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The Impact of Welfare Reform on Marriage and Divorce
Marianne P. Bitler, Jonah B. Gelbach, Hilary W. Hoynes, and
Madeline Zavodny
Working Paper 2002-9
June 2002

Working Paper Series

Federal Reserve Bank of Atlanta
Working Paper 2002-9
June 2002

The Impact of Welfare Reform on Marriage and Divorce
Marianne P. Bitler, NICHD Post-Doctoral Fellow, RAND
Jonah B. Gelbach, University of Maryland (on leave) / RWJ Scholar,
University of California, Berkeley
Hilary W. Hoynes, University of California, Davis and NBER
Madeline Zavodny, Federal Reserve Bank of Atlanta

Abstract: The goal of the 1996 Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) was
to end the dependency of needy parents on government benefits, in part by promoting marriage; the pre-reform
welfare system was widely believed to discourage marriage because it primarily provided benefits to single mothers.
However, welfare reform may have actually decreased the incentives to be married by giving women greater financial
independence via the program’s new emphasis on work. This paper uses Vital Statistics data on marriages and
divorces during 1989–2000 to examine the role of welfare reform and other state-level variables on marriage and
divorce rates. The results indicate that implementation of TANF is negatively associated with marriage and divorce
rates, as are pre-TANF waivers from the AFDC program in some specifications.
JEL classification: I3, J1
Key words: welfare reform, marriage, divorce

The authors thank Steve Haider and David Loughran for helpful comments and C. Anitha Manohar for excellent research
assistance. Bitler gratefully acknowledges the financial support of the National Institute of Child Health and Human
Development. The views expressed here are the authors’ and not necessarily those of the Federal Reserve Bank of Atlanta
or the Federal Reserve System. Any remaining errors are the authors’ responsibility.
Please address questions regarding content to Marianne P. Bitler, RAND, P.O. Box 2138, Santa Monica, California 90407,
310-393-0411, ext. 6012, 310-393-7061 (fax), bitler@rand.org.
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The Impact of Welfare Reform on Marriage and Divorce

The U.S. welfare system underwent dramatic change during the 1990s, beginning with
various state-implemented experimental programs and culminating in passage of the Personal
Responsibility and Work Opportunity Reconciliation Act (PRWORA) in 1996. A primary goal
of PRWORA was to end the dependency of needy parents on government benefits by promoting
marriage as well as by encouraging job preparation and work.1 Although there is a burgeoning
literature on the effect of welfare reform on welfare caseloads, women’s labor force outcomes
and children’s well being (e.g., Bell 2001; Schoeni and Blank 2000), few studies have examined
whether welfare reform has affected transitions into and out of marriage. The effect of the
welfare system on marital transitions has considerable policy implications given the recent plan
by the Bush administration to use federal funds to promote marriage as an alternative to public
assistance.
Prior to the 1990s reforms, the welfare system was widely regarded as providing
disincentives to marriage because it primarily allocated benefits to single women with children.
Some studies have concluded that more generous welfare programs were associated with higher
rates of female household headship and nonmarital fertility and lower rates of marriage (e.g.,
Hoynes 1997; Moffitt 1992; Moffitt 1998; and the references therein).2 Welfare generosity
appears to be positively associated with divorce, although empirical findings tend to be weaker
than for other outcomes related to family structure (e.g., Ellwood and Bane 1985; Hoffman and
1

The full text of PRWORA can be found by searching on "H.R. 3734" in the 104th Congress at
http://thomas.loc.gov/home/c104query.html. Other stated goals of PRWORA include reducing the incidence of
nonmarital pregnancies and encouraging the formation and maintenance of two-parent families.
2
However, the estimated effects of welfare tend to be sensitive to the inclusion of state and individual fixed effects,
which generally result in lower significance levels (Hoynes 1997; Moffitt 1994). Earlier studies tended to not find
any significant effects whereas more recent studies tend to find significant effects on marriage and fertility (Moffitt,
1998).

Duncan 1995). The estimated effects generally appear to be relatively small in magnitude and
cannot explain the secular decline in U.S. marriage rates and rise in divorce rates since the
1960s, a period during which average real welfare benefits declined.
Welfare reform was designed to encourage marriage and the formation of two-parent
families as well as promote work and job training. The reforms, which recast Aid to Families
with Dependent Children (AFDC) as Temporary Assistance for Needy Families (TANF), gave
states extreme flexibility in determining eligibility rules as well as benefit levels. Many states
opted to extend eligibility to considerably more two-parent families than were previously eligible
for benefits.3 Although few provisions of PRWORA were directly aimed at encouraging
marriage, the imposition of time limits and other restrictions were implicitly designed to promote
marriage (Moffitt, 2002a). However, as Moffitt (2002b) notes, extending welfare to two-parent
families may not necessarily encourage marriage because some women will meet the TANF
income eligibility requirements if they are single but not if they are married to a spouse with
earned income, reducing their incentive to marry. In addition, welfare reform also may have
indirectly reduced the incentives for marriage if the increased emphasis on work leads to greater
financial independence for women, thereby reducing the need or desire to be married.
Research to date on the effect of welfare reform on marital status has not reached a
consensus.4 The literature has primarily relied on data from the Current Population Survey

3

Prior to reform, two-parent families had primarily been eligible under AFDC-UP (AFDC Unemployed Parents)
program. This program allowed two-parent families to receive AFDC benefits if the primary earner was working
less than 100 hours per month and met the program’s work history requirement in addition to the family meeting the
other AFDC program rules. Welfare reform gave states more flexibility in extending benefits to two-parent families
than under the AFDC-UP program. Concomitant expansions in the Earned Income Tax Credit (EITC), the child tax
credit, and the State Child Health Insurance Program (SCHIP) also expanded the eligibility of low-income families
for federally funded transfer programs during the 1990s.
4
In a related literature on the effect of welfare reform on female household headship, Fitzgerald and Ribar (2001)
find weak evidence in the Survey of Income and Program Participation that pre-1996 waivers reduced female
headship. Schoeni and Blank (2000) similarly find that waivers are negatively associated with female headship
among high school dropouts in CPS data.

