and eligibility is a function of earnings history. States administer their programs and set payroll taxes and benefit levels. Workers' wages are subject to tax while employed, and unemployed workers receive benefits for a fixed duration, with replacement rates (the ratio of benefits to most recent earnings) averaging 47 percent since 1995 (U.S. Department of Labor 2010). The extended benefit program extends receipt of unemployment compensation beyond the 26-week maximum when state unemployment rates or the share of the insured population claiming benefits is high. Funding for the extended program is shared by the states and the federal government. In most major downturns, Congress has enacted emergency extensions to unemployment insurance, such as the current program, which in most states extends benefits up to 99 weeks. Recently, these emergency extensions have been fully federally funded.

Although unemployment compensation plays a central role in recessions, it is often not considered part of the safety net because it primarily provides insurance and is funded through worker contributions. We mention it here for three reasons. First, given the increase in employment among the potentially welfare-eligible population since TANF's passage (see the discussion of figure 6 below), unemployment compensation may be increasing in importance for low-income families. Second, although the insurance is not means tested, replacement rates fall as earnings rise, providing greater protection for lower-wage workers. Third, the emergency federal benefit extensions tend to be explicitly countercyclical and are passed by Congress in response to bad economic times. Although these emergency programs are typically short lived, when in effect they account for a large share of total spending on unemployment compensation. Table 3 shows that in 2009, emergency benefits were about $44 billion, compared with a combined $87 billion for regular and extended benefits.

THE TRANSITION FROM OUT-OF-WORK TO IN-WORK ASSISTANCE. As discussed above, the EITC is one of the most costly cash or near-cash assistance programs. It functions as an earnings subsidy and as such is extended only to working families. The expansion of the EITC, facilitated through tax acts in 1986, 1990, and 1993, has featured prominently in the movement toward more "in-work" assistance in the safety net. However, the emergence of TANF has also been an important part of this transition. Virtually all TANF policies--the work requirements, the time limits, and the lowering of the benefit reduction rate--are designed to increase work. In addition, under TANF, states have the flexibility to use their federal block grant funding toward assistance other than periodic cash benefits: examples include child care subsidies as well as transportation, training, and diversion payments. (23) To illustrate the importance of these trends, figure 5 shows real spending per capita from 1980 to 2009 for families receiving cash grants through AFDC/TANF as well as total TANF expenditure per capita and total EITC tax cost per capita. (We also show spending on food stamps per capita because this program, too, serves the working poor.) The expansion of the EITC between 1986 and 1998, coupled with the decline in cash welfare expenditure beginning with the waivers of the early 1990s, represents a tremendous change in the incentives faced by low-income families with children. Importantly, the post-welfare reform trend in total TANF expenditure presents a somewhat different picture concerning welfare funding than the trend for cash grants only--in fact, total funding has been more or less constant (in real terms) over the last 10 or more years. Unfortunately, the state reporting requirements for noncash TANF expenditure are minimal, and thus very little is known about who receives this funding and what it is spent on. (24) Nonetheless, these changes illustrate an important transition from out-of-work aid to in-work aid for low-income families with children.

[FIGURE 5 OMITTED]

The result of these policy changes, coupled with the strong labor market of the late 1990s, was a historic increase in employment for single women with children. Figure 6 presents, for 1980-2009, the percentages of three groups of women aged 20-58 with any weeks of work in the last year: single women heading families with children, married women with children in the family, and single women without children in the family. Between 1992 and 2000 the employment rate of single women with kids rose by 15 percentage points; the other groups saw minimal changes. This trend suggests that outcomes for these single-woman-headed families will be more procyclical, given their increased connection to the labor market.

[FIGURE 6 OMITTED]

II.B. Cycles and Participation in Safety Net Programs

Figure 7 presents cash welfare and food stamp caseloads from 1980 to 2009. These data come from administrative sources rather than self-reports from household surveys (see the data appendix for details). To account for changes in population over this period, we show the ratio of the caseload to the total population. (25) Several observations can be made. First, throughout the pre- and post-welfare reform periods, many more families received food stamps than received cash welfare. Second, cash welfare caseloads dramatically declined in the period around welfare reform and have remained low since. Third, compared with cash welfare, the food stamp caseload shows a stronger countercyclical tendency, at least during the early part of the period. (26) Fourth, since 2000 the trend in the TANF caseload bears little relationship to the national business cycle. Notably, the TANF caseload increased by very little in the recent recession, as figure 3 showed, despite unemployment rates reaching over 10 percent in many states. (27)

[FIGURE 7 OMITTED]

[FIGURE 8 OMITTED]

In figure 8 we return to our broader measure of safety net benefits (excluding Medicaid and cash welfare for families with children; see table 1), which we construct from the 1981-2010 March CPS data. Other than an increase in the early 1990s, followed by a decline, this more comprehensive measure of safety net participation also shows a fair amount of cyclical variation. (28)

Why might it make sense that the food stamp program and our broader measure of the non-AFDC/TANF, non-Medicaid safety net are more counter-cyclical than cash welfare? As mentioned above, the implicit tax rates in cash welfare are high, much higher than those in the food stamp program. It is much more common for families with food stamps to also have earned income, whereas this is relatively uncommon for cash welfare recipients (see table 2).

One should be cautious about drawing conclusions from national trends, however. The problem, as noted in section I, is that it is difficult to distinguish between changes due to labor market fluctuations and changes due to reforms in the programs themselves. For example, the fall in the cash welfare caseload in the late 1990s has been shown to be a function of both the strong economy and welfare reform (for example, see Council of Economic Advisers 1997, Blank 2001, and Ziliak and others 2000). To separate out the impact of welfare reform from labor market fluctuations, our empirical model will use disaggregated data and take advantage of rich variation in cycles and reform across states and time.

III. Welfare Reform and the Impact of the Business Cycle on Family Well-Being

In this section we present our central empirical results on the impact of welfare reform on family well-being over the business cycle. These are new results that build on the models used in two separate literatures: the first examines the impact of the cycle on family economic outcomes and on different demographic groups (for examples, see Hoynes 2000 and Hines, Hoynes, and Krueger 2001), and the second the impacts of welfare reform (see reviews by Blank 2002 and Grogger and Karoly 2005). Clearly, the fact that the safety net provides less than perfect insurance implies that a recession will lead to reductions in family well-being, as measured by increases in poverty, reductions in consumption, increases in doubling up, and so on. What we want to examine is how welfare reform has affected that tendency.

A standard approach in both of these literatures is to use variation across states to distinguish the impact of labor market cycles from that of policy changes. We adopt that approach here as well. In particular, we estimate the following model:

(1) [y.sub.M] = [alpha] + [phi][UR.sub.st], + [theta][REFORM.sub.st], + [delta][UR.sub.st], x [REFORM.sub.st], + [[gamma].sub.s], + [[lambda].sub.s] + [[eta].sub.s]t + [epsilon].sub.st],

where s indexes states, t indexes years, UR is the unemployment rate, and REFORM is a measure of welfare reform. (29) Our equation controls for state fixed effects ([[gamma].sub.s]), year fixed effects ([lambda.sub.t]), and linear time trends for each state ([[eta].sub.s]t). When we use household survey data, we also control for demographics ([X.sub.ist], where i indexes households). Standard errors allow for arbitrary correlation within states. The main specifications for administrative caseloads are at the monthly level, and for them t denotes months rather than years.

We begin by analyzing the administrative caseload data on AFDC/ TANF and food stamps and then move on to a wide range of family well-being measures based on the March CPS. Using the CPS, we examine impacts on official poverty, our own alternative measure of poverty, program participation (single programs as well as multiple programs), living arrangements (female-headed families), employment among female heads of family units, measures of housing stress (doubling up, households containing subfamilies, and others), health insurance coverage, receipt of child support or alimony, and general health. Finally, we present estimates for food insecurity and, using data from the Panel Study of Income Dynamics, family food consumption. Caseload models are weighted by the total population, and the survey data models are weighted using the surveyprovided weights.

The model controls for a main effect for welfare reform and a main effect for labor markets (the unemployment rate). The parameter of interest is [delta], the interaction between the reform variable and the unemployment rate, which measures how the impact of the cycle on outcome y changes with welfare reform. With controls for fixed state effects and fixed time (year or month) effects, our estimates are identified off of changes within states over time. This type of model is commonly known as a difference-in-differences model. (30)

This model, by controlling for an unrestricted time trend ([[lambda].sub.t]), captures any elements that are common to all states in a given year. A downside of this approach is that the time effects absorb some features of the national cycle. However, the benefit of this approach is that it allows us to identify the impacts of welfare reform separately from labor market fluctuations. To illustrate the variation we are using, figure 9 presents a series of scatter-plots of state data in which each state's population is represented by the size of the circle centered on the data point for that state. The horizontal axis in each panel plots the change in state annual unemployment rates (in percentage points) over a contraction, and the vertical axis a change in a state outcome (in percent) over the same period. The first three panels present data for 2007-09, and the next three panels for 1979-82. For each cycle we show the percent change in cash welfare caseloads per capita (top panels), the percent change in food stamp caseloads per capita (middle panels), (31) and the percent change in official child poverty rates (bottom panels). We have forced the scales to be the same for each of the two contractions for each outcome to provide better comparisons across contractions. The figure reveals considerable variation in the depth of the recessions across states. For example, between 2007 and 2009, state changes in the unemployment rate ranged from about 1 to 7 percentage points, and the change in child poverty varied from a reduction of 25 percent to an increase of nearly 100 percent. Further, the figure shows a positive correlation between the severity of a recession and the increase in official child poverty and program caseloads per capita.

[FIGURE 9 OMITTED]

We explore the effects of three measures of welfare reform. First, we use a state pre-versus-post design where REFORM equals 1 if the state has implemented a waiver or has implemented TANF, and zero otherwise. (32) Second, we use an explicit categorization of states based on their TANF and waiver policies, focusing on two policy dimensions: the length of time limits and the severity of sanctions. We adopt definitions and data from Caroline Danielson and Jacob Klerman (2004) in constructing these variables. (33) We define time limits as short (less than 48 months), long (48 months or longer), or adult (time limits remove only adults from aid), with the omitted group being state-year cells with no time limits (either prePRWORA AFDC rules or no time limit under TANF). We define financial sanctions as full (immediate, full family sanction) or gradual (gradual, full family sanction), with the omitted group being weak sanctions (either AFDC sanctions or, under TANF, sanctions no more stringent than the AFDC sanctions).

With the administrative monthly caseload data, we use the policies in place that month. For CPS outcomes measured over the last calendar year, such as program participation, income, poverty, and health insurance coverage, the main reform variable is measured as the share of the past calendar year during which reform was in place, and the time limit and sanction policies are coded according to what was in place in December of the preceding year. For the other outcomes measured at the time of the CPS survey (living arrangements, health status), welfare reform is measured by whether the policy was in place as of March of the survey year.

III.A. Safety Net Caseloads

Table 4 presents estimates of the model using administrative data on participation in the cash welfare and food stamp programs. The dependent variable is caseloads per capita at the state-month-year level for 1980 through 2009. State monthly unemployment rates are seasonally adjusted (but the results are very similar if we use non-seasonally adjusted unemployment). We view the results here as a sort of "first stage": they are useful to establish the basic relationship between welfare reform and the cyclicality of safety net programs for low-income families. Additionally, these caseloads are measures from administrative data and do not suffer from underreporting. Thus, they provide us with a valuable benchmark for understanding whether the underreporting documented by Bruce Meyer, Wallace Mok, and James Sullivan (2009) and others has implications for analysis using state-year panels with state and year fixed effects. (34) Finally, considerable attention has been given to the rise in food stamp caseloads in the recent recession, (35) yet no prior research has identified whether welfare reform contributed in any way to that rise.

Table 4 reports the coefficients on the state unemployment rate and the interaction between the unemployment rate and welfare reform. We present three specifications, one for each of the reform variables we discuss above. The dependent variable is the ratio of the caseload to the population (multiplied by 100), and the unemployment rate is measured in percent.

For cash welfare caseloads (column 4-1), the coefficient of 0.06 implies that a 1-percentage-point increase in the unemployment rate leads to an increase in the scaled AFDC/TANF caseload-population ratio of 0.06, which, relative to the mean of 1.2, implies an effect size of 4.7 percent. Interestingly, food stamp caseloads (column 4-4) show a similar effect size: the coefficient of 0.17 scaled by the mean of 3.5 implies an effect size of 4.9 percent.

A negative coefficient on the interaction between the unemployment rate and reform implies that welfare reform led to a reduction in the cyclicality of program participation, and a positive coefficient implies an increase (since program participation is expected to be, and is, countercyclical). We expect that the impact of short time limits on cyclicality should exceed (in magnitude) that of long time limits, and both should be larger in magnitude than the effect of the omitted group of no time limits. Adult time limits are generally the least stringent of the three; however, this measure ignores the length of the time limit, which also might be important. We expect the impact of full sanctions on cyclicality to be greater in magnitude than the impact of gradual sanctions, and both should be larger than the effect of the omitted group of no sanctions.

With the exception of the "any reform" specification, the results for AFDC/TANF caseloads (columns 4-1 to 4-3) imply that welfare reform is associated with a decrease in the cyclicality of cash welfare. With the exception of the adult time limit, the results for food stamp caseloads (columns 4-4 to 4-6) imply that welfare reform led to an increase in the cyclicality of food stamp receipt. However, only 4 of the 12 interaction coefficients reach statistical significance at the 10 percent level or better, and only 3 do so at the 5 percent level or better. Clearly, there is no evidence that welfare reform led to cash assistance caseloads being significantly more cyclically responsive.

