Embed Size (px)
Citation preview
Long-Term Impacts of Childhood Medicaid Expansions
on Outcomes in Adulthood∗
David W. Brown† Amanda E. Kowalski‡ Ithai Z. Lurie§
June 22, 2018
Abstract
We use administrative data from the IRS to examine long-term impacts of child-
hood Medicaid eligibility expansions on outcomes in adulthood at each age from 19–28.
Greater Medicaid eligibility increases college enrollment and decreases fertility, espe-
cially through age 21. Starting at age 23, females have higher contemporaneous wage
income, although male increases are imprecise. Together, both genders have lower
mortality. These adults collect less from the earned income tax credit and pay more in
taxes. Cumulatively from ages 19–28, at a 3% discount rate, the federal government
recoups 57 cents of each dollar of its “investment” in childhood Medicaid.
∗A previous version of this paper circulated as “Medicaid as an Investment in Children: What is theLong-Term Impact on Tax Receipts?” We thank Manasi Deshpande, Danny Yagan, and participants atthe NBER Summer Institute, UCLA Anderson, the University of Connecticut, the University of Kentucky,Vanderbilt, and Yale for helpful comments. Kate Archibald, William Bishop, Saumya Chatrath, AnnaCornelius-Schecter, Rebecca McKibbin, Pauline Mourot, Sam Moy, Ljubica Ristovska, Sukanya Sravasti,Rae Staben, and Matthew Tauzer provided excellent research assistance. Support for Amanda Kowalski’swork on this project was provided in part by National Science Foundation (NSF) CAREER Award 1350132,National Institute on Aging of the National Institutes of Health (NIH) Award P30AG12810, and the RobertWood Johnson Foundation. The findings, interpretations, and conclusions expressed in this paper are entirelythose of the authors and do not necessarily represent the views of the US Department of Treasury or theRobert Wood Johnson Foundation.†Office of Tax Analysis, US Department of the Treasury. E-mail: [email protected].‡Corresponding author. Department of Economics, Yale University. 37 Hillhouse Avenue, Room 32, Box
208264, New Haven CT 06520. E-mail: [email protected].§Office of Tax Analysis, US Department of the Treasury. E-mail: [email protected].
1
1 Introduction
In the United States, several elements of the social safety net target children. One rationale
for targeting children is that the childhood years are formative. In addition to delivering
short-term gains, programs targeted at children have the promise of improving human capital
formation, health, and economic outcomes. We assess and compare the age profiles of such
long-term gains by examining the impact of policies that occurred in the past.
Using data from the Internal Revenue Service (IRS), we examine long-term impacts of
previous expansions to childhood Medicaid on several outcomes during adulthood. Medicaid,
an important element of the U.S. social safety net that provides health insurance to low-
income individuals, began over 50 years ago in 1965. It expanded dramatically in the 1980s
and again in the 1990s with the establishment of the State Children’s Health Insurance
Program (SCHIP) in 1997. These combined “Medicaid” expansions resulted in a tremendous
amount of variation in health insurance eligibility for similar children born in different months
residing in different states. We focus on children born from January 1981 to December 1984,
as these children were exposed to many expansions, and we can observe their outcomes in each
year of adulthood from age 19 to 28. Our main outcomes include college enrollment, fertility,
mortality, wage income, earned income tax credit (EITC) receipts, and tax payments.
One reason why we might expect to observe long-term impacts of Medicaid eligibility on
children is that a very large literature demonstrates robust short-term impacts on children
and other groups. Seminal papers examine a doubling of eligibility for children from 1984
to 1992 and increases in eligibility for pregnant women from 1979 to 1992 (Cutler and
Gruber, 1996; Currie and Gruber, 1996a,b). Pioneering the use of a simulated instrument
methodology that we adapt to our application, they find increases in Medicaid coverage and
utilization of medical care, as well as reductions in childhood and infant mortality. Card
and Shore-Sheppard (2004) use a regression discontinuity design to examine two childhood
eligibility increases examined by the previous literature, and they find modest increases in
coverage. Several other papers revisit Medicaid expansions and later SCHIP expansions,
generally finding Medicaid takeup rates from 5 to 24 percent.1
Building on the early literature, several papers have found short-term impacts of Medicaid
on outcomes that could serve as mechanisms for long-term impacts. These outcomes include
child and infant mortality (Goodman-Bacon, 2018), doctor visits (Lurie, 2009), births (Lin-
drooth and McCullough, 2007), vaccination rates (Joyce and Racine, 2003), assets (Gruber
and Yelowitz, 1999), marriage (Yelowitz, 1998), and abortions (Blank et al., 1996). Findings
from the Oregon Health Insurance Experiment demonstrate short-term impacts on a wide
1See Blumberg et al. (2000); Rosenbach et al. (2001); Zuckerman and Lutzky (2001); Cunningham et al.(2002); Cunningham et al. (2002); Lo Sasso and Buchmueller (2004); Ham and Shore-Sheppard (2005);Hudson et al. (2005); Bansak and Raphael (2006); Buchmueller et al. (2008); and Gruber and Simon (2008).