1

(CPS). Bitler, Gelbach and Hoynes (2002) find that welfare reform led to a moderate reduction
in the fraction of women currently married and an increase in the fraction who are divorced,
separated or widowed, with some differences by race and ethnicity. Schoeni and Blank (2000)
do not find a significant effect of TANF on women’s marriage rates but do report a positive
effect of waivers-state experimental programs implemented prior to PRWORA-on marriage rates
among female high school dropouts. Kaestner and Kaushal (2001), in contrast, conclude that
both TANF and waivers had negligible effects on the fraction of non-college-graduate females
who are married. Ellwood’s (2000) results suggest that the fraction of low-income mothers who
are married declined slightly more between 1986 and 1999 in states with the most aggressive
welfare reform policies than in states with the least aggressive policies but are not conclusive.
This paper examines the effect of welfare reform on marriage and divorce rates using
Vital Statistics data from 1989 through 2000. As discussed below, Vital Statistics data offer
several advantages over the CPS data used in previous studies, including that they are a near
complete universe of marriages and divorces and the data measure flows into and out of marriage
instead of stocks of the number of people in various marital status categories. Because the
analysis extends through 2000, we examine the effect of federal welfare reform after PRWORA
as well as the effect of state waivers prior to PRWORA. We also estimate the relationship
between marriage creation and destruction and welfare benefit levels, AFDC-UP programs, and
Medicaid eligibility thresholds. The results indicate that welfare reform is associated with lower
marriage rates and lower divorce rates, suggesting that welfare reform as enacted thus far has not
promoted marriage but also has not led to increased dissolution of marriages.

2

THEORETICAL FRAMEWORK
As first formalized by Becker, economic models of marriage and divorce posit that
individuals get married when the benefits less costs (utility) of being married are higher than the
net benefits of remaining single, and analogously for divorce. In a typical utility model of
marriage, an individual’s utility from being single depends on that individual’s earned income if
single, other income if single, and individual characteristics, such as education and race. An
individual’s utility from being married depends on the individual’s earned income if married, the
spouse’s income, other income if married, and individual characteristics. An individual then
chooses the utility maximizing state, marriage or being single.
The utility-maximizing model does not clearly predict the effect of own income on
marital status because higher own earned income raises utility in both the married state and the
single state. As discussed by Fitzgerald and Ribar (2001), if income is shared among spouses,
earning a higher income may make being single more attractive and discourage marriage, or
there is an "independence effect." However, increased income can also have a "stabilizing
effect" on unions, thereby encouraging marriage and discouraging divorce, so the net effect of
higher own income is ambiguous. An increase in a potential spouse’s income, in contrast,
unambiguously increases the utility of being married relative to being single.
Studies typically find that better labor market opportunities for women are negatively
associated with marriage ratessuggesting that the independence effect dominates for
womenwhile better labor market opportunities for men are positively associated with marriage
rates (Blau, Khan, and Waldfogel 2000; Schultz 1994). Divorce rates are typically negatively
associated with men’s labor market opportunities, such as the unemployment rate and average

3

earnings, but are either positively or not correlated with women’s labor market opportunities
(e.g., Hoffman and Duncan 1995).
The structure of welfare programs affects an individual’s marriage and divorce incentives
if program rules result in different benefits for married and single individuals. Because AFDC
benefits were primarily available to single women with dependent children, the AFDC program
decreased the gains from marriage and increased the gains from divorce. As discussed above,
studies typically conclude that states with more generous cash benefits have lower marriage rates
and higher divorce rates than other states. The presence of an AFDC-UP program, which made
two-parent families eligible for AFDC benefits under certain circumstances, could theoretically
reduce or even cancel out the effects of the traditional AFDC program on marriage and divorce,
suggesting that states with AFDC-UP programs should have higher marriage rates and lower
divorce rates than other states. However, previous research suggests that the presence of an
AFDC-UP program does not significantly influence marriage rates (Schultz 1994; Winkler
1995).
Welfare reform could have both direct and indirect effects on marriage. Changes in
program rules that expanded eligibility for two-parent families should increase the benefits to
being married without affecting the benefits of being single. This would lead to an increase in
marriage and a decrease in divorce. The predicted effect of other changes is less clear. Welfare
reforms, in the form of either pre-TANF waivers or TANF, can be classified as "welfare
tightening" or "welfare loosening." Welfare tightening reforms make welfare less generous by,
for example, increasing work requirements and imposing time limits. Welfare loosening reforms
make welfare more generous by raising earnings disregards and assets tests and providing more

4

funds for childcare. Overall, the reforms are usually characterized as welfare tightening and prowork.
The work incentives created by welfare reform have ambiguous effects on marriage and
divorce. As discussed above, improved labor force outcomes for women as a result of welfare
reform could either increase or decrease the utility of being single relative to being married. An
increase in women’s earned income could lead to lower marriage rates and higher divorce rates if
the independence effect dominates or to higher marriage rates and lower divorce rates if the
stabilizing effect dominates. The effect of raising earnings disregards and asset limits is also
theoretically ambiguous, but the net effect may be pro-marriage since the pre-reform earnings
disregards and asset limits are more likely to have been binding for couples than for single
women. Providing more funds for childcare could discourage marriage by reducing women’s
reliance on a spouse to share childcare responsibilities or could encourage marriage via a pronatal effect. Thus, the net effects of welfare reform on marriage and divorce are an empirical
question.