Our results are highly robust to several alternative specifications not reported here. We find similar results if we use lagged unemployment rates and if we allow a more flexible state trend (quadratic rather than the linear trends in the main specification). Further, we find no evidence of nonlinear impacts of unemployment rates--we had conjectured that an increase in unemployment from a higher base might lead to larger effects. The results are very similar if we use only data from the 19892010 period. Finally, both the food stamps and cash welfare results are robust to adding controls for the state maximum real AFDC/TANF benefits for a family of three. (Benefit levels are an important state cash welfare policy variable that changes throughout the pre- and post-welfare reform period.) (36)

We conclude from these results that the unemployment rate has a positive, significant, and robust effect on cash welfare and food stamp caseloads. Further, welfare reform is generally associated with reductions in the cyclicality of cash welfare participation and increases in the cyclicality of food stamp participation, although not all interactions reach statistical significance. (37)

III.B. Outcomes for Households and for Single Female Family Heads Using the March CPS

We next analyze data from the pooled 1980-2010 March CPS surveys. Our primary focus is on outcomes for single female-headed families with children (table 5) and on households containing at least one child under 18 (tables 6 and 7). We estimate equation 1 and include controls for the race or ethnicity, sex (where appropriate), age, and education of the woman or the household head. We also examine impacts on various subsamples, including single female family heads with 12 or fewer years of education, households whose head has 12 years of education or fewer, and households with at least one family unit with a single female head and a child. These alternative subsamples are intended to select groups that are relatively more disadvantaged and more likely than the general population to have been at risk of participating in the safety net in general, and cash welfare in particular.

We start by examining impacts on earnings, income, and cash welfare income for a sample of single mothers with children. This is a useful starting place because many prior studies have shown that welfare reform has led to increases in employment for this group (see Blank 2002 for a review). These results (reported in table 5) show robust and statistically significant evidence that cash welfare income is countercyclical and that earnings and income are procyclical. A 1-percentage-point increase in the unemployment rate leads to a $78 (in 2009 dollars, or about 6 percent) increase in yearly public assistance income in the any-reform specification.

The same increase in unemployment leads to about a 1 percent decline in wage and salary income and a 1 percent decline in total (nuclear) family income in the any-reform specification. Further, the interactions between welfare reform and unemployment are largely negative, 8 of the 12 interactions are statistically significant at the 10 percent level or better, and 7 are significant at the 5 percent level or better. A negative coefficient implies that welfare reform led to a decrease in the cyclicality for cash welfare income (since the main effect on unemployment is positive, showing that cash welfare receipt is countercyclical) and an increase in the cyclicality for earnings and total income (since the main effect is negative, showing that earnings and total income are procyclical). This is important because if earnings are more procyclical after reform--falling more in the recent recession than they would have before reform--then greater countercyclicality in the safety net is necessary to maintain the same level of well-being. This combination (less insurance through cash welfare and more vulnerability in recessions) suggests a bad combination of effects. To get a sense of the magnitudes of the interaction coefficients for the any-reform specifications, a 1-percentage-point increase in the unemployment rate after reform would lead to an additional decrease in public assistance income of $4, or about 0.3 percent (with a 95 percent confidence interval of-4.9 to 4.3 percent), an additional decrease in wage and salary income of $356, or about 2.0 percent (95 percent confidence interval of-4.2 to 0.3 percent), and a decrease in total family income of $423, or about 1.6 percent (95 percent confidence interval of -3.3 to 0.1 percent). These findings suggest that increases in unemployment such as that during the recent recession could lead to economically meaningful decreases in earnings and income in the wake of reform. In results not shown, coefficients on the unemployment rate and its interaction with reform are larger in magnitude (more negative) for wage and salary income and for total income for the sample of low-education single female family heads.

Table 6 presents results for our central measure of family well-being, the poverty rate, for all households with children. We present results using both the official poverty measure and our alternative measure, and we measure poverty at the household level. We construct our alternative poverty measure using the existing official thresholds and an expanded measure of household income, which adds to money income the cash value of food stamps, school lunches, and housing subsidies and subtracts payroll taxes and net federal and state taxes (including the EITC). (38) To explore outcomes across the distribution, we look at the fractions of households below 50 percent of the poverty threshold (extreme poverty) and below 100 and 150 percent of the poverty threshold, using total household cash income and our alternative measure of resources including some transfers and taxes. Here we present results for our pre-versus-post measure of welfare reform, where reform is defined as any reform. For each specification we report the coefficients on the main effect for the unemployment rate and its interaction with the welfare reform variable.

Table 6 shows that higher unemployment rates lead to statistically significant increases in official and alternative poverty as well as in the fractions of families below 50 percent and 150 percent of the poverty threshold, using either measure. The any-reform results consistently show that the countercyclicality of poverty increased after welfare reform (positive interaction added to the positive main effect). This is true for our preferred, alternative poverty measure, it holds across all levels of poverty, and the effect sizes are fairly similar across the different poverty measures (all between 1 and 2.5 percent of the mean of the dependent variable). Interestingly, the results reach statistical significance only for 150 percent of official poverty. (Results using time limits or sanction severity are less consistent.) For the low-education household head sample, the findings (not shown in the table), are similar, the magnitudes are about the same as a share of the mean, and the positive interaction coefficient is statistically significant at the 5 percent level for 150 percent of official poverty, and at the 10 percent level for 150 percent of alternative poverty.

Table 7 presents our final set of results for CPS outcomes. The top panel shows results for any household participation in AFDC/TANF, food stamps, SSI, and the broader safety net (non-Medicaid, non-AFDC/TANF safety net benefits). The bottom panel shows the household measures for "anyone uninsured last year," for demographic stress (more than one family in the household, at least one of which has a child), for the presence of any female family head in the household, and for the presence of a woman in the household who is "disconnected" by Blank and Brian Kovak's (2008) definition. (39) To focus on a group with higher likelihood of being affected by welfare, all of the outcomes in this table are estimated on the sample of households with children where the head has 12 years of education or less.

To begin, we use our CPS sample to examine participation in cash welfare and food stamps. We present these results for two reasons. First, given concerns about underreporting in the CPS, it is informative to compare these results with those from the administrative data. If they are similar, it lessens our concern about the importance of underreporting in a pooled cross-sectional analysis with demographic controls and state and year fixed effects. (40) The qualitative conclusions using the CPS sample match those from the administrative results well: cash welfare and food stamps are both countercyclical (with a positive main effect on unemployment), and the magnitudes are in the same ballpark as those for the administrative data. A 1-percentage-point increase in unemployment leads to about a 0.4-percentage-point increase in the probability that someone in the household had cash assistance income last year (this is about a 3.3 percent increase). The same increase in the unemployment rate leads to a 1.0-percentage-point increase in the probability that someone in the household got food stamps last year (about a 5 percent increase). The coefficients on the interaction of reform and the unemployment rate are also positive in both regressions, and the pattern of significance is similar to that in the administrative data (the p-value for the interaction for welfare is 0.105, and that for food stamps is 0.023). (41) The effect of a 1-percentagepoint increase in the unemployment rate on food stamp receipt is about a 4 percent increase after reform. Our conclusion from these specifications is unchanged from that from the administrative caseloads: both programs are cyclically responsive, but only the food stamp program has become significantly more so after reform.

In separate analyses we find that SSI bears little relationship to the business cycle and that this does not change with welfare reform. The final column in the top panel of table 7 reports results for our comprehensive measure of safety net benefits that includes many public assistance programs (but excludes AFDC/TANF, general assistance, and Medicaid). The results here are very clear: overall safety net participation is strongly countercyclical (the main effect is positive and significant, and a 1-percentagepoint increase in unemployment leads to about a 2.1 percent increase in receipt), and the cyclicality significantly increases after welfare reform (the interaction is positive and significant, and again a 1-percentage-point increase in unemployment after reform leads to an additional 2.1 percent increase in receipt). The picture that emerges is that although the effect of cash welfare protection (follow-ing increases in unemployment) has fallen or stayed the same after reform, protection through other safety net programs is increasing.

The bottom panel of table 7 presents other household outcomes. The propensity to be uninsured and the rate of doubling up increase with unemployment, yet the propensity for the household to contain a female head or a disconnected woman does not vary significantly over the cycle. Interestingly, all of the interactions are positive, implying that welfare reform is associated with an increase in the cyclicality of these adverse outcomes. However, these results are only suggestive, as none reaches statistical significance. We also considered a host of other outcomes, none of which showed significant changes in their cyclicality after reform, including the presence of disability income in the household, the presence of any related subfamily with a child, the presence of more than one family with a child, health, and the other measures of disconnected women (results available from the authors on request).

III.C Other Outcomes

The CPS income and poverty measures that we described above are important for capturing the economic well-being of families affected by welfare reform, whereas some of the other outcomes matter for capturing other dimensions such as health insurance coverage or doubling up. A limitation of the income and poverty results is that it is well known that welfare and other government transfers are underreported in the CPS and other household surveys (Meyer, Mok, and Sullivan 2009). This is what motivated our use of both administrative data and an alternative measure of poverty in the micro data. Furthermore, households may save or borrow and may receive private transfers that are not well measured in household survey data.

One common alternative measure of well-being considered in the development literature is consumption, which may be easier to measure than income and poverty in some contexts. Meyer and Sullivan (2008) have used expenditure and time use as alternative measures of well-being and have shown that among single woman-headed families, those low in the income distribution and low in the expenditure distribution experienced different changes from the 1990s to the 2000s. The public use version of the Consumer Expenditure Survey does not contain state identifiers and is available only through the first quarter of 2009, and so we leave these data to be analyzed in future work.

We estimated models for food expenditure using data from the Panel Study of Income Dynamics (available only through 2005). We estimated equation 1 on a sample of female heads of household aged 25-61 living with children, for the period 1980-2005. These results, not shown here, show that increases in the unemployment rate lead to reductions in food consumption, with no evidence that the cyclicality changed with reform (although these estimates had large standard errors relative to the estimated coefficients). We also estimated models for food insecurity, data for which come from the December CPS supplements. (42) The drawback of the food insecurity measures is that because they are consistently available only from 2001 on (our sample goes through 2008), nearly all the variation with which reform's effects on cyclicality are identified is cross-sectional, and thus we do not focus on them.

IV. Discussion

Prior work indicates that participation in cash welfare has decreased with the transition from AFDC to TANF (Council of Economic Advisers 1997, Ziliak and others 2000, and more recently Danielson and Klerman 2008). Why this is so is not fully understood, but possibilities include an interest in "banking" benefits for the future (see, for example, Grogger and Michalopoulos 2003), the burden of complying with work requirements, individuals being removed from the rolls because they reached the time limits, changes in what the state spends TANF money on, and so on. This might lead one to anticipate that the cyclical response of cash welfare would be less strong after welfare reform.

Our view of the results is that cash welfare has indeed become less cyclical after reform, or at least has not become more cyclical, although we caution that our estimated coefficients do not uniformly support this view and that few reach statistical significance. By contrast, our findings for food stamps and a broader measure of "any safety net participation except for AFDC/TANF and Medicaid" suggest an increased sensitivity to the business cycle after reform; for both of these, participation is countercyclical (rising when unemployment rates rise) and becomes more so after reform.

The descriptive evidence about the role that eligibility and take-up play in informing these findings is informative. Our own descriptive work and that of others (for example, Zedlewski 2008) suggest that use of cash assistance did not increase in either the mild recession of 2001 or the most recent recession (with the caveat that unemployment may not have peaked yet). The available evidence suggests that the decline in caseloads after welfare reform (and the lack of increase in the post-welfare reform recessions) is explained almost completely by declines in take-up rather than declines in eligibility (for example, because recipients reached their time limits). The U.S. Department of Health and Human Services (2008) estimates that eligibility for cash welfare has fluctuated within a relatively narrow range, from 5.7 million families in 1995 to 5.1 million in 1999, 4.6 million in 2001, 4.8 million in 2003, and 5.3 million in 2005 (the most recent year available; all years in this paragraph are fiscal years). (43) By contrast, take-up rates have fallen steeply, from 84 percent in 1995 to 48 percent in 2001, 46 percent in 2003, and 40 percent in 2005. At the same time, the number of households eligible for food stamps went up from 15 million in 1995 to 15.2 million in 2001, 17.9 million in 2003, and 18.1 million in 2005, while take-up declined from 69 percent in 1995 to a low of 48 percent in 2001 before rising to 59 percent in 2005. This suggests that the cyclical response in caseloads after welfare reform is driven primarily by changes in take-up.

It would be of interest to know about the effects of the Great Recession on the outcomes of groups who are no longer participating in welfare as well as those that are. Unfortunately, not only is it hard to statistically identify groups who would have been at high risk of participating but are no longer doing so, but many of the outcomes of interest are not well measured or are measured only in small samples. Thus, we again turn to descriptive evidence.

To the extent that women were able to leave welfare through employment, have they been able to stay employed through recessions? Robert Lerman (2005) finds that single mothers lost some ground during the 2001 recession but still were more likely to be employed or in the labor force than before welfare reform. Are workers who might end up unemployed able to access other parts of the safety net such as unemployment compensation? Christopher O'Leary (2010) presents findings from administrative data about experiences of welfare recipients from four states who left welfare for work: 79 percent experienced a new spell of unemployment within 3 years, yet only 24 percent of these applied for unemployment insurance (far below application rates in the general population), and only 50 percent of the applicants eventually received unemployment insurance benefits (also low relative to the general population). In our pooled March CPS data, about 11 percent of households with children who had some public assistance income from 1979 to 2009 also had income from workers' compensation, unemployment compensation, or veterans' payments. This fraction ranged from 7.3 percent of households in 2007 to 16 percent in 2009.

What about the most disadvantaged? Concern has been growing about the part of the pre-reform welfare caseload that was least ready to work. Several recent studies have addressed the experience of so-called disconnected women, single female heads of families with children who neither are participating in cash welfare (TANF and sometimes SSI as well) nor have substantial earnings. Some share of this group is undoubtedly made up of welfare leavers, and some of the leaver studies can inform us about this group. Blank and Kovak (2008) find that among single female-headed families with children with incomes under 200 percent of the poverty line, 20 percent are disconnected. How these families are surviving is a puzzle. More data and research are needed in order to know how to address this issue.