2
variety of other outcomes (Finkelstein et al., 2012; Taubman et al., 2014; Baicker et al., 2013,
2014; Finkelstein et al., 2016).
A small number of papers find long-term impacts of Medicaid on health and health care
utilization. Sommers et al. (2012) finds impacts of recent Medicaid expansions on mortality
up to five years later. Revisiting one of the expansions examined by Card and Shore-Sheppard
(2004), Wherry and Meyer (2016) find a decrease in disease-related mortality for black teens
between ages 15 and 18, and Wherry et al. (2015) find decreases in hospital and emergency
department visits for black adults, but neither paper can reject decreases for whites. Other
work by Miller and Wherry (2016) finds that in utero exposure to Medicaid decreases obesity
as well as some types of hospitalizations in adulthood. Earlier work by Currie et al. (2008)
finds evidence that children living in states with greater Medicaid eligibility in early childhood
have better health outcomes later in childhood.
Other papers set the stage for why we might find long-term impacts of Medicaid on
economic outcomes in adulthood. Levine and Schanzenbach (2009) and Cohodes et al.
(2016) find long-term impacts of childhood Medicaid expansions on human capital formation.
Boudreaux et al. (2016) find impacts of the initial adoption of Medicaid on an index of health
outcomes, but they do not have enough power to detect meaningful impacts on economic
outcomes. A growing literature finds impacts on the long-term economic outcomes of children
exposed to other elements of the social safety net, including disability insurance (Deshpande,
2016), the Food Stamp program (Hoynes et al., 2016), housing policy (Chetty et al., 2016),
and a deworming program in Kenya (Baird et al., 2016).
Using administrative data from the IRS, we can examine long-term impacts of Medicaid
on outcomes that have not been examined by the Medicaid literature, and we can compare
how several outcomes evolve with each year of age. The tax data include all individuals
with any interaction with the U.S. tax system starting in 1996, yielding a very large sample
size. We focus on all children born from 1981 to 1984. Given the time span of our data,
these children are young enough for us to link them to their parents to determine Medicaid
eligibility during childhood, and they are old enough for us to observe their outcomes from
ages 19 to 28. By comparing outcomes for the same cohorts over a range of adult ages, we
can discern relationships between human capital formation, fertility, and earnings.
The tax data do not contain information on Medicaid directly, but we simulate Medicaid
eligibility in our data using an eligibility calculator that we developed from federal and state
policies, which we distribute in the BKL Calculator Appendix.2 We also examine robustness
2Several individuals contributed to the development of the calculator, and we acknowledge them in theBKL Calculator Appendix available at http://users.nber.org/~kowalski/BKL.Calculator.Appendix.
zip. Along with the calculator itself, we provide detailed documentation on each source. We also distributesimulated Medicaid eligibility series that we constructed by applying our calculator to our tax data and tothe Current Population Survey (CPS).
3
to simulating Medicaid eligibility in the Current Population Survey (CPS). We focus on
Medicaid eligibility rather than takeup or spending because policymakers can manipulate
eligibility thresholds directly. However, we also examine measures of Medicaid takeup and
spending derived from the Medicaid Statistical Information System (MSIS).3 When we add
external sources of data, we still take advantage of our longitudinal tax data to assign
childhood states of residence.
Our baseline specification harnesses variation across children born in the same state in
different birth month cohorts and across children born in different states in the same birth
month cohort. While our specification is subject to similar concerns as other specifications
that harness state-level policy variation, we conduct exercises that alleviate some concerns.