DATA AND METHODS
Previous studies examining the relationship between welfare and marriage patterns have
used either individual- or state-level data to examine the determinants that an individual is never
married, single or divorced or the determinants of state-level marriage and divorce rates, pooling
data across states and years. This analysis follows the state-level approach of regressing
marriage and divorce rates on measures of welfare reform, other social assistance programs,
economic and demographic factors, and other controls, or
yst = Wstβ + Pstδ + Estφ + Dstφ + γs + νt + εst,

5

where yst denotes the log of the marriage or divorce rate per 1000 women aged 15 and older in
state s and year t. The time period examined is 1989-2000.5 Vital Statistics data on the number
of marriages are available for all 50 states and the District of Columbia during this period, a total
of 612 observations, but data on the number of divorces are only available for 572 observations.6
We use Vital Statistics data on marriages and divorces for several reasons. Previous
studies that examine the effect of welfare reform use data from the Current Population Survey
(CPS), which underreports both marriages and divorces (Goldstein 1999). An advantage of Vital
Statistics data is that they are a near universe of marriages and divorces. As noted by Thorton
and Rodgers (1987), survey data like the CPS contain more measurement error than Vital
Statistics registration data because survey respondents may report inaccurate or incomplete
information about household members’ marital histories. Vital Statistics data are useful for
examining flows into and out of marriage, which welfare reform may affect more rapidly than it
affects stock measures such as the share of women who have never been married. CPS data are
more useful than Vital Statistics data for examining the proportion of women who are married at
a given point in time but less so for examining new marriages or divorces.7

5

We chose this period because it starts immediately prior to the onset of the 1990-1991 recession and ends
immediately prior to the onset of the 2001 recession. In addition, AFDC waivers were first implemented during the
early 1990s. The results for the welfare reforms variables are qualitatively similar if the time period is extended
back to 1981.
6
Divorce data are not available for California, Indiana, and Louisiana in 1991-2000; Colorado in 1994-2000; and
Nevada in 1991-1993. The marriage results are not sensitive to excluding observations from states for which any
divorce data are missing.
7
The June supplements to the CPS in some years report the date of first marriage, so the CPS can be used to look at
transitions into first marriages. In addition, CPS waves can be matched to look at marital transitions over time, but
people who move do not remain in the survey, so the sample would likely disproportionately include individuals
who do not experience marital transitions. The National Survey of Family Growth (NSFG) has nearly complete
marital histories, but women’s state of residence is not publicly available and the sample sizes are small. In addition,
the most recent NSFG was in 1995, before implementation of TANF. The Survey of Income and Program
Participation offers larger sample sizes than the NSFG but has more limited information on marital histories. One
advantage of individual-level data is the ability to look at effects across different race and education groups as well
as remarriages versus first marriages. The national Vital Statistics data do not allow such levels of disaggregation
during the TANF period.

6

The vector Wst includes two measures of welfare reform: a dummy variable indicating
whether a state has a major waiver in place prior to TANF (Waiver) and a dummy variable
indicating whether a state has implemented TANF (TANF).8 The coefficients for the welfare
reform variables give the estimated effect of each particular welfare reform relative to the
traditional AFDC program. In other words, the coefficient of the TANF variable gives the
estimated average effect of TANF relative to the AFDC program without waivers, and the
waiver coefficient gives the estimated average effect of waivers from AFDC relative to AFDC
without waivers.9 For the first year that a given welfare reform policy is in effect, the variable is
equal to the fraction of the year after the policy was implemented. (Data sources and details are
in the Data Appendix.)
Pst includes three variables measuring other aspects of public assistance programs: the
value of cash benefits, the availability of AFDC-UP, and the eligibility threshold for Medicaid,
the health insurance program for low-income individuals. The value of cash benefits is
measured by the real maximum AFDC/TANF payment to a family of four with one adult in a
given state and year. The AFDC-UP measure is a dummy variable indicating whether a state has
an AFDC-UP program.10 The regressions also include a variable measuring the income

8

We experimented with using two separate TANF variables, one for states that ever implemented an AFDC waiver
and one for other states, instead of one combined TANF variable. Theoretically, implementation of TANF may
have resulted in fewer changes in welfare policies during the TANF period in states that had waivers from the
AFDC programs than in states without waivers, or many individuals might have adjusted their marital status when
waivers were implemented, either of which would lead to a smaller magnitude for the TANF coefficient for waiver
states than for non-waiver states. Alternatively, states with AFDC waivers might implement more extensive reforms
under TANF than states without waivers, leading to larger effects in the waiver states during the TANF period. The
estimated coefficients of the two TANF variables were not significantly different in any of the specifications,
however, so we report results for the combined variable.
9
The waiver variable is set equal to zero after a state with an AFDC waiver implements TANF.
10
States were required to have an AFDC-UP program by October 1990; the dummy variable remains equal to one
after a state implements TANF.

7

eligibility threshold of pregnant women for Medicaid benefits as a fraction of the federal poverty
level because Medicaid eligibility is positively associated with marriage rates (Yelowitz 1998).
The vector Est includes several controls for local labor market conditions. The
regressions include the overall unemployment rate and its lag, adult women’s labor force
participation rate, the growth rate of non-farm private employment and its lag, the poverty rate,
and real median family income. All of these variables are annual averages.
Dst includes several additional variables to capture demographic and other factors that
influence state-level marriage and divorce rates. The regressions include variables measuring the
fraction of the population that is black and that is Hispanic to control for differences in marriage
and divorce patterns across racial and ethnic groups (e.g., Bennett, Bloom, and Craig 1989). The
regressions also control for the fraction of the state population living in metropolitan areas
because urban residence tends to be negatively associated with women’s marriage rates (Moffitt
1990). We include a dummy variable indicating whether a state has a "covenant marriage"
option.11 As discussed below, we also experimented with a variety of additional controls, none
of which influenced the results.
The regressions also include state and year fixed effects, and some specifications add
state-specific linear time trends. The state fixed effects γs control for time-invariant differences
across states, and the year fixed effects νt control for changes in marriage and divorce rates in a
given year that are common to all states. The time trends control for unobservable factors that
change linearly over time within states and affect marriage and divorce rates; we show results
with and without time trends because the trends absorb much of the variation in the dependent

11

Whether a state allows unilateral divorce is also likely to affect marriage and (particularly) divorce rates, but we
do not include this as a covariate because it does not vary over time within any state during 1989-2000.