V. Conclusion

The passage of the 1996 welfare reform act led to sweeping changes to the central cash safety net program for families with children, replacing the AFDC program with TANF. The key provisions of that law included work requirements, financial sanctions for noncompliance, and a lifetime time limit for receipt of cash welfare. The imposition of lifetime time limits is particularly noteworthy because it overturned more than 60 years of entitlement to cash welfare for low-income families with children. Despite dire predictions of rising poverty and deprivation, previous research has shown that with reform, caseloads declined and employment increased, with no detectible increase in poverty or reduction in child well-being.

Several important factors likely contribute to explaining "why the experts were wrong." It turns out that as welfare reform hit, earnings subsidies for low-income families with children were rising through expansions in the EITC. Further, the labor market of the first 5 years after welfare reform offered the most favorable conditions for low-skilled workers in many decades. Finally, it seems that the new and stringently applied pro-work policies led to larger behavioral responses than had been expected based on models of the pre-welfare reform period.

This paper has reevaluated welfare reform in light of the severe recession that began in December 2007. In particular, we have examined how reform has altered the cyclicality of the response of program caseloads and family well-being. We find that TANF provides less protection, or at least no more protection, in an economic downturn than the AFDC program that preceded it, but that the noncash welfare safety net (and especially food stamps) is providing significantly more protection. In our analyses using both the official measure and our own alternative measure of poverty, the point estimates imply that the increase in poverty in an economic downturn is greater after welfare reform than it would have been before reform. These results are only suggestive, given that few are statistically significant, but the findings are statistically significant and robust for the propensity to live in a household with income under 150 percent of the official poverty line. We find no significant effect of reform on the cyclical responsiveness of food consumption, food insecurity, or health, or on a number of other measures including doubling up, lack of health insurance, and presence of a single female family head.

Overall, we find no evidence that the prevalence of negative family or household well-being in an economic downturn has improved after welfare reform, and some weak evidence that it has worsened. Further, it appears that food stamp benefits are playing an important role in mitigating adverse impacts on income in post-welfare reform recessions. This suggests a policy recommendation for continued current funding of the food stamp program, should these results hold up with more data and for a broader range of outcomes.

A limitation to our work derives from the fact that we (and others) find a portion of children to be living in families that are "disconnected," with limited income and limited use of public support. Ideally, we would zero in on this particularly fragile group. However, doing this would require better data on family consumption, child and family well-being, and other child outcomes as well as on family histories of welfare and other public assistance and employment and income for large samples of families with children by state and year, and these data are not available.

APPENDIX

Data and Sources

Contractions and Expansions: For table 1 we identified changes over contractions as the range of years from an unemployment low (in terms of the annual unemployment rate) to an unemployment high, and expansions as the range from an unemployment high to an unemployment low. Necessarily, then, the periods of expansion and contraction overlap by one year. Each contraction corresponds to a recession (in one case to two recessions) as identified by the Business Cycle Dating Committee of the National Bureau of Economic Research. We pooled the two early1980s recessions, and the data end in 2009. The contraction periods are 1979-82 (corresponding to the NBER recessions of January to July 1980 and July 1981 to November 1982), 1989-92 (NBER recession of July 1990 to March 1991), 2000-03 (NBER recession of March to November 2001), and 2007-09 (NBER recession of December 2007 to June 2009). The expansion periods are thus 1982-89, 1992-2000, and 2003-07. The end date of 2009 for the most recent contraction may end up not being the peak annual unemployment period, but 2009 is the last year for which the bulk of our data are available. In figures 2, 5, 7, and 8 we have shaded periods of contraction; for these we drop the first one-year period (the unemployment rate low) and thus those periods are 1980-82, 1990-92, 2001-03, and 2008-09.

AFDC/TANF Administrative Data on Caseloads and Expenditure: AFDC caseloads were downloaded from the web site of the Office of Family Assistance, U.S. Department of Health and Human Services (DHHS) at www.acf.hhs.gov/programs/ofa/ data-reports/caseload/caseload_archive. html, and TANF caseloads (which, beginning in 2000, include Separate State Program/Maintenance of Effort cases) from www.acf.hhs.gov/ programs/ofa/data-reports/index.htm. Both measure average monthly case-loads during the year. Unpublished data on AFDC cash expenditure (and combined AFDC/TANF expenditure) for 1980-2000 were provided by Don Oellerich in the Office of the Assistant Secretary for Planning Evaluation at DHHS. TANF expenditure data are from the DHHS website at www.acf.hhs.gov/programs/ofs/data/index.html. TANF cash expenditure is defined as the figure in the second data column (line 5a, "Basic Assistance") of table F-3, "Combined Spending of Federal and States Funds with ARRA Funds Expended... in FY 2009." TANF total expenditure includes all expenditure (maintenance of effort from the state and federal sources, including separate state programs, combined federal and state expenditures on assistance, nonassistance, and both together, as reported in table F, "Combined Spending of Federal and State Funds Expended in FY [year]." Federal stimulus expenditure under the American Recovery and Reinvestment Act of 2009 (ARRA) is included in the 2009 data. AFDC cash assistance numbers for 1979 came from the Green Book of the U.S. House Committee on Ways and Means (waysandmeans.house. gov/singlepages.aspx?NewsID= 10490). The average monthly TANF benefit (used in table 3) is the average family benefit for 2006, expressed in 2009 dollars, from DHHS (2008), appendix A, table TANF-6. All AFDC and TANF data are for the month or the fiscal year (which ends on September 30).

Food Stamp Administrative Data on Caseloads and Expenditure: Caseloads and expenditure by month for calendar years 1980-2009 and for January through March 2010 come from unpublished U.S. Department of Agriculture (USDA) data generously provided by Katie Fitzpatrick and John Kirlin of the Economic Research Service, USDA. Table 1 presents average monthly caseload and total annual payments.

Unemployment Insurance Administrative Data on Caseloads and Expenditure: Data for calendar years 1980 (or in some cases a later starting date) through 2009 are unpublished data provided by the Office of the Chief Economist at the U.S. Department of Labor. The average benefit is the weekly average benefit amount for 2009Q4 from the website of the Employment and Training Administration at the U.S. Department of Labor, at workforcesecurity.doleta.gov/unemploy/content/data_stats/datasum09/ DataSum_2009_4.pdf.

Unemployment for the United States and by State: The number of unemployed and the unemployment rate for the nation as a whole and for each state, annually and by month, come from the Bureau of Labor Statistics' Current Population Survey, accessed at www.bls.gov/cps/and www. bls.gov/lau/. The monthly numbers are seasonally adjusted.

Population for the United States and by State: U.S. population data are from the annual Economic Report of the President, accessed at www. gpoaccess.gov/eop/2010/B34.xls. State population data are from the National Cancer Institute's SEER (Surveillance Epidemiology and End Results, at seer.cancer.gov/popdata/download.html) for 1980-2007, and from the U.S. Census Bureau for 2008 on.

Deflator: The CPI-U is from the Economic Report of the President, accessed at www.gpoaccess.gov/eop/tables 10.html.

Census Poverty Rates: Official poverty, all persons, and official poverty, children, come from the U.S. Census Bureau, "Income, Poverty, and Health Insurance Coverage in the United States: 2009," report P60-238, tables B-1 and B-2. NAS alternative poverty numbers come from the U.S. Census Bureau web site, at www.census.gov/hhes/www/povmeas/web_ tab4 nas measures_historical.xls, "Official and National Academy of Sciences (NAS) Based Poverty Rates: 1999 to 2008." We report the series MSI-NGA-CE, in which imputed out-of-pocket medical expenses are subtracted from income (MSI), no geographic adjustments are made (NGA), and the thresholds are based on consumption data from the Consumer Expenditure Survey (CE).

EITC: Data on the annual number of recipients and the total tax cost (including refundable and nonrefundable portions) of the EITC for 19802008 are from the Tax Policy Center's "Tax Facts: Historical EITC Recipients" for fiscal 1976-2010, downloaded from www.taxpolicycenter. org/taxfacts/displayafact.cfm?Docid=37.

SSI: Data on number of recipients (those who received any payment during the year), total benefit payments, and average monthly benefit are from Social Security Administration (2010) and refer to federal plus state supplementation program.

Other sources for tables 1 and 3 include the following:

--Consumption: statistics for expenditure by "Quintiles of income before taxes," published by the Bureau of Labor Statistics and available at www.bls.gov/cex/csxstnd.htm.

--Food insecurity: based on Food Security Supplements to the December Current Population Survey for 2001-2008, compiled by Craig Gundersen and Feeding America and graciously shared with us by Gundersen.

--Health insurance and delayed/didn't get care because of cost: data published by the Centers for Disease Control in "Health Insurance Coverage Trends, 1959-2007" (www.cdc.gov/nchs/data/nhsr/nhsr017.pdf) as well as annual reports based on the National Health Interview Survey ("Summary Health Statistics for the U.S. Population: National Health Interview Survey," various years).

--Homeless: from the Office of Community Planning and Development, U.S. Department of Housing and Urban Development, "Annual Homeless Assessment Report to Congress," for 2007 and 2009.

ACKNOWLEDGMENTS We thank the editors, Sandy Jencks, Bruce Meyer, Rebecca Blank, Karl Scholz, Dan Wilson, Bart Hobijn, Mary Daly, Rob Valletta, and Caroline Danielson; seminar participants at the Federal Reserve Bank of San Francisco; and Brookings Panel conference participants for helpful suggestions. We thank Jessamyn Schaller, Danielle Sandler, Ankur Patel, Ted Wiles, and Joyce Kwok for excellent research assistance. We also thank Robert Moffitt, Jim Ziliak, Donna Pavetti, Patty Anderson, Rob Valletta, Don Oellerich, John Kirlin, Caroline Danielson, Paige Shevlin, David Langon, and Katie Fitzpatrick, who generously shared data and expertise on administrative and labor market data. The views in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Federal Reserve Bank of San Francisco or the Board of Governors of the Federal Reserve System.

The authors report no relevant potential conflicts of interest.

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MARIANNE P. BITLER

Federal Reserve Bank of San Francisco

HILARY W. HOYNES

University of California, Davis

(1.) Comprehensive reviews can be found in Blank (2002) and Grogger and Karoly (2005). The research summarized there focuses on the effects of reform on program participation, income and earnings, consumption, child outcomes, and a host of other measures.

(2.) The effect of the Great Recession on the operation of the safety net for the elderly is also an important topic, but not one within the scope of this paper.

(3.) The official poverty thresholds were developed in 1963 and 1964 and adopted in 1969, and official statistics are available back to 1959. The thresholds have been adjusted each year to reflect changes in the cost of living, using the CPI-U. but otherwise have changed little since their creation. The Census Bureau is developing a supplemental poverty measure to be published in addition to the official measure. The supplemental measure is intended to incorporate many of the suggestions of the NAS report on the poverty measure. The Census Bureau and the Bureau of Labor Statistics have long examined various alternative measures of both income and thresholds and have published various experimental series (for example, Dalaker 2005); they have also explored whether the NAS recommendations could be implemented (for example, Garner and Short 2008).

(4.) In our own empirical analysis of the March CPS data below, we are able to construct a consistent alternative poverty measure for calendar years 1980-86, 1988-90, and 1991-2008. Because of Census data limitations at the time of writing, the Census tabulations for the NAS measure as well as our own tabulations of alternative poverty are not yet available for 2009.

(5.) The official NBER recession dating is monthly, whereas most of our analyses in the paper rely on annual data. Therefore we constructed an annual series for contractions based on the official monthly dates, augmented by examination of the peaks and troughs in the national unemployment rate. See the appendix for a comparison of NBER monthly recession dating and our annual contraction dating.

(6.) After welfare reform, states had flexibility to spend federal block grant funding on not only cash assistance, but also other noncash aid such as subsidized child care, transportation, and education and training. The total expenditure series includes spending from all sources. We discuss this further below.

(7.) These calculations are based on the 1996 and 2010 March CPS, which collects information on current living arrangements and on income, transfers, and health insurance coverage for the preceding calendar year. Like all sample surveys, the CPS relies on self-reports, and as in many such surveys, income is underreported. The degree of underreporting varies both over time and across types of income as well as by recipiency and total dollar amounts. (Weinberg 2004 summarizes some of the issues; see also specific studies such as Meyer, Mok, and Sullivan 2009, Wheaton 2007, and Bitler, Currie, and Scholz 2003.) In part because of this concern about the validity of self-reports of income from public assistance and other programs, we also present results using administrative counts.

(8.) It may seem surprising that we find just over a quarter of families receiving welfare to have married heads. However, under AFDC, states could offer benefits to support children in two-parent families where the primary earner was unemployed (in 1995, these families accounted for 7 percent of cases; U.S. House of Representatives 1996), and under TANF, many of the eligibility rules distinguished far less between two- and one-parent families. Further, because family structure is measured as of March whereas income is measured for the preceding calendar year, some share of individuals may have gotten married after having been on cash assistance.

(9.) In these tabulations, a family is identified as a welfare recipient if it received any public assistance income (AFDC/TANF or other) during the previous calendar year. We measure employment as of the week before the survey. (We can also measure any employment during the last calendar year.) Consequently, because one cannot tell from the CPS whether people had earnings when they were also receiving cash assistance, the CPS does not allow for identification of simultaneous welfare and work status.

(10.) This measure takes a value of 1 for any household where a member is reported as participating in food stamps, SSI, public housing or rental subsidies, free or reduced-price school lunches, or energy assistance during the calendar year before the survey.

(11.) Food security is a measure of households having enough nutritionally adequate and safe foods or having assured ability to acquire acceptable foods in socially acceptable ways (for example, not through emergency food supplies or scavenging). Haider (2006) describes advantages and disadvantages of this measure of well-being, which contains a psychological component.