Of particular note, we conduct a dose-response exercise made possible by our longitudinal
data. The foundation for the dose-response exercise is that poorer children are more likely
to be eligible for Medicaid, so we should see greater impacts of Medicaid on children who
resided in poorer households during childhood. The results of our dose-response exercise
show that state-level factors that affect all children regardless of household income do not
drive our results. We also conduct a falsification exercise using gender, and the results lend
credibility to our specification.
Our results show long-term impacts of Medicaid eligibility from birth to age 18 on several
outcomes in adulthood. Children with more years of Medicaid eligibility during childhood
enroll in college at higher rates, especially through age 22, and they still have a higher
probability of having ever enrolled in college by age 26. These children are less likely to have
their first dependent child in their teenage years, but impacts on this measure of fertility are
most pronounced from ages 18–21, overlapping with the ages of greatest impact on college
enrollment. After age 21, as individuals who delayed their fertility have their first child,
impacts on fertility decrease, but an absolute decrease is still apparent at age 28. Temporal
patterns in adult mortality are harder to discern, but cumulative adult mortality rates are
lower for individuals who had greater Medicaid eligibility as children.
Turning to economic outcomes, females with more years of Medicaid eligibility during
childhood have higher wage income starting at age 23, and the increases get larger with age.
By age 28, each additional year of simulated childhood Medicaid results in an increase of
$1,784 in cumulative wage income on a base of $136,600. Male increases are smaller and
imprecise. However, both genders collect less from the earned income tax credit (EITC), at
each age from 19–28. Cumulatively by age 28, for each additional year of simulated childhood
Medicaid eligibility, they collect $182 less on a base of $3,044. The increase in their total
tax payments grows with age. Cumulatively by age 28, they pay $533 more in total taxes
on a base of $20,623 for each additional year of simulated childhood Medicaid eligibility.
3We distribute these data in the BKL Calculator Appendix.
4
Each additional year of simulated Medicaid eligibility results in an additional 0.59 years of
coverage and costs the government $636. Discounted to birth at a 3% rate and focusing on
the IV estimates, each additional year of Medicaid eligibility increases spending by $433 and
taxes by $248. The ratio of $248 to $433 implies that the government recoups 57 cents of
each dollar it spends on childhood Medicaid by age 28. Forecasts indicate that Medicaid
pays for itself by age 32 when discounted to birth at a 3% rate and delivers positive fiscal
returns thereafter.
In the next section, we discuss our data and methodology. In Section 3, we present our
main results on the long-term impact of Medicaid. We examine heterogeneity in our results
and the robustness of our results in Section 4. In Section 5, we examine Medicaid takeup
and spending, and we calculate the implied fiscal return on investment in Medicaid. We
conclude in Section 6.
2 Data and Methodology
2.1 Sample Selection
Our primary source of data comes from administrative tax records obtained from the Internal
Revenue Service (IRS). These data span 1996 to the present and include all individuals who
interacted with the tax system in those years. With access to an array of tax forms, we can
examine effects for a variety of outcomes with a high level of precision and generality. These
data have been used in few studies because of extremely limited accessibility due to their
confidential nature. Examples of studies that have used these data include Chetty et al.
(2011), Chetty et al. (2013), and Yagan (2016). Our project is one of the first to use the
population of administrative tax data to evaluate the intersection of health policy and tax
administration, alongside other work coauthored by members of our team (Helmchen et al.,
2015; Heim et al., 2017)
We focus on children born from 1981 to 1984 because these children are old enough for us
to observe their adult outcomes from ages 19 to 28, and they are young enough for us to link
them to their parents so that we can estimate their Medicaid eligibility during childhood.
We restrict analysis to children that we can link to their parents using Form 1040 in 1997,
the earliest year in which we are confident in the linkage. We do not require parents to
claim the children in any year other than 1997, but we do require parents to file a Form
1040 in each tax year from 1996 (the first year of our data) through the year in which the
child turns 18 to increase the accuracy of our Medicaid eligibility estimates. After imposing
other minor restrictions, the filing restriction eliminates about 20% of children, yielding a
main sample of 10,045,162 children.4 We examine robustness to this restriction by imputing
4Census estimates show that approximately 14.6 million children were born in 1981–1984. In the taxdata, we begin with 13,834,198 dependents claimed on Form 1040 in 1997 that were born in 1981–1984
5
Medicaid eligibility for children whose parents do not file in years other than 1997. In any
given year, the vast majority of low-income parents file because the EITC and the child tax
credit are refundable, providing an incentive to file even if the taxpayer faces no tax liability.