8

variables. Unobservable factors that affect marriage and divorce rates are captured by εst, and
the covariance matrix estimates are White/Huber corrected, which allows for arbitrary
heteroscedasticity. Observations are weighted by the population of women aged 15 and older in
each state/year. Table 1 presents summary statistics for the variables used in the analysis.
The analysis focuses on the relationship between marriage and divorce rates and the two
welfare reform variables. The regression coefficients for the welfare reform variables implicitly
measure the effect of the welfare reform in place in a state during a given year relative to the
AFDC program in place in that state prior to implementation of an AFDC waiver and/or TANF.
In other words, the estimated coefficients on the welfare reform variables measure the effect of
waivers and TANF relative to the effect of AFDC within a given state, averaged across states.
This identification method requires that not all states implement waivers or TANF at the same
time. In our coding, two states first implemented major waivers from the AFDC program in
1992, and by 1997 29 states had a major waiver. Nineteen states implemented TANF in 1996
and one in 1998, with the remainder implementing TANF in 1997.12
Table 2 reports mean marriage and divorce rates for states, classified by welfare reform
regime. The means suggest that marriage rates were lower in state/years with waivers from the
AFDC program than in state/years participating in the AFDC program. The average marriage
rate is slightly lower after TANF was implemented than it was during the AFDC program
without waivers. The average divorce rate is also slightly lower in state/years with waivers from
the AFDC program and in state/years after implementation of TANF than the average across
states during the AFDC program without waivers. Of course, these differences may be due to
many factors other than welfare reform. Differences in states’ demographic composition,
12

Table 1 in Bitler, Gelbach, and Hoynes (2002) lists the year when states first implemented waivers and/or TANF
(as of March), and Table 2 describes some of the characteristics of the waivers and TANF programs in states.

9

economic conditions, or other forms of state heterogeneity could underlie the differences in the
means. In addition, time trends in marriages and divorces unrelated to welfare reform could
skew the interpretation of the means in Table 2 since waivers were implemented during the
middle of the sample period and TANF toward the end. We therefore turn to multivariate
analysis to examine the effect of welfare reform on marriage and divorce rates.

RESULTS
Because of concerns about multicollinearity and endogeneity among some of the
variables described above, we present several sets of results. The first column in each table
shows results when only the two welfare reform measures are included in the regressions (in
addition to state and year fixed effects and, in some specifications, linear state time trends). The
second column adds the other measures of public assistance generosity, the third adds the statelevel controls for economic conditions, and the fourth adds the demographic and other controls.
We first discuss the results for marriage rates and then for divorce rates.
Waivers from the AFDC program and implementation of the TANF program are
generally negatively associated with marriage rates. Although the waiver coefficients are not
statistically significant in every specification presented in Tables 3 and 4, all of the TANF
coefficients are statistically significant at the 1 percent level. Waivers from the AFDC program
are associated with a decline in marriage rates of about 4-6 percent, and implementation of
TANF is associated with a 17-21 percent decline relative to marriage rates during the AFDC
program.
Some of the non-welfare reform measures of public assistance are associated with
marriage rates as well. In the results without time trends (Table 3), the real level of cash benefits

10

is generally positively associated with marriage rates, counter to the predicted effect. In the
regressions with linear state trends, in contrast, cash benefits are negatively (but insignificantly)
associated with marriage rates in some specifications. The presence of an AFDC-UP program is
positively (albeit not always statistically significantly) associated with marriage rates, as
expected. The estimated coefficients of the variable measuring the threshold for Medicaid
eligibility are negative in all specifications but not significant.
None of the other economic or demographic variables included in the regressions are
significantly associated with marriage rates. Our failure to find an association between economic
conditions and marriage rates may be surprising given that previous studies suggest that marriage
rates are related to macroeconomic conditions. However, the state and year fixed effectswhich
were not included in many previous studiesabsorb much of the effect of the business cycle and
time-invariant differences across states. If the state fixed effects are not included, the
contemporaneous and lagged employment growth rates, the contemporaneous unemployment
rate, and the female labor force participation rate are positively associated with the marriage rate,
and real median income is negatively associated with the marriage rate. Demographics also
apparently do not change enough within states over time during 1989-2000 to influence marriage
rates.
Welfare reform is also associated with lower divorce rates. AFDC waivers and
implementation of TANF are generally significantly negatively associated with divorce rates, as
Tables 5 and 6 indicate. As in the marriage rate results, the effect of TANF appears to be larger
in magnitude than the effect of waivers. TANF is associated with an average decline in divorce
rates of about 8-15 percent while waivers are associated with a 4-6 percent average reduction in
divorce rates. In addition, the magnitudes of the estimated effects of TANF on divorce rates are

11

smaller than the effects of TANF on marriage rates (although none of the differences appear to
be statistically significant).
The specification with trends indicates that states with an AFDC-UP program have higher
divorce rates even though AFDC-UP was intended to encourage the formation and preservation
of two-parent families (Table 6). Cash welfare benefit maximums and the eligibility threshold
for Medicaid are not significantly associated with divorce rates in any of the specifications.
The results indicate that states with a covenant marriage option have lower divorce rates
in both specifications. Because the regressions include state fixed effects and the result is robust
to including state trends, the results suggest that adoption of a covenant marriage law may affect
divorce rates instead of merely reflecting pre-existing lower propensities for divorce in states that
pass covenant marriage laws. A higher Hispanic population share is negatively associated with
divorce rates when trends are not included (Table 5), and the employment growth rate is
positively associated with divorce rates in all specifications that include that variable.

Robustness of Results
We tried including a wide variety of additional control variables to verify the robustness
of our findings. 13 In results not shown here, including separate controls for male and female
unemployment rates does not qualitatively impact the estimated coefficients of the welfare
reform variables in any of the regressions. The male and female unemployment rates are not
significantly associated with marriage or divorce rates. Including the male labor force
participation rate or the male employment-to-population rate also does not affect the results for

13

All results discussed in the paper but not shown in tables are available from the first author on request.