(12.) These figures update earlier graphs from a presentation by LaDonna Pavetti, "Responding to Increasing Need: Assessing TANF's Responsiveness during Hard Economic Times," Center for Budget and Policy Priorities, June 3, 2010.

l3. We are unable to update this figure to 2009 because the amount of food stamps per household has not yet been released by the Census Bureau as of this writing.

(14.) The share of income provided by food stamps might increase mechanically if families leave welfare and do not replace all of their welfare income, because the food stamp program reduces benefits by 30 cents for each dollar of other income.

(15.) These calculations for poverty alleviation perform the hypothetical exercise of eliminating one program at a time while maintaining all of the others. The exact numbers differ somewhat from study to study: for another set of estimates see Meyer (2010). Of course, EITC eligibility rules mean most EITC benefits are received by individuals near the poverty line, thus making it more likely for the EITC to lift families out of poverty. Other programs such as AFDC/TANF have eligibility thresholds further from the poverty line, making it less likely they will lift families out of poverty.

(16.) Other cash or near-cash programs of relevance for families with children include public housing and vouchers and rent subsidies, other nutrition programs (the National School Lunch and Breakfast programs, WIC), energy assistance, and state general assistance programs. In addition, Medicaid provides health insurance for poor children and families, and higher-income (but still low-income) children are eligible for SCHIP.

(17.) More precisely, a family had to show that the children were deprived of parental support by the absence, incapacitation, or (in some states and some periods) unemployment of one parent. In practice, throughout its history more than 90 percent of the AFDC caseload consisted of single mothers (see U.S. Department of Health and Human Services 2008, appendix A, table TANF-1). Large changes in the mid-1960s expanded the program considerably for unmarried mothers.

(18.) The 1990s reforms were by no means the first reforms of AFDC. Without a doubt, however, they were the furthest reaching, and today "welfare reform" generally refers to those changes.

(19.) Enhanced earnings disregards refer to changes in the benefit formula to reduce the rate at which earnings are "taxed" by the welfare system and thus increase incentives to work. Other changes adopted by some states include expanding eligibility for two-parent families, "family caps" (freezing benefits at the level associated with current family size), and imposing residency and schooling requirements for unmarried teen recipients. For a detailed discussion of the policy changes, see Blank and Haskins (2001) and Grogger and Karoly (2005).

(20.) The 5-year lifetime limit on receipt of federal TANF assistance applies to adult-headed families, but the law allowed states to exempt from this limit for hardship reasons up to 20 percent of their total caseload.

(21.) Note that eligibility for many federal safety net programs is based on poverty guidelines, which are simplified versions of the Census poverty thresholds, varying by fewer dimensions and made available earlier in the year. Poverty guidelines vary by number of persons and are different for Alaska and Hawaii than for the rest of the states and the District of Columbia. See aspe.hhs.gov/poverty/figures-fed-reg.shtml.

(22.) Technically, the 3-months-in-3-years limitation applied to able-bodied adults aged 18-49 with no dependents who were not working, in a work program, or doing workfare. Individuals are exempt if they are caring for a child, are unable to work, or are pregnant. States can exempt 15 percent of individuals and can get this provision waived if the state unemployment rate is above 10 percent or if the state is eligible for state extended unemployment benefits or there are not enough jobs.

(23.) Diversion payments are one-time payments made in lieu of monthly benefit payments at the recipient's request.

(24.) In the March CPS from 2001 to 2009. individuals were asked whether they had obtained transportation assistance or child care assistance so that they could work or go to school or training; they were also asked whether they had obtained job readiness training or attended a job search class or job club or participated in GED classes or a community service job as a condition of receiving cash assistance. We combined these into two household-level variables. Although these activities need not all be funded by TANF, surely some are. From 2000 to 2008. 2.5 percent of households included someone getting child care assistance or transportation assistance: 3.4 percent of households had someone in job readiness, job search, GED classes, or community service, compared with 3.8 percent of households in which one or more members received public assistance income. Furthermore, most of the households with cash welfare did not get either of the two other supports, and vice versa: among households with a child under 18, only 30 percent of those getting cash welfare had someone getting one of these other noncash benefits, while of those getting the noncash benefits, only 21 percent got public assistance income.

(25.) The caseload is essentially a count of families or households, whereas the denominator is a count of persons. Although it might be more intuitive to put the number of recipients in the numerator, the caseload measure is more commonly used to abstract away from changes in the size of families receiving benefits. In practice, trends in the ratio of recipients to population look quite similar to those presented here.

(26.) Over the early 2000s, and culminating in provisions included in the 2002 farm bill, the U.S. Department of Agriculture implemented a number of provisions to expand food stamp access by allowing more state policy choices in recertification and reporting and funding some outreach. Klerman and Danielson (2009) look at the effects of these changes and changes in the labor market on food stamp caseloads through 2004.

(27.) Toward the end of the period depicted in figure 7, in order to remain in compliance with various TANF requirements, many states moved portions of their caseloads off TANF and into new, "solely state-funded" programs. Data collected by LaDonna Pavetti of the Center for Budget and Policy Priorities suggest that these programs are relatively small and show small increases in the recent recession.

(28.) We also include household participation in cash welfare and food stamps, as measured in the CPS, in figure 8. We find it encouraging that the trends in participation are so similar to those seen in the administrative data.

(29.) We have also explored other measures of the cycle, including other labor market measures (employment-to-population ratios or employment growth) and, alternatively, GDP growth, which maps more naturally onto the official recession dating. Although the magnitudes differ, the qualitative conclusions are similar to those reported here.

(30.) Our central parameter, on the interaction between the unemployment rate and welfare reform, would still be identified if reform were captured by a national pre-versus-post1996 variable (because the unemployment rate still varies by state). However, we use state variation in reform, which we view as a more credible source of identification.

(31.) Because our data on food stamp caseloads begin in 1980. the second middle panel measures the percent change in food stamp caseloads between 1980 and 1982, but the change in unemployment rates from 1979 to 1982.

(32.) Whereas the timing and the presence of waivers vary considerably across states, TANF implementation varies minimally, as all states implemented TANF in late 1996, 1997, or 1998. See table 1 of Bitler, Gelbach, and Hoynes (2006) for implementation dates and an example of a paper using this identification strategy.

(33.) We thank Caroline Danielson of the Public Policy Institute of California for generously providing us with their data and coding.

(34.) Weinberg (2004) discusses a host of such studies related to underleporting in the CPS and other Census surveys; Wheaton (2007) documents underreporting of benefit receipt in the CPS.

(35.) Jason DeParle and Robert Gebeloff, "Food Stamp Use Soars, and Stigma Fades," The New York Times, November 29, 2009.

(36.) We thank Rebecca Blank for suggesting that we control for this variable, especially since our time period 1980-2009 contains a long period before welfare reform. Our results are also unchanged if we incorporate the solely state funded program caseload (data obtained from LaDonna Pavetti and starting in 2006) into our measure of state cash welfare caseloads.

(37.) We also examined similar models for unemployment compensation and found stronger countercyclical responses than of cash welfare or food stamps to the unemployment rate (not surprisingly/ but no evidence that the use of unemployment compensation over the business cycle has been affected by welfare reform.

(38.) We constructed this alternative measure ourselves, making every effort to maintain consistency over time while including as many components of CPS experimental poverty measures as possible (see, for example, Dalaker 2005). This measure is available only for a subset of survey years: 1980-87, 1989-90. and 1992-2008 (2009 calendar-year data had not been released at the time of this writing).

(39.) More precisely, our definition approximates Blank and Kovak's definition 1, in which a disconnected woman is a single female family head aged 18-58 living with a child, with no income from public assistance or earnings. We also explored two other definitions. The first defines a disconnected woman as a single female family head aged 18-58 living with a child and earning less than $2,000 a month while receiving income from public assistance of less than $1,000 a month (both figures in 2009 dollars): the second adds the restriction that real monthly income from SSI is less than $1,000. Results were similar across measures.

(40.) For another approach to dealing with underreporting in a recent analysis of trends in poverty, see Scholz, Moffitt, and Cowan (2009).

(41.) They should not be identical for the following reasons. First. the administrative data are monthly and define the main reform variable as a dummy for implementation by a particular month, whereas the CPS data are annual and the reform variable is the share of the calendar year that reform was in place. Second, the sample in the administrative regressions is everyone (with the dependent variable having the total caseload in the numerator and total population in the denominator), whereas the CPS sample is households with children and a low-educated head (with the dependent variable being the presence or absence of someone in the household receiving the benefit). Third, the CPS welfare variable includes other FOrms of public assistance such as general assistance.

(42.) Craig Gundersen and Feeding America generously provided us with tabulations on state-year rates of food insecurity.

(43.) These estimates are based on the Urban lnstitute's TRIM3 microsimulation model, which uses March CPS data (adjusted for nonresponse) and simulates eligibility for AFDC/TANF. The report also presents results from a Mathematica microsimulation model of food stamp eligibility (Cunnyngham, Castner, and Schirm 2010).

Table 1. Changes in Unemployment, Safety Net Program Expenditure, and
Family Well-Being across Contractions and Expansions (a) Percentage
points except where stated otherwise

                                                     Contractions

Statistic                         1979-82   1989-92   2000-03   2007-09

Change in unemployment rate           3.9       2.2       2.0   4.7 (b)
  (annual average)

Changes in real safety net
  expenditure per capita
  (in percent)
AFDC/TANF assistance payments         -14        10       -17        -2
AFDC/TANF total expenditure          n.a.      n.a.        -3         8
Food stamps                            11        48        36        68
Unemployment insurance, state        n.a.        52        84       150
  regular plus extended
Unemployment insurance, all          n.a.       132       132       277
EITC                                  -37        68         9  -0.4 (c)

Changes in family well-being:
  employment and poverty
Official poverty rate, all            3.3       2.0       1.2       1.8
  persons
Official poverty rate,                5.5       2.7       1.4       2.7
  children
Official extreme poverty rate,       n.a.       2.1       1.2       1.5
  children
NAS alternative poverty rate,        n.a.       n.a.      1.0   0.6 (c)
  all persons
Share of single women with           -1.9      -1.4      -3.3      -3.9
  children with job last week
Share of single women with           -0.8       0.7       0.6       0.4
  children out of labor force
  last week
Share of children receiving          n.a.       4.3       1.3       4.5
  any non-AFDC/TANF,
  non-Medicaid safety net
  benefit

Changes in family well-being:
  consumption and food
  insecurity
Real consumption by lowest
  income quintile (percent)
  Total consumption                  n.a.      -7.8      -3.5       2.0
  Food consumption                   n.a.      -9.3      11.3      11.5
Share of households                  n.a.      n.a.      n.a.   3.2 (c)
  experiencing food insecurity

Changes in family well-being:
  demographic and housing
  stress
Share of children living in           2.9       1.7       0.4       0.2
  female-headed family
Share of children living in           2.9       1.0      -0.1       0.2
  household with more than
  one family

Changes in health insurance
  and access
Share of nonelderly persons           1.9       1.2      -0.3       1.0
  uninsured
Share of persons who delayed         n.a.      n.a.       1.4       3.4
  care or had no care because
  of cost

Homelessness (change in
  number of persons)
Persons on the street at a           n.a.      n.a.      n.a.   -41,000
  given point in time
Persons ever using shelter or        n.a.      n.a.      n.a.   -30,000
  transitional housing over
  past year
Families ever using shelter          n.a.      n.a.      n.a.    62,000
  or transitional housing
  over past year

                                           Expansions

Statistic                         1982-89   1992-2000   2003-07

Change in unemployment rate          -4.4        -3.5      -1.4
  (annual average)

Changes in real safety net
  expenditure per capita
  (in percent)
AFDC/TANF assistance payments          -2         -63       -24
AFDC/TANF total expenditure          n.a.         -17       -13
Food stamps                           -10         -48        19
Unemployment insurance, state         -56         -41       -33
  regular plus extended
Unemployment insurance, all          n.a.         -61       -47
EITC                                  171          84         7

Changes in family well-being:
  employment and poverty
Official poverty rate, all           -2.2        -3.5       0.0
  persons
Official poverty rate,               -2.3        -6.1       0.4
  children
Official extreme poverty rate,       -1.7        -3.4      -0.1
  children
NAS alternative poverty rate,       n. a.        n.a.       1.6
  all persons
Share of single women with            3.0        14.6       0.5
  children with job last week
Share of single women with           -0.8       -11.9       1.8
  children out of labor force
  last week
Share of children receiving          -2.2        -3.9      -1.1
  any non-AFDC/TANF,
  non-Medicaid safety net
  benefit

Changes in family well-being:
  consumption and food
  insecurity
Real consumption by lowest
  income quintile (percent)
  Total consumption                  n.a.        15.6      -1.8
  Food consumption                   n.a.        -3.9     -15.3
Share of households                  n.a.        n.a.       0.2
  experiencing food insecurity

Changes in family well-being:
  demographic and housing
  stress
Share of children living in           1.4        -0.7       0.8
  female-headed family
Share of children living in           0.3         0.0       1.0
  household with more than
  one family

Changes in health insurance
  and access
Share of nonelderly persons           1.7         0.0       0.1
  uninsured
Share of persons who delayed         n.a.        n.a.       0.8
  care or had no care because
  of cost

Homelessness (change in
  number of persons)
Persons on the street at a           n.a.        n.a.      n.a.
  given point in time
Persons ever using shelter or        n.a.        n.a.      n.a.
  transitional housing over
  past year
Families ever using shelter          n.a.        n.a.      n.a.
  or transitional housing
  over past year

Sources: Various published sources and authors' calculations from
March Current Population Survey data. For details on sources and
methods, see the appendix.

(a.) n.a. = not available.

(b.) Change from 2007 to 2008 is 1.2 percentage points.