Taxpayers whose employers file Form W-2 have another incentive to file because if they do
not, they forfeit any federal income tax that has been withheld.
Even if children in our sample do not file in every year of adulthood, we can observe our
six main outcomes—college enrollment, fertility, mortality, wage income, earned income tax
credit (EITC) receipts, and tax payments—given a rich set of returns filed by other parties
and the longitudinal nature of our data. For example, colleges file Form 1098-T, from which
we derive college enrollment. The Social Security Administration maintains death records
that are linked to the administrative tax records. Employers file Form W-2, which provides
information on wage income, payroll taxes, and federal income tax withholding. If individuals
do not file, their EITC receipts are zero. Our measure of fertility only requires individuals
in our sample to claim a child on a Form 1040 in at least one year of our data. From a single
filing, we can infer the age of the individual when their child was born.
2.2 Medicaid Eligibility
Our administrative tax data do not contain information on Medicaid directly, but we cal-
culate Medicaid eligibility in our data using a calculator that we developed. We provide
the calculator and associated documentation in the BKL Calculator Appendix. The calcu-
lator incorporates many federal and state policies that affected Medicaid eligibility for the
children in our sample. Since Medicaid eligibility was initially linked to eligibility for cash
assistance, we incorporate need standards defined by the Aid to Families with Dependent
Children (AFDC) program. We also incorporate eligibility thresholds from the State Chil-
dren’s Insurance Program (SCHIP) as well as federally mandated expansions to Medicaid,
such as OBRA 90.
To determine Medicaid eligibility for an individual at a given age, we first calculate
“household FPL,” household income as a percent of the federal poverty level (FPL). The
FPL is a statutory function of household size, household income, year, and state of residence;
all states except Alaska and Hawaii share the same FPL. For years prior to when our data
(we rely upon the date of birth (DOB) maintained by the Social Security Administration linked to thedependent’s social security number rather than taxpayer-provided DOB on Form 1040). However, someof these dependents are duplicates claimed on more than one return. Addressing this issue by randomlyselecting one return for duplicates, we arrive at 13,113,433 children matched as dependents in 1997. We loseadditional children for whom we cannot identify a state of residence in each filing year from 1996 through age18, arriving at 12,852,988 children. Restricting the sample to children whose parents file in every tax yearfrom 1996 until the child turns 18, we arrive at our main estimation sample of 10,045,162 children: 4,913,139females and 5,132,023 males. Part of the reason why we lose sample size in the last selection step is that3,429,112 Form 1040 records are missing from our data in Florida in 1999 (some of the missing records arefor parents of children who would otherwise be in our main sample).
6
start in 1996, we hold household FPL constant using household FPL in the year of parent-
child linkage. We then compare household FPL to the eligibility threshold in the calculator
that corresponds to the household’s state of residence, the month of eligibility, and the child’s
age in December.5
Since we are interested in the long-term impact of Medicaid eligibility, we construct mea-
sures of cumulative eligibility during childhood. We do so by summing Medicaid eligibility
at each age from birth to age 18. To calculate Medicaid eligibility at ages before our data
begin (before age 12 for our youngest cohort and age 15 for our oldest cohort), we assume
that the child resides in the state of residence observed in the year of linkage (1997).
To address measurement error and to isolate policy-induced variation in Medicaid eligi-
bility, we first construct simulated measures of Medicaid eligibility in the tradition of Currie
and Gruber (1996b). To construct simulated Medicaid eligibility in our data, we first extract
a national sample of 200,000 dependents from 1997. For each eligibility year and state, we
use our calculator to compute the share of children born in each month of the simulation
sample who are eligible for Medicaid. To take into account trends in income over time, we
also examine robustness to simulating Medicaid eligibility using a national sample drawn
from the CPS in each year. We construct our main measure of simulated Medicaid eligibility
during childhood by summing the assigned simulated Medicaid eligibility from birth to age
18 for each individual in our data. Simulated eligibility varies with the vector of states in
which we observe the child residing in our longitudinal data.