12

the welfare reform variables, although the male employment rate is negatively associated with
the marriage rate in some specifications.
We also included the incarceration rate in the regressions to further control for the
number of available male marriage partners. The results for the welfare reform variables are
similar to those shown in the tables, and the incarceration rate is not significantly associated with
the marriage rate or the divorce rate. Including a variable measuring the fraction of births that
are to unmarried women, which may affect marriage rates if having a nonmarital birth influences
the likelihood that women will soon marry, does not appreciably affect the magnitudes of the
estimated coefficients of the welfare reform variables. 14 The nonmarital birth ratio variable is
not significantly associated with the marriage rate.
We also included a variable measuring the sex ratio, which is generally believed to affect
marriage and divorce rates (South and Lloyd 1992). The results are similar to those shown in the
tables. The sex ratio, measured here as the ratio of men aged 15 and older to women aged 15 and
older, is not significantly associated with marriage or divorce rates; it is positively associated
with both marriage and divorce rates if, as in most previous studies, state and year fixed effects
(and trends) are not included in the regressions.15 The marriage rate results shown in Table 3 are
also generally robust to not including the 40 observations from states for which divorce data
were missing in any year during the sample period; the significance of the estimated coefficient
of the waiver variable tends to increase in the specification with trends when the observations
without divorce data are excluded.

14

Because the percent of births to unmarried women variable is likely to be endogenous with respect to marriage or
divorce decisions and also may be affected by welfare reform, we do not include it in the main set of covariates.
15
The difference between our results for the sex ratio and those in most previous studies also may be due to the level
of aggregation. We use state-level data that combines all racial and ethnic groups whereas many other studies use
data at the local area level stratified by race and ethnicity. Brien (1997) notes that the effect of marriage markets is
sensitive to the level of aggregation.

13

The results are somewhat sensitive to the use of weights. In all of the results discussed
this far, observations are weighted by the population of women aged 15 and older in a given state
and year. We weight the data in this manner in order to approximately reflect the number of
marriages and divorces occurring at the national level. If the data are not weighted, the
magnitude of the estimated coefficients of the welfare reform variables declines in the marriage
rate models; the waiver variable suggests a decline of about 2-3 percent and the TANF variable
about 10 percent (both are significant at the 5 percent level). In the divorce rate models, the
magnitudes of the welfare reform variables decline and the TANF variable is no longer
significant at the 5 percent level. Finally, the welfare reform results are robust to excluding
observations from Nevada, which has a marriage rate of about 10 times the national average and
a divorce rate of about twice the national average because of nonresidents getting married or
divorced in Nevada.

DISCUSSION
Understanding the effect of welfare reform on marital transitions is important for several
reasons. Along with increased earnings, marriage was a primary route off of AFDC for women
with children (Fitzgerald 1991), so any policy changes that discourage transitions into marriage
could lead to increased dependency on welfare. This would be particularly troubling since
welfare reform as implemented involves time caps. Marital disruption is the single largest cause
of the beginning of a spell of AFDC receipt (Bane and Ellwood 1983), and women experience a
sizable decline in economic status after divorce (Hoffman and Duncan 1988; Smock 1993). The
effect of welfare reform on transitions out of marriage therefore also has considerable
implications for women and their children. Moreover, one of the major goals of reform was

14

raising marriage rates and lowering nonmarital birth rates, making an evaluation of the effects of
reform on marriage and divorce of considerable interest to policymakers.
The results indicate that marriage and divorce rates are generally negatively associated
with AFDC waivers and with implementation of TANF and are robust to a variety of
specification checks. We do not find that welfare reform is "pro-marriage," on balance, but
neither does it appear to encourage divorce. Our finding that welfare reform is associated with
both lower marriage and divorce rates is somewhat of a paradox. A Becker-style model of utility
maximization does not give unambiguous predictions for the effect of welfare reform on marital
transitions, but it is unlikely to predict that changes in welfare policies would have the same
effect on the likelihood of getting married as on the likelihood of getting divorced.
There are several possible explanations for our findings. Changes in welfare programs
may have different effects on single persons than on married persons, perhaps because single
people have different preferences than married people. If welfare reform encouraged or required
more work, single women may be less likely to get married because they have higher earnings,
or the independence effect dominates for these women. For married women, welfare reform may
mean that they would have to work more hours if they divorced than under AFDC program rules,
discouraging divorce. Using individual-level data on work histories pre- and post-welfare
reform to investigate the joint effects of welfare reform on marriage and work while controlling
for individual heterogeneity is therefore an area for future research. In addition, welfare reform
may have introduced considerable uncertainty about the future and made people less likely to
change their current marital status, consistent with our finding of a reduction in transitions into
and out of marriage.

15

Another potential explanation for our findings is that welfare reform has discouraged
divorce among married individuals but has had a much smaller effect among never married
individuals. If the number of divorces has declined as a result of welfare reform, the number of
remarriages would be expected to fall as well; most divorced individuals remarry, and average
time until remarriage is only about three years (Kreider and Fields 2002). Our finding of a
slightly larger effect of TANF on marriage than on divorce is consistent with a large effect on
divorces and remarriages but a small effect among the never married, as found by Bitler,
Gelbach and Hoynes (2002). Data stratified by the number of previous marriages would allow
for examining this possibility, but national Vital Statistics data on remarriages versus first
marriages are not available for the post-TANF period.
This analysis uses data through 2000, four years after passage of PRWORA. However,
the long run effects of welfare reform on marriages and divorces may not yet be evident in our
data, particularly for divorces. If welfare reform lowered the likelihood of getting married but
did not affect the fraction of marriages that end in divorce, then the long run effects of welfare
reform on marriage rates and divorce rates should be in the same direction and of similar
magnitude. Our results suggest that TANF had slightly larger negative effects on marriage rates
than on divorce rates; this is consistent with the expected short run effects if couples take longer
to transition from marriage to divorce than to transition from dating to marriage. The long run
impact of welfare reform on marriage and divorce should be revisited as more data become
available. In the meantime, investigating the effect of welfare reform on separations may
indicate the likely long run impact on divorce rates.
This paper does not report results for detailed aspects of waivers and TANF
implementation within states. The major areas in which state welfare policies and rules vary in

16

the post-AFDC era include: the level of earnings disregards; whether time limits result in
termination or reduction of benefits; whether minor parents who receive TANF benefits are
required to reside with adults; whether there is a family cap that prevents benefits from rising
when a new child is born; and whether a state loosened the 100-hour rule or other rules
governing eligibility for the AFDC-UP program. In results not shown here, we included
interactions of the waiver and TANF variables with variables indicating these five specific
reforms. Neither the marriage nor the divorce regression results indicated any clear pattern in the
coefficients for the specific reform variables. We suspect that difficulties in accurately coding
the specific state reforms underlie our failure to find any clear effects. Bell (2001) reports that
studies have had difficulty convincingly linking changes in welfare caseloads to specific reforms,
similar to our findings here. Future research should further examine the effects of such policies
and other specific reforms, such as child care subsidies and changes to asset limits.