(c.) Change from 2007 to 2008.

Table 2. Characteristics of Families Receiving Public Assistance
Income in 1995 and 2009, and of All Families in 1995 (a)

Percent except where stated otherwise

                                     Families with
                                  children receiving     All families
                                     cash welfare,      with children,
Characteristic                         1995 (b)            1995 (c)

Heads of family
Percent white, non-Hispanic              39.0                69.7
Percent black, non-Hispanic              33.9                13.6
Percent Hispanic                         21.5                12.0
Percent female                           78.4                36.7
Percent with <12 years                   40.5                15.8
  education
Percent with exactly                     34.0                31.8
  12 years education
Percent with >12 years                   25.5                52.4
  education
Percent never married                    37.6                 8.8
Percent divorced, separated,             34.7                18.4
  or widowed
Percent married                          27.7                72.9
Average age (years)                      33.9                38.2
Percent insured                          96.6                85.6
Percent working last week                30.6                80.3
Percent out of the labor                 56.0                14.3
  force last week

Families
Percent in household receiving           86.5                14.4
  food stamps
Percent in household in public           32.8                 6.0
  or subsidized housing
Percent in household owning              16.6                64.3
  home
Percent with child insured               98.9                87.4

                                     Families with
                                  children receiving
                                     cash welfare,
Characteristic                         2009  (b)

Heads of family
Percent white, non-Hispanic              37.5
Percent black, non-Hispanic              34.4
Percent Hispanic                         23.9
Percent female                           82.2
Percent with <12 years                   33.8
  education
Percent with exactly                     33.4
  12 years education
Percent with >12 years                   32.8
  education
Percent never married                    45.1
Percent divorced, separated,             27.4
  or widowed
Percent married                          27.6
Average age (years)                      35.4
Percent insured                          94.4
Percent working last week                34.1
Percent out of the labor                 49.1
  force last week

Families
Percent in household receiving           82.1
  food stamps
Percent in household in public           32.1
  or subsidized housing
Percent in household owning              19.9
  home
Percent with child insured               99.1

Sources: Authors' tabulations of 1996 and 2010 March CPS data.

a. Demographics and living arrangements are as of the time of the
survey (March 1996 or 2010); income and program receipt refer to
calendar year 1995 or 2009.

b. Families with at least one child and receiving public assistance
income (AFDC. TANF, or general assistance).

c. All families with at least one child.

Table 3. Expenditure on and Participation in Cash or Near-Cash Safety
Net Programs, 2009, and Children Removed from Poverty, by Program,
2009 (a)

                                                         Total
                                                        benefit
                                                        payments
                                                       (millions
Program                                  Thousands    of dollars)

Cash welfare (TANF) (b) (cases)              1,796          9,324
Food stamps (cases)                         15,232         50,360
EITC (c) (tax filing units)                 24,757         50,669
Cash welfare (SSI, nonaged caseload)         6,407         41,023
Unemployment compensation (persons)
  Regular state benefits                     n.a.          79,600
  Extended benefits                          n.a.           7,574
  Emergency benefits                         n.a.          44,246
  Total                                      5,757        131,420

                                                       Estimated
                                                        no. of
                                                       children
                                          Average       removed
                                          monthly        from
                                          benefit       poverty
Program                                  (dollars)    (millions)

Cash welfare (TANF) (b) (cases)               397           0.8
Food stamps (cases)                           276           2.2
EITC (c) (tax filing units)                   171           2.6
Cash welfare (SSI, nonaged caseload)          517           1.0
Unemployment compensation (persons)
  Regular state benefits                    1,335          n.a.
  Extended benefits                          n.a.          n.a.
  Emergency benefits                         n.a.          n.a.
  Total                                      n.a.          n.a.

Sources: For children removed from poverty see Sherman (2009). For all
other sources seethe appendix.

(a.) Data refer to calendar 2009 and are in 2009 dollars except where
noted otherwise.

(b.) Data refer to fiscal 2009.

(c.) Data refer to 2008 and are in 2008 dollars.

Table 4. Regressions Estimating Impacts of the Business Cycle and
Welfare Reform on Cash Welfare and Food Assistance Caseloads (a)

                                          Dependent variable

                                    AFDC/TANF caseload-population
                                            ratio x 100

Independent variable               4-1           4-2           4-3

State unemployment rate         0.058 ***     0.066 ***     0.065 ***
                               (0.010)       (0.011)       (0.013)
Unemployment rate x any         0.012
  reform                       (0.023)
Unemployment rate x short                    -0.026
  time limit                                 (0.022)
Unemployment rate x long                     -0.039 *
  time limit                                 (0.020)
Unemployment rate x adult                    -0.046 ***
  time limit                                 (0.015)
Unemployment rate x full                                   -0.018
  sanction                                                 (0.013)
Unemployment rate x gradual                                -0.010
  sanction                                                 (0.019)
Mean of dependent variable      1.234         1.234         1.234
No. of observations            18,360         18,360        18,360
Adjusted [R.sup.2]             0.95           0.95          0.95

                                          Dependent variable

                                   Food stamp caseload-population
                                           ratio x 100

Independent variable               4-4           4-5           4-6

State unemployment rate         0.171 ***     0.187 ***     0.159 ***
                               (0.027)       (0.024)       (0.020)
Unemployment rate x any         0.050
  reform                       (0.042)
Unemployment rate x short                     0.20
  time limit                                 (0.059)
Unemployment rate x long                      0.000
  time limit                                 (0.045)
Unemployment rate x adult                    -0 173
  time limit                                 (0.036)
Unemployment rate x full                                    0.138 **
  sanction                                                 (0.056)
Unemployment rate x gradual                                 0.105
  sanction                                                 (0.063)
Mean of dependent variable      3.499         3.499         3.499
No. of observations             18,417       18,417        18,417
Adjusted [R.sup.2]              0.9           0.91          0.91

Source: Authors' regressions. See the appendix for details on data
sources and coding of welfare reforms.

(a.) Regressions were performed on monthly data on program caseloads
per capita by state and year from January 1980 through December 2009
(for AFDC/TANF) and January 1980 through March 2010 (for food stamps).
Observations for food stamp cases are missing for Vermont for October
1988 through September 1996. Models also include a full set of time
fixed effects, state fixed effects, state-specific linear time trends,
and main effects for welfare reform. Welfare reform policies are state
policies in place in the month before the caseload month. Asterisks
indicate statistical significance at the *** 1 percent, **5 percent,
and * 10 percent level.

Table 5. Regressions Estimating Impacts of the Business Cycle and
Welfare Reform on Earnings and Income for Single Female Family Heads
with Children (a)

                                   Dependent variable

                              Annual public assistance income

Independent variable            5-1         5-2         5-3

State unemployment rate         78 ***      9l ***      81 ***
                               (20)        (14)        (16)
Unemployment rate x any         -4
  reform                       (28)
Unemployment rate x short                  -99 ***
  time limit                               (24)
Unemployment rate x long                   -63 **
  time limit                               (28)
Unemployment rate x adult                 -109 ***
  time limit                               (25)
Unemployment rate x full                               -23
  sanction                                             (27)
Unemployment rate x                                     13
  gradual sanction                                     (26)
Mean of dependent variable     1,224       1,224       1,224
Adjusted [R.sup.2]             0.19        0.19        0.19

                                     Dependent variable

                                 Annual wage and salary income

Independent variable             5-4          5-5          5-6

State unemployment rate         -214 ***     -277 ***     -250 ***
                                 (56)         (73)         (70)
Unemployment rate x any         -356 *
  reform                        (200)
Unemployment rate x short                    -498 **
  time limit                                 (212)
Unemployment rate x long                     -245
  time limit                                 (255)
Unemployment rate x adult                     142
  time limit                                 (296)
Unemployment rate x full                                  -353
  sanction                                                (222)
Unemployment rate x                                       -493 **
  gradual sanction                                        (191)
Mean of dependent variable     17,866       17,866       17,866
Adjusted [R.sup.2]              0.19         0.19         0.19

                                    Dependent variable

                                Total annual family income

Independent variable             5-7         5-8        5-9

State unemployment rate        -297 ***    -390 ***    -357
                                (76)        (72)        (50)
Unemployment rate x any        -423 *
  reform                       (218)
Unemployment rate x short                  -403
  time limit                               (250)
Unemployment rate x long                   -276
  time limit                               (251)
Unemployment rate x adult                    47
  time limit                                303)
Unemployment rate x full                               -394 **
  sanction                                             (177)
Unemployment rate x                                    -409 **
  gradual sanction                                     (194)
Mean of dependent variable     26,465      26,465      26,465
Adjusted [R.sup.2]              0.23        0.23        0.23

Source: Authors' regressions.

(a.) Regressions are performed on data from the 1980/2010 March
Current Population Surveys; outcomes refer to the preceding calendar
year and thus cover 1980/2009. Observations are by family, and the
sample includes single female family heads living with a child. Models
also include year fixed effects, state fixed effects, state specific
linear time trends, main effects for welfare reform, and demographic
controls for race/ethnicity, age, and education of the woman. The main
reform variable is measured as the share of the past calendar year
that the reform was in place, and the time limit policies were coded
according to what was in place in December. Number of observations is
181,353 in all regressions. Asterisks indicate statistical
significance at the *** I percent, ** 5 percent, and * 10 percent
level.

Table 6. Regressions Estimating Impacts of the Business Cycle and
Welfare Reform on Poverty (a)

                                 Dependent variable: share of all
                                 households with children in
                                 indicated group

                                     By official poverty measure

                                 Below 50%    Below 100%   Below 150%
                                 of poverty   of poverty   of poverty
Independent variable             line         line         line

State unemployment rate          0.0030 ***   0.0064 ***   0.0073 ***
                                 (0.0005)     (0.0008)     (0.0011)
Unemployment rate x any reform   0.0007       0.0023       0.0036 **
                                 (0.0012)     (0.0016)     (0.0018)
Mean of dependent variable       0.059        0.150        0.249
No. of observations              759,990      759,990      759,990
Adjusted [R.sup.2]               0.10         0.19         0.23

                                 Dependent variable: share of all
                                 households with children in
                                 indicated group

                                    By alternative poverty measure

                                 Below 50%    Below 100%   Below 150%
                                 of poverty   of poverty   of poverty
Independent variable             line         line         line

State unemployment rate          0.0014 ***   0.0057 ***   0.0075 ***
                                 (0.0004)     (0.0008)     (0.0013)
Unemployment rate x any reform   0.0007       0.0013       0.0027
                                 (0.0008)     (0.0022)     (0.0019)
Mean of dependent variable       0.029        0.123        0.263
No. of observations              682,762      682,762      682,762
Adjusted [R.sup.2]               0.03         0.15         0.22

Source: Authors' regressions.

(a.) Regressions are performed on data from the 1981-2010 March CPS;
outcomes refer to the preceding calendar year and thus cover 1980-
2009 (except for alternative poverty, which covers only 1980-86, 1988-
89, and 1991-2008). Observations are by household, and the sample
includes all households with a child under 18. Models also include
year fixed effects, state fixed effects, state/specific linear time
trends, main effects for welfare reform, and demographic controls for
race/ethnicity, age, sex, and education of the household head. The
main reform variable is measured as the share of the past calendar
year that the reform was in place, and the time limit policies are
coded according to what was in place in December. Asterisks indicate
statistical significance at the *** 1 percent, ** 5 percent, and * 10
percent level.

Table 7. Regressions Estimating Impact of the Business Cycle and
Welfare Reform on Safety Net Participation and Household Well-Being (a)

                        Dependent variable: probability that household
                               received indicated assistance (b)

                                                             Any non-
                                                             Medicaid,
                           Any        Any                   non-AFDC/
                         public       food                 TANF safety
Independent variable   assistance    stamps      Any SSI    net benefit

State unemployment      0.004 ***    0.010 ***  -0.001      0.008 ***
  rate                 (0.001)      (0.002)     (0.0004)   (0.002)
Unemployment rate x     0.005        0.008 **    0.0004     0.008 **
  any reform           (0.003)      (0.003)     (0.001)    (0.003)
Mean of dependent       0.122        0.199       0.044      0.387
  variable
No. of observations    378,067      378,067     378,067     361,340
Adjusted [R.sup.2]      0.17         0.17       0.04         0.21

                        Dependent variable: probability that household
                               had indicated characteristic (b)

                         Anyone                    Any      Any family
                          lacks     Household    family      head is a
                         health      contains    head is   disconnected
                        insurance   >1 family    female      woman (c)

State unemployment       0.006 **    0.002 **   -0.0004       0.0003
rate                    (0.003)     (0.001)     (0.001)      (0.0005)
Unemployment rate x      0.001       0.001       0.004        0.001
any reform              (0.003)     (0.001)     (0.003)      (0.001)
Mean of dependent        0.357       0.092       0.293        0.041
variable
No. of observations     346,817     381,817     381,817      381,817
Adjusted [R.sup.2]       0.09        0.13        0.46         0.05

Source: Authors' regressions

(a.) Regressions are performed on data from the 1980-2010 March CPS.
Program participation and lack of insurance refer to the preceding
calendar year and thus cover 1980-2009; living arrangements refer to
the time of the survey. Observations are by household, and the sample
includes all households with a child under 18 headed by someone with a
high school education or less. Models also include year fixed effects,
state fixed effects, state-specific linear time trends, main effects
for welfare reform, and demographic controls for race/ethnicity, age,
sex, and education of the household head. For outcomes measured over
the last calendar year, the main reform variable is measured as the
share of the past calendar year that reform was in place. and the time
limit policies are coded according to what was in place in December of
that year. For outcomes measured at the time of the survey, welfare
reform is measured by whether the policy was in place as of March of
the survey year. Asterisks indicate statistical significance at the
*** 1 percent, ** 5 percent, and * 10 percent level.

(b.) Sample consists of households with children whose head has less
than 12 years of education.