Overall, individuals in our sample were eligible for Medicaid from birth to age 18 for an
average of 3.77 years, with a standard deviation of 5.61 years. Simulated Medicaid eligibility
is 4.49 years on average, with a standard deviation of 1.60 years. Figure 1 shows cross-state
variation in simulated Medicaid eligibility during childhood for children born in our oldest
and youngest cohorts, assuming that they resided in the same state from birth to age 18,
so simulated eligibility does not vary within a state.6 As shown in the top panel, children
born in January 1981 had just over one year of simulated eligibility from birth to age 18
in Mississippi and more than six years in Vermont. As shown in the bottom panel, there
is still a considerable amount of variation across states for children born in December 1984.
However, individuals in this youngest cohort have a population-weighted average of 1.85
additional years of simulated eligibility relative to individuals in the oldest cohort. There is
also variation in simulated Medicaid eligibility across individuals born in different months of
the same calendar year that is not visible in this figure.
5We only use the eligibility threshold from December of each year because we only observe the informationneeded for the calculator once per year (after the tax year is complete). Our focus on December eligibilityshould overstate our Medicaid eligibility levels because eligibility generally increased over time.
6Figure 1 shows cross-state variation in actual (non-simulated) Medicaid eligibility.
7
Figure 1: State Variation in Simulated Years Eligible for Medicaid, Ages 0–18
7.18 − 7.226.15 − 7.185.21 − 6.154.68 − 5.214.22 − 4.681.23 − 4.22
Born Jan '81Eligibility
7.18 − 9.356.15 − 7.185.21 − 6.154.68 − 5.214.22 − 4.683.45 − 4.22
Born Dec '84Eligibility
Note. Bins reflect the sextiles of the distribution for the cohort born in December 1984. We present theJanuary 1981 and December 1984 cohorts because they are the oldest and youngest cohorts in our sample.
8
2.3 Methodology
To estimate the effect of Medicaid eligibility during childhood on long-term outcomes by
age, we estimate the following main reduced form specification:
Yi,a = βa
18∑t=0
Zi,t + γc + γs + εi,a, (1)
where∑18
t=0 Zi,t represents our “simulated instrument:” simulated years eligible for Medicaid
from birth to age 18 for individual i, where t denotes childhood age. We interpret the
coefficient βa as the effect of an additional year of Medicaid eligibility during childhood on
an outcome Yi,a measured at adult age a. We estimate equation (1) for each adult age from
19 to 28 for two measures of each main outcome: (i) a contemporaneous measure at the given
age, which we use to discern temporal patterns in the effect of Medicaid eligibility, and (ii)
a cumulative measure from age 19 to the given age, which we use to measure an aggregate
effect of Medicaid eligibility. We estimate equation (1) in the full sample and separately for
females and males.
Equation (1) incorporates fixed effects for monthly birth cohort c and fixed effects for state
of residence s at age 15 (the youngest age at which we observe all individuals in our sample).
These fixed effects control for time-invariant state characteristics and state-invariant birth
month cohort characteristics. The specification harnesses variation in Medicaid eligibility
across birth month cohorts within a state and across states within a birth month cohort.7
We examine robustness to the inclusion of income controls, but we exclude income controls
from the main specification because household income at age 15 could be a function of
Medicaid eligibility for children at previous ages, which would lead to an attenuation of our
estimates. We cluster standard errors by state of residence at age 15 to account for arbitrary
correlations within states over time.
While our specification is subject to similar concerns as other specifications that harness
policy variation by state and cohort, the longitudinal nature of our data allows us to conduct
a dose-response exercise that alleviates some concerns. The foundation for the dose-response
exercise is that poorer children are more likely to be eligible for Medicaid, so we should see
greater impacts of Medicaid on adults who resided in poorer households during childhood.
7For robustness, we also conduct an exercise that harnesses only variation from OBRA 90, a federalpolicy that selectively applied to children born in different months of the same year. We estimate a regressiondiscontinuity specification with a discontinuity at September 30, 1983, following Card and Shore-Sheppard(2004), Wherry and Meyer (2016), and (Wherry et al., 2015). Although the results are qualitatively similarto our main results, they are much noisier, so we report them and discuss their limitations relative to ourpreferred specification in Online Appendix 21. While Card and Shore-Sheppard (2004) also examine theOBRA 89 expansion, which started in 1990 and applied to children under six, we do not use this source ofeligibility because the youngest children in our sample were six years of age by December 1990.