17

DATA APPENDIX
Number of marriages and divorces: National Center for Health Statistics, Vital Statistics of the
United States and Monthly Vital Statistics Report, various years.
AFDC waivers and TANF implementation: The primary source for the dating of state reforms is
the tables on the website of the Assistance Secretary for Planning and Evaluation (ASPE) for the
Department of Health and Human Services, http://aspe.hhs.gov/hsp/WaiverPolicies99/policy_CEA.htm. A state is coded as having an AFDC waiver if it has a "major"
waiver, or that there was a significant deviation from the state’s AFDC program and the waiver
was in place statewide. More details on the coding of the welfare reform variables are provided
in Bitler, Gelbach, and Hoynes (2002) and are available on request.
AFDC-UP program and maximum AFDC/TANF welfare benefits for a 4-person family with 1
adult: Robert Moffitt’s web site, www.econ.jhu.edu/People/Moffitt/DataSets.html. Benefits
deflated using the personal consumption expenditures deflator (1997=100).
Medicaid income eligibility threshold for pregnant women as percentage of federal poverty level:
National Governors’ Association, "State Medicaid coverage of pregnant women and children,"
MCH Update, various years, and Yelowitz (1995).
Population, by age, sex, race and ethnicity: Bureau of the Census website,
http://eire.census.gov/popest/estimates.php.
Percentage of population living in metropolitan areas: Bureau of the Census, Statistical Abstract,
various years. Data for 1989, 1991, 1995, and 1999 were linearly interpolated.
Poverty rate: Bureau of the Census website,
http://www.census.gov/hhes/poverty/histpov/hstpov21.html.
Average annual unemployment rates: Bureau of Labor Statistics, Employment and Earnings and
Geographic Profile of Employment and Unemployment, various years.
Percentage change in non-farm private employment: Bureau of Economic Analysis, Survey of
Current Business, various years.
Women’s labor force participation rate: Bureau of Labor Statistics, Geographic Profile of
Employment and Unemployment, various years.
Real median income for a family of 4: Bureau of the Census website,
http://www.census.gov/hhes/income/4person.html. Deflated using the personal consumption
expenditures deflator (1997=100).
Covenant marriage: Coding based Americans for Divorce Reform website,
http://www.divorcereform.org/cov.html.

18

REFERENCES
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Bell, S.H. 2001. "Why Are Welfare Caseloads Falling?" Urban Institute Discussion Paper No.
01-02, March.
Bennett, N.G., D.E. Bloom, and P.H. Craig. 1989. "The Divergence of Black and White
Marriage Patterns." American Journal of Sociology 95: 692-722.
Bitler, M.P., J.B. Gelbach and H.W. Hoynes. 2002. "The Impact of Welfare Reform on Living
Arrangements." NBER Working Paper No.8784, February.
Blau, F.D., L.M. Kahn and J. Waldfogel. 2000. "Understanding Young Women’s Marriage
Decisions: The Role of Labor and Marriage Market Conditions." Industrial and Labor Relations
Review 53: 624-647.
Brien, Michael J. 1997. "Racial Differences in Marriage and the Role of Marriage Markets."
Journal of Human Resources 32: 741-778.
Ellwood, D.T. 2000. "The Impact of the Earned Income Tax Credit and Social Policy Reforms
on Work, Marriage, and Living Arrangements." National Tax Journal 53: 1063-1105.
Ellwood, D.T. and M.J. Bane. 1985. "The Impact of AFDC on Family Structure and Living
Arrangements." Pp. 137-207 in Research in Labor Economics, Vol. 7, edited by R.G. Ehrenberg.
Greenwich, CT: JAI Press.
Fitzgerald, J.M. and D.C. Ribar. 2001. "The Impact of Welfare Waivers on Female Headship
Decisions." Mimeo, Washington, DC: George Washington University, November.
Fitzgerald, J. 1991. "Welfare Durations and the Marriage Market: Evidence from Survey of
Income and Program Participation." Journal of Human Resources 26: 545-561.
Goldstein, J.R. 1999. "The Leveling of Divorce in the United States." Demography 36: 409-414.
Hoffman, S.D. and G.J. Duncan. 1988. "What Are the Economic Consequences of Divorce?"
Demography 25: 641-645.
Hoffman, S.D. and G.J. Duncan. 1995. "The Effect of Incomes, Wages, and AFDC Benefits on
Marital Disruption." Journal of Human Resources 30: 19-41
Hoynes, H.W. 1997. "Does Welfare Play Any Role in Female Headship Decisions?" Journal of
Public Economics 65: 89-117.