(c.) Defined similarly to Blank and Kovak (2008) as a single female
family head aged 18-58 living with a child, with no income from public
assistance or earnings.

Comments and Discussion

COMMENT BY CHRISTOPHER JENCKS

Marianne Bitler and Hilary Hoynes have provided the most comprehensive treatment to date of how low-income families with children fared during the first 3 years since the recent recession began. Their primary goal however, is not to chronicle what happened to these families but to investigate whether they would have fared better if the pre-1996 welfare system had still been in place. Simply tracking what has happened to these families since 2007 is a challenging task, partly because there are dozens of potentially relevant indicators and no agreement about their relative importance, and partly because the U.S. statistical system takes so long to produce many of these indicators. Figuring out what would have happened in the absence of welfare reform is even more challenging, because the details of this counterfactual are so uncertain. I take up these two issues in turn.

WHAT HAPPENED BETWEEN 2007 AND 2010? According to the National Bureau of Economic Research, the economy began to contract in December 2007 and began to grow again in July 2009. But for families that derive most of their income from the labor market, what matters is not whether the economy is contracting or expanding, but whether demand for workers is growing fast enough to provide jobs for a growing population of adults who want work. Bitler and Hoynes therefore use the unemployment rate to estimate the impact of the business cycle on family income and other measures of well-being.

If we judge by official statistics on employment and population growth, the number of would-be workers has grown faster than the number of jobs since the summer of 2007. and the gap continued to widen even after the official unemployment rate peaked in October 2009. The official unemployment rate began to decline in the fall of 2009 because more unemployed workers stopped searching for jobs and were therefore dropped from the official unemployment count. If the job market tightens, most of these "discouraged" workers will start looking again. That means they must be taken into account both when we assess how many families have been affected by the downturn and when we estimate how many additional jobs would be needed to get the unemployment rate down to the level that prevailed in the middle of 2007.

One imperfect way to address this problem is to assume that the overall fraction of adults who want a job is likely to be about the same when unemployment returns to its prerecession level as it was before the recession began. If that is the case, the size of the labor force as a share of the adult population should yield a better picture of how far the nation is from full employment at any given point in a downturn than the official unemployment rate does. In 2007 civilian employment averaged 146.0 million and unemployment averaged 7.1 million, so the total civilian labor force averaged 153.1 million people, or 66.0 percent of all U.S. residents over the age of 16. In November 2010, just before this comment was written, seasonally adjusted employment was 138.9 million, unemployment was 15.1 million, and the civilian labor force was 64.5 percent of the population over 16. If 66.0 percent of those over the age of 16 still wanted jobs of the kind that were available in 2007, and only 138.9 million people had jobs, roughly 18.7 million people who would have taken a job in 2007 were unemployed in November 2010. If we define the "unemployed" in this way, the "true" unemployment rate in November 2010 was 11.8 percent. Making the same calculation for October 2009, when the official unemployment rate peaked, the "true" unemployment rate was then 11.5 percent. At some point job growth will presumably begin to exceed growth in the number of would-be workers, but no one knows when that will be.

Bitler and Hoynes focus primarily on how rising unemployment affected low-income families with children. The official child poverty rate rose 2.7 percentage points between 2007 and 2009 (see their table 1 and U.S. Bureau of the Census 2010, table B-2). However, the official poverty rate suffers from several problems that make it an unreliable guide to trends in material hardship (Jencks, Mayer, and Swingle 2004). One well-known problem is that poverty rates are calculated using family rather than household income, and the Census Bureau defines a family as including only household members related by blood, marriage, or adoption. Thus, if an unmarried mother has a live-in boyfriend, the Census Bureau does not count his income when it determines whether the mother and her children are poor. This rule makes mothers cohabiting with working boyfriends look poorer than they are. In bad times, however, this rule hides the increase in child poverty that occurs when live-in boyfriends lose their jobs.

Another well-known problem is that the official poverty rate ignores both taxes (notably the earned income tax credit, or EITC) and noncash government benefits such as Medicaid, food stamps, and housing subsidies, all of which play a critical role in the well-being of low-income families. This approach to measuring income inflates the child poverty rate even more than ignoring live-in boyfriends, but it biases the estimated impact of unemployment on poverty only when taxes or noncash benefits change at the same time as unemployment. Bitler and Hoynes show that spending on per capita on Temporary Assistance for Needy Families (TANF) did not substantially increase between 2007 and 2009 but that spending per capita on food stamps rose by two-thirds (see their table 1). Ignoring this increase presumably tends to offset the bias created by ignoring any decline in income from live-in boyfriends who become unemployed. Because of these and other problems, Bitler and Hoynes calculate an adjusted poverty rate, but it is available only through 2008. They also try to check their conclusions against more direct measures of material hardship. I focus here on hardship in three domains: food, housing, and health care.

FOOD. Every December the Census Bureau's Current Population Survey includes a "food security" supplement designed by the U.S. Department of Agriculture. This supplement asks families about their food expenditure, their use of rood pantries, and their ability to buy as much food as they think they need. The median family with children reported weekly spending per person of $33 in both 2007 and 2009 (Nord, Andrews, and Carlson 2008, p. 24; Nord and others 2010, p. 25). (1) Since food prices rose about 3 percent over those 2 years, $33 bought about 3 percent less (or at least less desirable) food in 2009 than in 2007. Median expenditure per person was only about $2 per week lower among families headed by a single mother and only $1 per week lower among families with incomes below the poverty line, presumably because the reported median is quite close to an eligible family's food stamp budget.

Median spending does not tell us how many families with children had trouble getting enough to eat. In rich countries like the United States, few families experience protracted periods of hunger or malnutrition, but many families experience occasional crises when they cannot afford to buy enough food, and some experience such crises fairly often. According to the food security survey, 7.8 percent of children lived in families that reported having turned to food pantries for help at some point during 2009, compared with only 5.3 percent during 2007. The fraction of all families reporting that there had been times when the food they bought "didn't last" and they "didn't have money to get more" rose from 12 percent to 16 percent between 2007 and 2009. Over the same period, the fraction of families reporting that an adult in the family was hungry and "didn't eat because there wasn't enough money for food" rose from 3.3 percent to 4.6 percent, and the fraction reporting that they had not eaten for a whole day rose from 1.3 percent to 1.7 percent (Nord and others 2010, p. 45).

HEALTH. People's health can suffer for many reasons during an economic downturn. In the United States many people lose their health insurance soon after they lose their job. Some even lose their health insurance without losing their job, because their employer stops offering coverage. The fraction of Americans with employment-based insurance fell from 59.3 percent in 2007 to 55.8 percent in 2009 (U.S. Census Bureau 2010, table C-3). Public programs picked up some of those who lost their private coverage, but the fraction without any heath insurance rose from 15.3 percent to 16.7 percent. Among children, however, Medicaid expansion cut the proportion who were uninsured from 11.0 percent in 2007 to 10.0 percent in 2009.

A large body of research has shown that even in countries with universal health insurance, workers' health tends to deteriorate if they lose their job. This is also true in the United States. However, Christopher Ruhm (2003) has shown that when one looks at the entire population rather than just the unemployed, mortality rates actually fall faster when the economy is contracting than when it is growing. This is true not only in the United States but in other high-income countries as well (Gerdtham and Ruhm 2005). At least in the United States, the pattern seems to be linked to the fact that heavy drinking, smoking, auto accidents, air pollution, and overtime work also decline during downturns (Ruhm 2005).

It is too soon to be sure whether this benign effect of economic austerity recurred between 2007 and 2009. Thus far the evidence is mixed. On the one hand, provisional data from the National Center for Health Statistics (NCHS, various years) indicate that infant mortality declined only modestly, from 6.7 to 6.6 deaths per 1,000 live births, between 2003 and 2007, a time when unemployment was falling, but that it declined three times as fast, from 6.6 to 6.3 per 1,000, between 2007 and 2009. That is consistent with Ruhm's earlier findings. Age-adjusted estimates for the rest of the population are not yet available. (2)

HOUSING. When unemployment rises, some families cannot pay their mortgage or their rent and instead double up with relatives or friends. One would expect doubling up to have been especially common in 2007-09, since the collapse of the housing bubble led to more foreclosures and evictions during these years than at any time since the 1930s. The U.S. Census Bureau (2010) reported an 11.6-percentage-point rise between March 2008 and March 2010 in the number of households that included more than one family. Apparently, however, very few of these families included children, since Bitler and Hoynes report in their table 1 that the fraction of children living in a household that included more than one family rose only 0.2 percentage points. It is hard to know what this measure means, since they report a smaller annual increase between 2007 and 2009 than between 2003 and 2007, when unemployment was falling. Average household size, which rose 1.1 percent between March 2007 and March 2010 (from 2.558 persons to 2.585 persons) may be a better measure of doubling up. (3) Indeed, the increase in household size may underestimate the amount of doubling up, because the number of births was 4.1 percent lower in 2009 than in 2007. In due course, moreover, many families tire of sharing their home with another family, especially if it includes children. Not surprisingly, the U.S. Department of Housing and Urban Development (2010) estimates that the number of families with children in shelters for the homeless also rose, from 131,000 in January 2007 to 170,000 in 2009.

Taking all this evidence together, it seems clear that both the fraction of families that sometimes had trouble getting enough to eat and the fraction with serious housing problems rose between 2007 and 2009, which is consistent with what one would expect based on both the rise in unemployment and the rise in the official poverty rate. Mortality rates appear to have fallen appreciably for infants, but there is no reliable evidence yet for adults.

WOULD THINGS HAVE BEEN BETTER UNDER THE OLD WELFARE SYSTEM? Bitler and Hoynes's main goal is to figure out whether families with children would have fared better during the current downturn if the pre-1996 welfare system had still been in place. They use standard econometric methods to address this question, comparing trends within states before and after each state implemented welfare reform. Their results suggest that the effect of unemployment on child poverty was somewhat greater after welfare reform, but their estimates have large standard errors, and in five out of six cases the confidence interval includes zero (see their table 6). Nonetheless, since the primary goal of welfare reform was to make single mothers more dependent on earnings and less dependent on "handouts," and since the clearest consequence of the new law was to reduce the number of families getting a monthly welfare check, from 4.5 million in fiscal 1996 to 2.1 million in fiscal 2002, Bitler and Hoynes's expectation that child poverty should have become more sensitive to labor market conditions seems plausible, and nothing in their findings suggests that it is wrong. That said, three comments are in order.

First, from a policy perspective it is not clear why we should even be investigating the impact of welfare reform. Even if Bitler and Hoynes and other researchers were finding that welfare reform had terrible consequences for millions of children, the chances that legislators would respond by bringing back anything like the old AFDC (Aid to Families with Dependent Children) regime are close to zero. Legislators might try to help single mothers in other ways, such as by providing jobs and child care for all single mothers or guaranteeing all low-income single mothers a housing subsidy, but bringing back AFDC would be a nonstarter.

Second, it is not clear what "welfare reform" really includes in Bitler and Hoynes's analysis. They treat the states that introduced more stringent requirements than those traditionally allowed by AFDC as having begun welfare reform when their federal waiver was approved. However, the new federal rules established in 1996 under the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA), which replaced AFDC with TANF, were far more stringent than the rules introduced by states under pre-1996 waivers. Welfare waivers were also contemporaneous with increases in the EITC between 1993 and 1996 that made work a more attractive alternative to welfare.

Furthermore, states did not implement the new TANF rules immediately. States made it progressively harder for new applicants to get on the rolls, and they enforced their time limits more assiduously over time. These efforts to keep cutting the rolls year after year were motivated partly by state legislators' desire to show their commitment to "work, not welfare," and partly by the threat of federal sanctions if states did not reduce the rolls more every year. As a result, the number of families getting TANF benefits fell by about half a million a year between fiscal 1996 and fiscal 2000 (from 4.5 million to 2.3 million). Some of this steady decline was surely due to the tightening labor market, but unemployment fell only from 5.4 percent to 4.0 percent between 1996 and 2000, and the labor force participation rate rose only from 66.8 percent to 67.1 percent. The welfare rolls fell by another 200,000 between 2000 and 2002, even though unemployment was higher in 2002 than it had been in 1996 (5.8 percent versus 5.4 percent).

This history suggests that the effects of the EITC and PRWORA unfolded gradually rather than instantaneously. When welfare reform is gradual and the lags are uncertain, disentangling the effects of reform from the effects of the EITC and unemployment is extremely difficult, and it is no surprise that most of Bitler and Hoynes's coefficients have large standard errors. My table 1 provides a simple illustration of the underlying problem by showing how child poverty changed between 1996 and 2009 as the unemployment rate rose and fell. To minimize the problem of lags, I focus on peak-to-trough and trough-to-peak changes in unemployment.

From 1996 to 2000 unemployment fell only 1.4 percentage points while child poverty fell 4.3 percentage points, suggesting a very strong post-reform effect of full employment on child poverty. But after 2000 the relationship between unemployment and child poverty weakened. Unemployment rose 2.0 percentage points between 2000 and 2003, but child poverty only rose 1.4 percentage points. Between 2003 and 2007 unemployment fell as much as it had between 1996 and 2000 (1.4 percentage points), but child poverty rose from 17.6 percent to 18.0 percent. By 2007, therefore, the link between child poverty and the labor market was looking quite tenuous. However, the recent recession has provided a fourth test of the link, and it points to a more cautious conclusion. The official unemployment rate rose from 4.6 percent in 2007 to 9.3 percent in 2009, and each l-percentage-point rise in unemployment was associated with an increase in child poverty of 0.57 percentage point, which is fairly similar to the association during the rise in unemployment between 2000 and 2003.