9
To implement the exercise, we estimate equation (1) on samples stratified by household
FPL during childhood. To the extent that we see a dose-response relationship between
household FPL during childhood and long-term impacts, we can be confident that policies
or economic changes coincident with Medicaid expansions that affected all children regardless
of household FPL do not drive our main results. Remaining threats to our design include
factors coincident with Medicaid expansions that differentially affected poor children (i) born
in different birth month cohorts who reside in the same state at age 15 , or (ii) born in the
same birth month cohort who reside in different states at age 15.
For several reasons, we focus on the reduced form specification given by equation (1)
rather than a traditional instrumental variable (IV) specification that instruments Medicaid
eligibility with simulated eligibility. First, the reduced form is simpler and more transparent.
To estimate the reduced form, we use longitudinal data on state of residence during childhood
to determine simulated Medicaid eligibility. To estimate the IV, we also need longitudinal
data on household FPL to determine endogenous Medicaid eligibility. Second, the reduced
form and IV are quantitatively similar, since the first stage is close to one, as we show in
Table OA.43. Third, a dose-response relationship between childhood poverty and outcomes
should only be visible in the reduced form (the first stage should be close to zero for children
far from poverty, so the IV, which is equal to the reduced form divided by the first stage,
is not well-defined). Although we focus on reduced form estimates, we also report IV and
ordinary least squares (OLS) estimates.
3 Results
3.1 College Enrollment
We measure college enrollment using Form 1098-T, which educational institutions send to
the IRS regardless of whether the enrollee files a return or claims a tax credit. The 1098-T
is used to administer educational incentives such as the American Opportunity Tax Credit
and the Lifetime Learning Credit. From the 1098-T, we derive our main measures of college
enrollment: (i) a contemporaneous measure that indicates whether an individual is currently
enrolled at a given age, and (ii) a cumulative measure that indicates whether an individual
has ever enrolled from age 19 to a given age. We do not consider cumulative years of
enrollment because five years of college is not necessarily better than four. The 1098-T does
not indicate college completion, but it does include a check box for enrollment that is at
least half-time, which we examine as a supplemental outcome. Using the 1098-T, Chetty
et al. (2014, 2016) measure contemporaneous college enrollment as we do. Chetty et al.
(2014) report a correlation greater than 0.95 between enrollment counts using the 1098-T
and a corresponding measure from the Integrated Postsecondary Education Data System
(IPEDS).
10
Figure 2a: Contemporaneous and Cumulative College Enrollment (%)
-10
12
3 C
oeffi
cien
ts (
%)
19 22 25 28
Female
-10
12
3
19 22 25 28Age
Male
-10
12
3
19 22 25 28
All
020
4060
Mea
ns (
%)
19 22 25 28
020
4060
19 22 25 28Age
020
4060
19 22 25 28
Contemporaneous College (Currently Enrolled)
0.5
11.
52
2.5
Coe
ffici
ents
(%
)
19 22 25 28
Female
0.5
11.
52
2.5
19 22 25 28Age
Male0
.51
1.5
22.
5
19 22 25 28
All
020
4060
80M
eans
(%
)
19 22 25 28
020
4060
80
19 22 25 28Age
020
4060
80
19 22 25 28
Cumulative College (Ever Enrolled)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous college enrollment indicates current enrollment in college at a given age, observed through Form1098-T, filed by educational institutions. Cumulative college enrollment indicates ever having enrolled in college by a givenage, starting at age 19. Coefficients for each age are obtained from separate reduced form regressions of college enrollment onsimulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residenceat age 15 (the youngest age at which we observe all individuals in our sample). Standard errors are clustered by state. Dashedlines show 95% confidence intervals. Table OA.1 contains corresponding results.