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Kaestner, R. and N. Kaushal. 2001. "Immigrant and Native Responses to Welfare Reform."
NBER Working Paper No. 8541, October.
Kreider, R.M. and J.M. Fields. 2002. “Number, Timing, and Duration of Marriages and
Divorces: 1996.” Current Population Reports P70-80, February.
Moffitt, R. 1990. "The Effect of the U.S. Welfare System on Marital Status." Journal of Public
Economics 41: 101-124.
Moffitt, R. 1992. "Incentive Effects of the U.S. Welfare System: A Review." Journal of
Economic Literature 30: 1-61.
Moffitt, R. 1994. “Welfare Effects on Female Headship with Area Effects.” Journal of Human
Resources 29: 621-636.
Moffitt, R. 1998. "The Effect of Welfare on Marriage and Fertility." Pp. 50-97 in Welfare, the
Family, and Reproductive Behavior, edited by R. Moffitt. Washington, DC: National Academy
Press.
Moffitt, R. 2002a. "Economic Effects of Means-Tested Transfers in the U.S." NBER Working
Paper No. 8730, January.
Moffitt, R. 2002b. "The Temporary Assistance for Needy Families Program." NBER Working
Paper No. 8749, February.
Schoeni, R.F. and R.M. Blank. 2000. "What Has Welfare Reform Accomplished? Impacts on
Welfare Participation, Employment, Income, Poverty, and Family Structure." NBER Working
Paper No. 7627, March.
Schultz, T.P. 1994. "Marital Status and Fertility in the United States: Welfare and Labor Market
Effects." Journal of Human Resources 29: 637-669.
Smock, P.J. 1993. "The Economic Costs of Marital Disruption for Young Women Over the Past
Two Decades." Demography 30: 353-371.
South, S.J. and K.M. Lloyd. 1992. "Marriage Opportunities and Family Formation: Further
Implications of Imbalanced Sex Ratios." Journal of Marriage and the Family 54: 440-451.
Thorton, A. and W.L. Rodgers. 1987. “The Influence of Individual and Historical Time on
Marital Dissolution.” Demography 24: 1-22.
Winkler, A.E. 1995. "Does AFDC-UP Encourage Two-Parent Families?" Journal of Policy
Analysis and Management 14: 4-24.
Yelowitz, A.S. 1995. "The Medicaid Notch, Labor Supply, and Welfare Participation: Evidence
from Eligibility Expansions." Quarterly Journal of Economics 110: 909-939.

20

Yelowitz, A.S. 1998. "Will Extending Medicaid to Two-Parent Families Encourage Marriage?"
Journal of Human Resources 33: 833-865.

21

Table 1. Sample Means
Variable
Marriage rate per 1000 women aged 15 and older

Mean
0.022

SD
0.016

Max
0.259

Min
0.008

Divorce rate per 1000 women aged 15 and older

0.011

0.003

0.028

0.004

Share of year major AFDC waiver in effect

0.129

0.316

1.000

0.000

Share of year TANF in effect

0.322

0.456

1.000

0.000

Real max. AFDC/TANF benefits, family of 4 ($1000)

6.034

2.358

14.088

1.710

State has AFDC-UP program

0.940

0.238

1.000

0.000

Medicaid eligibility threshold as share of poverty level

1.654

0.480

4.000

0.000

Overall unemployment rate

0.056

0.015

0.114

0.022

Female labor force participation rate

0.588

0.039

0.703

0.430

Employment growth rate

0.019

0.015

0.090

-0.051

Share of population under the poverty level

0.134

0.034

0.264

0.029

52.595

6.916

78.410

35.419

State has covenant marriage option

0.009

0.094

1.000

0.000

Share of population living in metro areas

0.794

0.161

1.000

0.202

Share of population that is black

0.126

0.081

0.666

0.003

Share of population that is Hispanic

0.101

0.103

0.421

0.005

Real median income, family of 4 ($1000)

Note: Observations are weighted by the state/year population of women aged 15 and older. Data are at the state level
for 1989-2000, except divorce data are missing for some state/year combinations during the 1990s. Dollar amounts
in 1997 $. The number of observations is 612 except for the divorce rate, which is 572 observations.

22

Table 2. Marriage and Divorce Rates, by State Welfare Reform Status
Variable

AFDC

Waiver

TANF

Marriage rate

0.0230
(0.0010)
[333]

0.0193
(0.0004)
[83]

0.0214
(0.0012)
[196]

Divorce rate

0.0112
(0.0002)
[315]

0.0101
(0.0003)
[75]

0.0103
(0.0002)
[182]

Note: Shown are average marriage and divorce rates, with standard errors in parentheses and number of observations
in brackets, by welfare reform regime. Column 1 is state/year combinations with no welfare reform; column 2 is
state/year combinations with a major AFDC waiver; column 3 is state/year combinations for TANF. Observations
are weighted by the female population aged 15 and older in the state/year.

23

Table 3. Determinants of Marriage Rates, without State Time Trends
Variable
Share of year major AFDC waiver in effect

(1)
-0.059*
(0.025)
Share of year TANF in effect
-0.197**
(0.058)
Log of real max. AFDC/TANF benefits, family of 4
AFDC-UP program
Medicaid eligibility threshold

(2)
-0.052*
(0.026)
-0.210**
(0.058)
0.185†
(0.100)
0.031
(0.023)
-0.014
(0.023)

Overall unemployment rate
Female labor force participation rate
Employment growth rate
Share of population under the poverty level
Log of real median income, family of 4

(3)
-0.047†
(0.028)
-0.192**
(0.050)
0.230*
(0.098)
0.046
(0.032)
-0.018
(0.027)
0.653
(0.980)
0.832†
(0.486)
0.424
(0.577)
0.358
(0.290)
-0.146
(0.242)

Covenant marriage state
Share of population living in metro areas
Share of population that is black
Share of population that is Hispanic
Adjusted R2
N

0.877
612

0.878
612

0.881
612

(4)
-0.047†
(0.028)
-0.196**
(0.051)
0.216*
(0.104)
0.056
(0.038)
-0.014
(0.029)
0.793
(0.973)
0.575
(0.417)
0.536
(0.576)
0.434
(0.296)
-0.188
(0.266)
0.068
(0.043)
-0.272
(0.551)
-3.197
(2.024)
-1.402
(0.950)
0.882
612

Note: Shown are coefficients from regressions of the determinants of marriage rates during 1989-2000. The
dependent variable is the natural log of the marriage rate. The regressions for columns 3 and 4 also include one lag
of the unemployment rate and employment growth rate variables. All regressions include state and year fixed
effects. Robust standard errors (adjusted for clustering by state/year) in parentheses. Observations are weighted by
the female population aged 15 and older in the state/year.
† p<0.10; * p<0.05; ** p<0.01