The fact that the relationship between unemployment and child poverty varies so much could have numerous causes. First, the big drop in child poverty between 1996 and 2000 reflected the fact that PRWORA and the EITC induced more single mothers to look for work, and tight labor markets helped them find it. Second, wages near the bottom of the distribution rose. At the 20th percentile of the combined distribution for men and women, for example, real wages rose 11 percent between 1996 and 2000, which was the only period of sustained increase between 1973 and 2007 (Economic Policy Institute 2009, table 3.5). These factors could also explain why child poverty was lower during 2001-03, a period of relatively high unemployment, than it had been in the early 1990s. The fact that child poverty hardly dropped at all after 2003, when unemployment began to fall, is harder to explain.

Bitler and Hoynes try to deal with these problems by looking at trends across the 50 states rather than within the United States as a whole. Their estimates therefore rely on the average relationship between trends in unemployment and child poverty within states. Nonetheless, their estimates have large standard errors and are seldom statistically significant. My tentative conclusion is thus that we are still some distance from identifying all the factors that affect either official child poverty rates or the authors' adjusted rates. The same conclusion probably holds for the direct measures of children's well-being that both they and I discuss.

REFERENCES FOR THE JENCKS COMMENT

Economic Policy Institute. 2009. The Slate of Working America 2008/2009. Washington. Data available at www.epi.org/resources/datazone_dznational/.

Gerdtham, Ulf-G., and Christopher J. Ruhm. 2006. "Deaths Rise in Good Economic Times: Evidence from the OECD." Economics and Human Biology 4, no. 3: 298-316.

Jencks, Christopher, Susan E. Mayer, and Joseph Swingle. 2004. "Can We Fix the Federal Poverty Measure so It Provides Reliable Information about Changes in Children's Living Conditions?" Harvard University, University of Chicago, and Wellesley College.

National Center for Heath Statistics. Various years. "Births, Marriages, Divorces, and Deaths: Provisional Data." National Vital Statistics Reports. Washington.

Nord, Mark. Margaret Andrews, and Steven Carlson. 2008. "Household Food Security in the United States, 2007." Report no. 65. U.S. Department of Agriculture, Economic Research Service.

Nord, Mark, Alisha Coleman-Jensen, Margaret Andrews, and Steven Carlson. 2010. "Household Food Security in the United States, 2009." Report no. 108. U.S. Department of Agriculture, Economic Research Service.

Ruhm, Christopher J. 2003. "Good Times Make You Sick." Journal of Health Economics 22, no. 4: 637-58.

--. 2005. "Healthy Living in Hard Times." Journal of Health Economics 24, no. 2: 341-63.

U.S. Census Bureau. 2010. "Income, Poverty, and Health Insurance Coverage in the United States: 2009." Current Population Reports, series P60-238. Washington.

--. 2010. "Webinar on 2009 Income, Poverty and Health Insurance Estimates from The Current Population Survey." (Washington, D.C. September 16).

U.S. Department of Housing and Urban Development. 2010. "The 2009 Annual Homeless Assessment Report to Congress." Office of Community Planning and Development. Washington.

(1.) This finding should be treated cautiously. Measured in current dollars, the median for all families with children was $33.33 per person in both years. This presumably reflects the fact that the median family had three members and reported spending $100 a week in both years. But because many families round their estimates of grocery spending to easily remembered numbers, far more families report spending $100 a week than, say, $97 or $103. As a result, the median may remain the same for a long time even if the full distribution is shifting to the left or right.

(2.) Provisional data on mortality from all causes that are not adjusted for the aging of the population indicate that the mortality rate fell more slowly between 2007 and 2009 than between 2003 and 2007. However, age-adjusted mortality is falling faster than unadjusted mortality, so conclusions based on the provisional data are very risky.

(3.) Household size is estimated using the ratio of persons to households in U.S. Census Bureau (2010), tables B-1 and A-1. The estimates shown there are for March 2009, when the survey was conducted.

Table 1. Changes in Unemployment and in Child Poverty during Upturns
and Downturns, 1996-2009

                           1996      2000      2003      2007      2009

Unemployment (percent)      5.4       4.0       6.0       4.6       9.3
Child poverty (percent)    20.5      16.2      17.6      18.0      20.7

                             1996-2000   2000-03   2003-07    2007-09

Change in unemployment         -1.4       +2.0      -1.4      +4.7
Change in child poverty        -4.3       +1.4      +0.4      +2.7
  As ratio to change in
  unemployment                  3.07       0.70     -0.29      0.57

Sources: Economic Report of the President 2010, table B-35; U.S.
Bureau of the Census (2010), p. 56.

COMMENT BY BRUCE D. MEYER

This paper by Marianne Bitler and Hilary Hoynes examines the important question of how the social safety net has changed over time and how these changes have affected the well-being of families. Many indicators suggest that the safety net has changed substantially. Whether in terms of program caseloads or in terms of expenditure, over the past 15 years or so, Aid to Families with Dependent Children (AFDC) and its successor Temporary Assistance for Needy Families (TANF) have become much less important, while the earned income tax credit (EITC) and the food stamp program (today known as the Supplemental Nutrition Assistance Program, or SNAP) have steadily expanded. More recently, enrollment in and spending on unemployment insurance (UI) skyrocketed in the Great Recession.

The paper begins with nice descriptions of the main programs that provide for the disadvantaged, focusing on AFDC/TANF, food stamps, and UI. The program rules are carefully summarized, and recent changes to these rules are described in detail. The focus on these programs partly flows from the authors' decision to examine the nonelderly exclusively. The study also focuses on nonmedical assistance. If one is concerned about where the current safety net might be failing to serve the disadvantaged, cash or near-cash assistance to the nonelderly is likely to be the right place to look. Robert Moffitt and John Karl Scholz (2010) have noted that recent

increases in income support have been focused on very poor elderly, disabled, and childless families through the Social Security (both its old-age and its disability components), Supplemental Security Income (SSI), and health programs. In contrast, very poor families with children have seen a decline in expenditure due to lower receipt rates of AFDC/TANF and food stamps, although recently SNAP caseloads have risen considerably.

The paper also focuses on how the safety net for the nonelderly has responded to the recession, rather than on how those disadvantaged by persistently poor skills, disability, or old age have fared in recent years. The paper's analysis thus concentrates on those likely to be hurt given the differing trends in government spending by demographic group, and given that the economy is in the midst of its most severe downturn since the Great Depression. The authors' conclusions about the functioning of the safety net will not be applicable to the elderly or to those among the nonelderly who are suffering more long-term disadvantage.

It is also worth stepping back and thinking about the ways a recession can hurt the disadvantaged. The most obvious way is through the loss of employment and a decline in earnings among the employed. Thus, the recession is likely to have its largest effects on those who depend on employment, namely, the able-bodied nonelderly. Another way to characterize the trends in income support in recent years is as a shift in support from the nonworking poor to the working poor (Moffitt 2003, 2007). Given this shift, one might be especially worried if the recession leads to a loss of benefits for the working poor, such as from the EITC, as employment falls. Other effects of the recession on the disadvantaged might include a reduced likelihood of marriage and higher rates of marital dissolution (although Hellerstein and Morrill 2010 provide evidence that divorce is procyclical), both of which might impoverish single adults and their families. Finally, one might see a decline in private transfers and other support for the poor.

A basic question that the paper could address more directly is how one should go about assessing the state of the safety net. Presumably, economists and policymakers would like to know how the safety net cushions any income shocks and prevents them from leading to a fall in family well-being. To examine this question, we first need to assess the extent of the shocks to income. We also need to decide how to measure family well-being. We could measure well-being using income, which has a long tradition. But income often only translates roughly into well-being, because families save and borrow. Furthermore, most families, even most poor families, have substantial nonfinancial assets: homes, cars, and other durables. Depending on their stock of these assets, a change in income will have different effects on their well-being. Finally, income is often misreported in household surveys, especially among the most disadvantaged households. Only half of food stamp and welfare dollars are reported in the main survey used by the authors, the Current Population Survey (Meyer, Mok, and Sullivan 2009, Meyer and Goerge 2010). The reporting of private transfers is likely worse. Consumption data are a good alternative to income data, given that recent research shows that consumption is better measured than income at the bottom and that low consumption is more closely associated with deprivation than is low income (Meyer and Sullivan 2003, forthcoming-b). Other dimensions to well-being might also be of concern. If families have less nonmarket time (including leisure), or if access to medical care has changed, for example, then well-being is affected.

Factors other than the safety net might also have changed in the Great Recession in ways that affect family well-being. The years leading up to the recession as well as the recession years themselves were a period of atypically slow employment growth. In addition, tighter credit and the sharp decline in housing prices imply that many households can no longer borrow or access housing equity in bad times, which suggests that the recession may have done more damage than its depth alone would indicate. Thus, it seems likely that the effect of changes in the safety net may be difficult to separate from that of other changes in economic conditions.

The paper reports three main sets of empirical results. The first summarizes aggregate changes in a number of measures of economic conditions, benefit receipt, and well-being both in the recent recession and in earlier contractions and expansions. Among the most important findings from this analysis are that even though unemployment rose more in the recent recession than in the 1979-82 recession, official poverty rose less, and total consumption and food consumption in the bottom income quintile actually went up. Also, food stamp receipt rose much more in this recession than in past ones. These initial results do not indicate a newly permeable safety net.

The second set of results describes the responsiveness of state program caseloads and individual reported receipt of benefits to state unemployment rates. The paper argues that food stamp caseloads and receipt have become more sensitive to unemployment, but that the sensitivity of AFDC/TANF to unemployment has not risen or may have fallen over time. However, the evidence seems to be mixed. The authors' variable interacting the unemployment rate with a dummy for the postreform period has a positive coefficient in both the AFDC/TANF and the food stamp regressions, suggesting increased responsiveness of these programs, but it is statistically insignificant in both cases. The authors also interact classifications of the different state welfare reforms with unemployment. Such a classification is not an easy thing to do or one that can be done with confidence, given the multidimensional and qualitative changes in state welfare laws. In any case, only one of five coefficients in the AFDC/TANF caseload regressions is significantly different from zero at the 5 percent level or better, and the two that are significant in the food stamp caseload regressions are of conflicting sign. Thus, the evidence of decreased responsiveness is weak.

In the analysis using survey data on benefit receipt by program, the results are similarly inconclusive. The responsiveness of AFDC/TANF receipt to changes in unemployment more than doubles after reform, whereas that for food stamps does not quite double but is more precisely measured and significantly different from zero. These survey results should be interpreted with caution, however, given that the survey misses half of TANF and food stamp receipt.

Another interesting feature of the paper is its use of both administrative aggregate data and survey data. The authors suggest that similarities in the results in the two data sources may mean that the deficiencies of the survey data are not important. However, the differences in specifications, the large standard errors, and the lack of comparison of the magnitudes of the coefficients make this exercise unconvincing. One can easily compare in the survey and administrative data, however, the magnitude of the interaction coefficient on unemployment after reform relative to the main effect (the unemployment rate alone) in tables 4 and 7. The administrative data indicate that AFDC/TANF caseloads are about 20 percent more sensitive after reform, whereas the survey data indicate an increased responsiveness of 125 percent. The discrepancy for food stamps is also very large. This is not evidence that allows one to conclude that survey errors are unimportant.

In any case, it is not clear that one should conclude a great deal from such regressions about the likely changes in caseloads or benefit receipt in future recessions. Each recession is a little different. The responsiveness of poverty to unemployment has varied sharply across decades, as many authors have found (for example, Blank and Card 1993, Blank 2000, Haveman and Schwabish 2004, and Meyer and Sullivan forthcoming-a). In addition, changes in state welfare programs over time have been very large and are hard to summarize, and these might be confounding the relationship of caseloads and expenditure with unemployment.

AFDC/TANF receipt may be less sensitive now to unemployment than it has been historically, but the evidence is not there yet to show it. It would not be surprising if AFDC/TANF were not particularly sensitive to unemployment, because it is a program that serves a population with low historical employment rates. Past research has found that this sensitivity is indeed low and has changed over time (Blank 2001). If this sensitivity is lower in recent decades, it might reflect the fact that federal funding does not vary with unemployment under the block grant system introduced as part of welfare reform. Alternatively, it might be due to the program being more targeted at those who cannot work and thus are less sensitive to labor market conditions.

The paper's third set of results examines the effects of welfare reform on various well-being measures, principally poverty rates. The authors also look at living arrangements and "disconnectedness" (the condition of being effectively cut off from both work and welfare). For all outcomes, the authors examine the coefficient on the interaction of unemployment with welfare reform, essentially asking whether well-being declines more with higher unemployment after welfare reform than before. Before examining this interaction, or second-order effect, it is worth knowing a bit more about what happened overall after welfare reform. One might suspect that changes in caseloads provide limited information on well-being, given that AFDC/ TANF caseloads fell from 5 million assistance units to under 2 million, yet the evidence is mixed on how families fared after welfare reform. James X. Sullivan and I looked extensively at this issue (Meyer and Sullivan 2004, 2008) and found that, overall, families' material well-being is apparently higher after welfare reform, but it is a complicated and mixed picture. Consumption by single mothers rose in all income deciles, and their income rose in all but the first. We argue that the decline in reported income for the bottom decile is likely due to misreporting. Housing characteristics (number of rooms, presence of air conditioning and appliances, and so forth) improved after welfare reform for those who were likely to be on welfare, but health insurance coverage fell for some groups of single mothers. Time spent in nonmarket activity (leisure time and time spent on housework) dropped substantially for single mothers, but this loss of time does not appear to have decreased their time with children (also see Gelber and Mitchell 2009); rather, it has come out of time spent cleaning and shopping and the like.