11
Figure 2a reports contemporaneous results in the top panel and cumulative results in the
bottom panel. Within each panel, the top subfigures plot the coefficient βa from equation
(1), estimated at each age a from 19 to 28. The columns report results within the female,
male, and full samples. The bottom subfigures in each panel plot the mean of the depen-
dent variable within each sample at each age. Table OA.1 in the Online Appendix reports
corresponding values in tabular form. To facilitate comparison across our main outcomes—
college enrollment, fertility, mortality, wage income, earned income tax credit (EITC), and
total taxes—we report contemporaneous results in Table A.1 and cumulative results in Ta-
ble A.2 for ages 19, 22, and 28.
The contemporaneous means in Figure 2a show strong temporal patterns in college en-
rollment; from age 19 to age 28, annual college enrollment falls from 53% to 17%. At every
age, females enroll in college at higher rates than males. The cumulative means show that
81% of women and 70% of men ever enroll by age 28. Despite the differences in means across
genders, the magnitudes of the coefficients are indistinguishable. At age 19, the coefficient
in the full sample indicates that each additional year of Medicaid eligibility increases college
enrollment by 1.69 percentage points on a base of 53%. The results are largest in magni-
tude through age 22. At older ages, as college enrollment decreases, so does the impact of
Medicaid.
The cumulative coefficients show that Medicaid shifts the timing of college enrollment to
younger ages. Additionally, the coefficients suggest that Medicaid inreases college enrollment
in general since the cumulative coefficients remain positive at older ages, though they are not
statistically significant at conventional levels after age 26. By age 28, each additional year
of Medicaid eligibility during childhood increases the probability of having ever enrolled
in college by 0.49 percentage points on a base of 75%. As shown in Figure OA.8 and
Table OA.15, we detect generally positive impacts on the probability of enrolling at least
half-time, with the most statistically significant results from ages 19–22.
To put our estimates in context, Cohodes et al. (2016) find that a 10 percentage point
increase in Medicaid eligibility during childhood decreases the high school dropout rate by
4%, increases college enrollment by 0.5%, and increases college completion by 2.5%. Their
10 percentage point increase in Medicaid eligibility from birth to age 17 translates into
1.8 (=0.1*18) additional years of eligibility. Our cumulative coefficient implies that a 1.8
year increase in Medicaid eligibility during childhood increases the likelihood of having ever
enrolled in college by 1.17% (=0.486*1.8/0.75) at age 28, which is larger than their estimate
for college enrollment but smaller than their estimate for college completion.
3.2 Fertility
We observe fertility if any individual in our sample ever claims a dependent child on a Form
1040. For each dependent child claimed, we use SSA records to obtain the DOB of the child
12
and thereby the age of the parent when the child is born, even if the parent does not claim
the child until a subsequent year.8 Contemporaneous fertility indicates if a first dependent
child is born at a given age, and cumulative fertility indicates if a dependent child is ever
born by a given age. While these measures of fertility depend on filing and claiming behavior,
the vast majority of children are claimed as dependents at some point early in their lives.
Further, claiming a dependent child is interesting in its own right, as it determines EITC
eligibility and reflects the unequal costs of fertility borne by females.
We focus on the first birth since the first child is likely to cause earlier disruptions in
human capital investment and labor force participation, resulting in greater effects on labor
market outcomes later in life. Furthermore, the first birth has a greater impact on EITC
eligibility and benefit levels than subsequent births. To capture first births that occur during
teenage years, we estimate impacts on fertility starting at age 15, the first year that we have
reliable data on Medicaid eligibility and covariates for all individuals in our sample. We
measure Medicaid eligibility through the age of the outcome or through age 18, whichever
is younger. We observe births before age 15, and we incorporate them into our cumulative
outcomes. Therefore, our cumulative outcome at age 19 should capture all births during the
teenage years.
As shown in Figure 2b and in Tables OA.2 and OA.3, our mean fertility outcomes are
larger for women than for men at all ages. By age 28, 51% of women and 36% of men
have dependents that have already been born (our specification includes children claimed as
dependents before, during, or after age 28). There are a variety of reasons why we could
observe larger fertility outcomes for women. For example, women could be more likely
to claim children as single parents, women could have children with older men, and women
could have children with men who also have children with other women. Despite the apparent
differences in means, the coefficients are only slightly larger for women than they are from
men, and the magnitudes are statistically indistinguishable across genders.