24

Table 4. Determinants of Marriage Rates, with State Time Trends
Variable
Share of year major AFDC waiver in effect

(1)
-0.048*
(0.020)
Share of year TANF in effect
-0.176**
(0.040)
Log of real max. AFDC/TANF benefits, family of 4
AFDC-UP program
Medicaid eligibility threshold

(2)
-0.044*
(0.022)
-0.166**
(0.040)
0.007
(0.104)
0.103*
(0.043)
-0.040
(0.041)

Overall unemployment rate
Female labor force participation rate
Employment growth rate
Share of population under the poverty level
Log of real median income, family of 4

(3)
-0.044†
(0.024)
-0.168**
(0.041)
-0.017
(0.100)
0.097†
(0.050)
-0.041
(0.040)
-0.064
(1.020)
-0.303
(0.394)
0.076
(0.547)
-0.244
(0.278)
0.051
(0.202)

Covenant marriage state
Share of population living in metro areas
Share of population that is black
Share of population that is Hispanic
Adjusted R2
N

0.905
612

0.908
612

0.908
612

(4)
-0.047†
(0.024)
-0.174**
(0.043)
-0.046
(0.102)
0.096†
(0.051)
-0.039
(0.041)
0.056
(1.062)
-0.264
(0.393)
0.144
(0.560)
-0.192
(0.267)
0.022
(0.202)
0.002
(0.055)
-0.649
(0.509)
-1.635
(3.733)
-2.355
(1.495)
0.907
612

Note: Shown are coefficients from regressions of the determinants of marriage rates during 1989-2000. The
dependent variable is the natural log of the marriage rate. The regressions for columns 3 and 4 also include one lag
of the unemployment rate and employment growth rate variables. All regressions include state and year fixed effects
and linear state time trends. Robust standard errors (adjusted for clustering by state/year) in parentheses.
Observations are weighted by the female population aged 15 and older in the state/year.
† p<0.10; * p<0.05; ** p<0.01

25

Table 5. Determinants of Divorce Rates, without State Time Trends
Variable
Share of year major AFDC waiver in effect

(1)
-0.050**
(0.017)
Share of year TANF in effect
-0.124*
(0.054)
Log of real max. AFDC/TANF benefits, family of 4
AFDC-UP program
Medicaid eligibility threshold

(2)
-0.052**
(0.017)
-0.126*
(0.055)
-0.074
(0.118)
-0.007
(0.021)
-0.014
(0.012)

Overall unemployment rate
Female labor force participation rate
Employment growth rate
Share of population under the poverty level
Log of real median income, family of 4

(3)
-0.061**
(0.016)
-0.144**
(0.048)
0.032
(0.122)
-0.021
(0.024)
-0.010
(0.013)
-0.671
(0.875)
0.531
(0.414)
1.834**
(0.621)
0.079
(0.292)
0.166
(0.202)

Covenant marriage state
Share of population living in metro areas
Share of population that is black
Share of population that is Hispanic
Adjusted R2
N

0.916
572

0.916
572

0.919
572

(4)
-0.060**
(0.016)
-0.154**
(0.052)
-0.025
(0.115)
0.011
(0.019)
0.000
(0.010)
-0.369
(0.831)
-0.187
(0.380)
1.819**
(0.555)
0.180
(0.263)
-0.013
(0.193)
-0.083*
(0.040)
-0.194
(0.260)
-1.169
(1.444)
-5.086**
(0.832)
0.929
572

Note: Shown are coefficients from regressions of the determinants of divorce rates during 1989-2000; divorce data
are not available for some state/years during the 1990s. The dependent variable is the natural log of the divorce rate.
The regressions for columns 3 and 4 also include one lag of the unemployment rate and employment growth rate
variables. All regressions include state and year fixed effects. Robust standard errors (adjusted for clustering by
state/year) in parentheses. Observations are weighted by the female population aged 15 and older in the state/year.
† p<0.10; * p<0.05; ** p<0.01

26

Table 6. Determinants of Divorce Rates, with State Time Trends
Variable
Share of year major AFDC waiver in effect

(1)
-0.045**
(0.016)
Share of year TANF in effect
-0.084
(0.059)
Log of real max. AFDC/TANF benefits, family of 4
AFDC-UP program

(2)
-0.042**
(0.016)
-0.084
(0.059)
-0.142
(0.120)
0.090**
(0.020)

Medicaid eligibility threshold
Overall unemployment rate
Female labor force participation rate
Employment growth rate
Share of population under the poverty level
Log of real median income, family of 4

(3)
-0.052**
(0.016)
-0.108*
(0.055)
-0.131
(0.123)
0.049**
(0.018)
0.009
(0.020)
-0.320
(0.802)
-0.067
(0.391)
1.596**
(0.461)
0.127
(0.292)
0.122
(0.180)

Covenant marriage state
Share of population living in metro areas
Share of population that is black
Share of population that is Hispanic
Adjusted R2
N

0.942
572

0.944
572

0.947
572

(4)
-0.055**
(0.016)
-0.123*
(0.061)
-0.166
(0.122)
0.045*
(0.018)
0.015
(0.019)
-0.124
(0.859)
-0.023
(0.361)
1.418**
(0.498)
0.122
(0.280)
0.093
(0.168)
-0.141*
(0.064)
-0.237
(0.268)
-6.519†
(3.829)
-3.055
(1.890)
0.948
572

Note: Shown are coefficients from regressions of the determinants of divorce rates during 1989-2000; divorce data
are not available for some state/years during the 1990s. The dependent variable is the natural log of the divorce rate.
The regressions for columns 3 and 4 also include one lag of the unemployment rate and employment growth rate
variables. All regressions include state and year fixed effects and linear state time trends. Robust standard errors
(adjusted for clustering by state/year) in parentheses. Observations are weighted by the female population aged 15
and older in the state/year.
† p<0.10; * p<0.05; ** p<0.01

27