With the above as background, let me turn to the current results. The paper regresses several poverty measures, family structure, and a dummy variable for neither work nor welfare receipt on the unemployment rate after welfare reform as well as the unemployment rate for the entire period. These results are probably the most important findings of the paper. For only one of the outcomes is the key interaction coefficient significantly different from zero. That outcome is the share of people with income below 150 percent of the official poverty line. For the other cutoffs (100 percent and 50 percent of the poverty line), the coefficients are insignificant. Given that the official income definition used to determine the official poverty measure misses many of the most important parts of the safety net (food stamps, the EITC, the child tax credit, housing assistance), it is not an especially useful tool for evaluating the safety net. When the authors examine poverty measures that use alternative income definitions that account for taxes, food stamps, and other benefits, the changes are insignificant, as they are for other well-being outcomes. Even the alternative poverty numbers are questionable given that, as noted above, the survey that the authors rely on misses half of food stamps and TANF. I would urge the authors to look at changes in means and low percentiles of consumption in the Consumer Expenditure Survey.

The situation of families with children may be worse in high-unemployment areas than it was in the past under similarly high unemployment, but the data to determine if this is so are not yet available. Chairman Mao, when asked whether the French Revolution was a success, reportedly said that it was too early to tell. This sentiment applies even more strongly to the topic of this paper. In evaluating these analyses, we should be aware that it may be too early to determine how the safety net is affecting families in the Great Recession and its aftermath. The unemployment rate was 5.8 percent, equal to the median value over the full sample, in 2008, the next-to-last year of data examined in the principal analyses in the paper. Unemployment rose sharply in 2009, but one year of data with high unemployment is not a lot on which to base conclusions. There is substantial variation across states, but still it is too early to conclude how the new safety net will perform in recessions.

REFERENCES FOR THE MEYER COMMENT

Blank, Rebecca M. 2000. "Fighting Poverty: Lessons from Recent U.S. History." Journal of Economic Perspectives 14, no. 2: 3-19.

--. 2001. "What Causes Public Assistance Caseloads to Grow?" Journal of Human Resources 36, no. 1(Winter): 85-118.

--. 2009. "Economic Change and the Structure of Opportunity for Less-Skilled Workers." In Changing Poverty, Changing Policies, edited by Maria Cancian and Sheldon Danziger. New York: Russell Sage Foundation.

Blank, Rebecca M., and Alan S. Blinder. 1986. "Macroeconomics, Income Distribution, and Poverty." In Fighting Poverty: What Works and What Does Not, edited by Sheldon H. Danziger and Daniel H. Weinberg. Harvard University Press.

Blank, Rebecca M., and David Card. 1993. "Poverty, Income Distribution, and Growth: Are They Still Connected?" BPEA, no. 2: 285-339.

Gelber, Alexander M., and Joshua W. Mitchell. 2009. "Taxes and Time Allocation: Evidence from Single Women." Working Paper no. 15583. Cambridge, Mass.: National Bureau of Economic Research.

Haveman, Robert, and Jonathan Schwabish. 2000. "Has Macroeconomic Performance Regained Its Antipoverty Bite?" Contemporary Economic Policy 18, no. 4: 415-27.

Hellerstein, Judith K., and Melinda Morrill. 2010. "Booms, Busts, and Divorce." Working paper. University of Maryland and North Carolina State University.

Meyer, Bruce D. 2003. "Measuring the Well-Being of the Poor Using Income and Consumption." Journal of Human Resources 38S: 1180-1220.

--. 2004. "The Effects of Welfare and Tax Reform: The Material Well-Being of Single Mothers in the 1980s and 1990s." Journal of Public Economics 88, no. 7-8 (July): 1387-1420.

Meyer, Bruce D., and Robert M. Goerge. 2010. "The Analysis of Food Stamp Program Participation with Matched Administrative and Survey Data." Working paper. University of Chicago.

Meyer, Bruce D., and James X. Sullivan. 2008. "Changes in the Consumption, Income, and Well-Being of Single Mother Headed Families." American Economic Review 98. no. 5 (December): 2221-41.

--. Forthcoming-a. "Consumption and Income Poverty over the Business Cycle." Research in Labor Economics.

--. Forthcoming-b. "Further Results on Measuring the Well-Being of the Poor Using Income and Consumption." Canadian Journal of Economics.

Meyer, Bruce D., Wallace K. C. Mok, and James X. Sullivan. 2009. "The Under-Reporting of Transfers in Household Surveys: Its Nature and Consequences." Working Paper no. 15181. Cambridge, Mass.: National Bureau of Economic Research.

Moffitt, Robert A. 2003. "Introduction." In Means-Tested Transfer Programs in the United States, edited by Robert A. Moffitt. University of Chicago Press.

--. 2007. "Four Decades of Antipoverty Policy: Past Developments and Future Directions." Focus 25, no. 1 (Spring-Summer): 39-44.

Moffitt, Robert A., and John Karl Scholz. 2010. "Trends in the Level and Distribution of Income Support." Working Paper no. 15488. Cambridge, Mass.: National Bureau of Economic Research.

GENERAL DISCUSSION

Donald Kohn wondered about possible interactions between welfare and unemployment insurance. Among the many advantages of having low-income individuals in the labor force rather than out of it is greater access to the UI system. Increased use of UI should damp the cyclicality of welfare by delaying any cyclical effects. This is particularly likely to occur with low-skilled people who have trouble reentering the labor force as extended benefits expire. One result is that any cyclical effects would tend to be seen at or after the end of a recession.

Steven Davis was persuaded by the recent work of Bruce Meyer and many others arguing that the official poverty measures are too flawed to be useful as objects of research. A good alternative is to look at post-tax, post-transfer measures of income among the lower percentiles of the consumption distribution. He further wondered why many experts in this field had been wrong ex ante about the impact of welfare reform. Understanding this error would inform the theories and models used in evaluating the impact of changes in this and other policy programs. Christopher Jencks thought one reason the predictions had been so wrong was that AFDC payments made up a much smaller fraction of what people were living on before welfare reform than most researchers had assumed. Bruce Meyer added that the employment rate of single mothers, whose ability to work and be hired had been in question, rose more quickly than expected.

Helen Ladd asked whether it was correct that most of the increase in employment was in short-term or temporary jobs that did not lead to longer-term employment. Meyer noted that among high school dropout single mothers, employment went up by roughly 60 percent after reform. The increases for that group have persisted, but it remains a good question whether they have received wage increases over time that are typical for people with their skill level.

David Romer thought the critical question was whether the social safety net had been shredded to the point where a sizeable recession would cause an enormous amount of suffering. The tone of the paper and of the discussion implied that it had not, but quite a few of the individual indicators discussed in the paper suggested that the answer was not entirely clear. The authors find that poverty is now more cyclical, as is the number of disconnected women. And they find that both food insecurity and the postponing or forgoing of medical care rose substantially more in the most recent recession than previously.

Justin Wolfers noted that issues related to welfare, like the extension of unemployment insurance, are very much on the current policy agenda, making the discussion of direct contemporary policy relevance. He also perceived a puzzle in the paper's results. Since the beginning of the recent recession, the poverty rate was up by 1.8 percentage points, whereas the early-1980s recession had raised the poverty rate by 3.3 points. If welfare reform was what was different between the two periods, why wasn't the rise in the poverty rate even greater in the current downturn? In addition, almost everything that has been done to the social safety net over the past 20 years is not measured by the poverty rate. These two issues together suggest that the real puzzle of this recession is why the aggregate poverty rate has not risen much at all. It may be that UI is the answer and not welfare reform, which appears to have raised the cyclicality of poverty.

James Hines suggested thinking also about the cyclicality of the earned income tax credit, a policy that was motivated by many of the same ideas that had inspired welfare reform. It would be interesting to know whether the generosity of the EITC increases during recessions, effectively acting as a counterbalance to welfare reform. He conjectured that it may not increase, since virtually all of the EITC's benefits are conditioned on working, whereas unemployment rises in a recession. On the other hand, to the extent a recession causes some previously fully employed workers to become underemployed or to have to accept a lower wage, some of them might become newly eligible for the EITC.

Henry Aaron saw the discussion as highlighting that the most understudied subject in income distribution research is disability insurance. Over the period in question, the number of people on disability insurance tripled, and total expenditure on that program was probably larger than for any of the other programs under discussion. Disability insurance is not an income-tested program and thus goes at least in part to people who would not have been poor without the benefits. But a complete accounting of the effects of the recession on low-income Americans nonetheless calls for a discussion of what has happened with respect to disability insurance enrollments and expenditure.

Melissa Kearney thought that welfare reform, by essentially making it harder to enroll in and stay on a key form of government assistance, was important to the debates surrounding other assistance programs: about extending unemployment insurance, about making disability insurance harder to qualify for, and even about allowing stimulus payments to go to states' provision of these programs. She was interested in the role of the states, and in particular how much larger the welfare caseload increase would have been if states were not actively discouraging caseloads. She cited a paper by Jeffrey Kubik showing that in times of fiscal stress, states push more people from AFDC onto SSI, which suggests that states might be acting differently in the post-welfare reform era in terms of discouraging applications. Kearney proposed thinking about applications to all of these programs collectively as a better measure of the need for assistance. Many people are applying for these programs but not getting them, and long-term programs like disability insurance and SSI are more relevant to fiscal consequences.

Kristin Forbes wondered if it was accurate to interpret the paper's results as saying that welfare reform had significantly reduced the costs of a major U.S. entitlement program over time, while producing not only no large negative effects during normal times, but also no large general negative effects even during recessions. If this is true, are there lessons for reforming other major entitlement programs? In particular, a look back at what people were saying during the welfare reform debate of the 1990s might enlighten some of the current discussions about entitlement reforms.

Gary Burtless underscored that both the employment and the earnings of the population affected by welfare reform were much more resilient than most forecasters had expected: real wages at the bottom end of the earnings distribution improved after reform, for the first time in probably 20 years. He also found it striking that, unlike a lot of reforms, this one had been preceded by almost a decade of systematic randomized trials across the country, in which many of the elements of the reform were tested in local populations. None of these randomized trials had uncovered employment gains of the size witnessed after reform passed at the national level. It was and remains a mystery how much of that increase was due to possible social interaction effects (that is, individuals within a group influencing each other's behavior, for example by informing one another of new program rules and how best to respond to them), and to what extent the limitations of doing randomized trials for this kind of policy caused the effect of nationwide reform to be underestimated. It is hard to observe social interaction effects in a small-scale randomized trial, because only a small percentage of the affected population is enrolled in any one tested program.

Burtless also argued that welfare reform should have made overall unemployment rates slightly more cyclical, because a population that formerly had been largely insulated from the labor market, by being outside of it, was forced to enter the workforce. In a recession, a lot of disadvantaged single women are on the margin of being employed or unemployed rather than being solidly outside the workforce. However, this effect is likely small, as this population does not make up a large proportion of the working-age population.

Melissa Kearney picked up on Burtless' point about the possible social network effects of the 1996 reform. There have been some isolated policy studies but nothing in the models for cultural change. These sorts of cultural network effects are very well captured, however, in the agent-based models that are part of the Brookings Social Genome Project.

Ricardo Reis noted that recessions are times when discretionary fiscal spending is taking place, trying to channel more money toward a whole series of programs, including those that assist the poor. Much of the fiscal response to the recent crisis has taken the form of increasing transfers in almost every transfer program. Reis was curious to know more about how welfare money had been spent over the last 2 years and to what channels it was directed, because this might shed light on whether the outcomes are what might have been expected 15 or 20 years ago.

Robert Hall was interested in the relationship between unemployment and the TANF caseload, which has been shown to rise substantially in proportional terms but not nearly as much as unemployment during recessions. To take unemployment as the benchmark would suggest that each TANF unit depended largely on one person's earnings with the typical amount of unemployment. In reality, the matching of workers to TANF units is more complicated, and any given TANF unit may have zero, one, two, or more earners. Further, a model that makes the TANF caseload rise in proportion to unemployment neglects the high earnings replacement rate of UI for the population potentially eligible for TANF, and it neglects the relationship between unemployment in that population and the overall unemployment rate. Throughout the recession and its aftermath, real post-transfer income per capita has continued to rise. Households have responded to the recession by spending substantially less of their income and increasing their saving. The social loss associated with the recession is huge, but the loss at the household level is not as large because an effective system is in place to replace the income lost during a recession. This point is consistent with the finding by Parker and Vissing-Jorgensen in their paper for this conference, that everybody except the very rich is fairly well insulated from extreme income fluctuations.

Brian Jacob stressed the importance of individual state responses and perhaps also of the part of the federal response that takes place through other mechanisms besides transfers. It may be that the total costs of assistance have not really been reduced dramatically if these other things are included. Also, it might be that some states are being generous in other ways that minimize any negative effects of welfare reform.

Christopher Jencks observed, following on Jacob's point, that the federal government spends more on the EITC than was ever spent on AFDC, and so it would not be accurate to say that welfare reform has saved the government money. Rather, money was shifted away from cash welfare in order to make it pay to go to work. In some sense welfare reform can be called a success only if one ignores the effects on people's well-being and considers only the goal of getting people to work. Jencks also pointed out that the reason the EITC is the most effective program in raising people above the poverty line is not so much the generosity of the benefit but because it tends to help those already close to the poverty line.

Jencks noted that applying for benefits under TANF can be difficult. In many states, applicants are required to inquire about work from a list of firms before applying. Some who were probably eligible, in terms of . genuine economic need, never come back. State welfare offices discourage people from applying, particularly when they do not want caseloads to rise. In the 1980s New York went so far as to close half its welfare offices. Simply counting applications can thus make it look like the need for welfare has collapsed even if actual eligibility has risen.

Bruce Meyer argued that it makes more sense to evaluate a program in terms of the reduction in the poverty gap it achieves. The effect of food stamps, for example, on the poverty gap is much more important than that of the EITC. Meyer suggested that in focusing on the interaction of welfare reform and unemployment, the paper was looking at a second-order effect. The main effect, namely, on consumption by single mothers, was an increase at almost all points of the distribution. For other outcomes like health insurance coverage, many single mothers toward the bottom have lost ground. They are also working more, which may have been the goal of the reform, but getting these single mothers into the workforce was itself costly.

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