The coefficients show that children eligible for Medicaid are less likely to have their first
dependent child in their teenage years. Each additional year of Medicaid eligibility during
childhood decreases the cumulative probability that the first dependent child has been born
by age 19 by 0.35 percentage points on a base of 12.1%. The contemporaneous coefficients
show that Medicaid eligibility has the most pronounced impacts on fertility from ages 18–
21, overlapping with the ages of greatest impact on college enrollment. After age 21, as
individuals who delayed their fertility have their first child, impacts on fertility decrease,
8Chetty et al. (2016) directly observe fertility in the tax data using the Kidlink (DM-2) database fromthe SSA, made available at the IRS. We cannot use this database to measure fertility in our sample becauseit begins in 1983. However, similar to Kidlink (DM-2), our measure uses SSA records linked through thesocial security number (SSN) to determine the time of fertility. It differs from Kidlink (DM-2) only in thatwe establish fertility through claiming behavior over a wide range of filing years.
13
Figure 2b: Contemporaneous and Cumulative Fertility (%)
-.3
-.2
-.1
0.1
Coe
ffici
ents
(%
)
14 16 18 20 22 24 26 28
Female
-.3
-.2
-.1
0.1
14 16 18 20 22 24 26 28Age
Male
-.3
-.2
-.1
0.1
14 16 18 20 22 24 26 28
All
01
23
45
Mea
ns (
%)
14 16 18 20 22 24 26 28
01
23
45
14 16 18 20 22 24 26 28Age
01
23
45
14 16 18 20 22 24 26 28
Contemporaneous Fertility (First Dependent Child Born)
-2-1
.5-1
-.5
0 C
oeffi
cien
ts (
%)
14 16 18 20 22 24 26 28
Female
-2-1
.5-1
-.5
0
14 16 18 20 22 24 26 28Age
Male-2
-1.5
-1-.
50
14 16 18 20 22 24 26 28
All
010
2030
4050
Mea
ns (
%)
14 16 18 20 22 24 26 28
010
2030
4050
14 16 18 20 22 24 26 28Age
010
2030
4050
14 16 18 20 22 24 26 28
Cumulative Fertility (Dependent Child Ever Born)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous fertility indicates if a first dependent child is born at a given age, and cumulative fertility indicates if adependent child is ever born by a given age, starting at age 19. If an individual ever claims a dependent child on a Form 1040,SSA records yield age at birth. Coefficients for each age are obtained from separate reduced form regressions of fertility onsimulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residenceat age 15 (the youngest age at which we observe all individuals in our sample). Standard errors are clustered by state. Dashedlines show 95% confidence intervals. Table OA.3 contains corresponding results.
14
but an absolute decrease is still apparent at age 28. By age 28, a dependent child has been
born to 43% of our sample, and each additional year of Medicaid eligibility during childhood
decreases the probability that the first dependent child has been born by 0.95 percentage
points.
Delays in fertility could serve as a mechanism through which Medicaid affects later-life
economic outcomes. Hotz et al. (2005) and Hotz et al. (1997) find that would-be teen mothers
who have miscarriages have lower annual hours of work and earnings as adults. However,
we generally expect reductions in fertility to improve economic outcomes, since our focus is
broader than teen motherhood and since we see decreases in fertility at ages where also see
increases in college enrollment.
We also see some evidence that Medicaid eligibility decreases marriage. However, we
interpret the results with caution because we only observe marriage contingent on filing a
Form 1040. We present marriage results in Online Appendix 20.
3.3 Mortality
We observe mortality regardless of filing behavior using Social Security Administration (SSA)
death records. We focus on mortality from age 19 to age 28 so that we can assess temporal
patterns in mortality relative to other outcomes, holding the sample constant. Though ex-
amining fertility before age 19 does not require us to change our sample, examining mortality
before age 19 would require us to expand our sample to include children who died during
childhood. As we discuss in Online Appendix 6.2, because we have limited administrative
tax data on children who die at young ages, including them would necessitate changes to our
instrument and specification that would inhibit comparability with our main results. How-
ever, we do observe the Social Security Administration (SSA) date of death for all children
with a social security number (SSN), so we report mean mortality from birth to age 28 in
Figure OA.10 and Table OA.17 to provide context for our results.
As shown in Figure 2c and Table OA.4, 0.07% of our sample dies at age 19, and mortality
generally increases with age through age 28, when 0.09% of our sample dies, but we do not
see strong temporal patterns.9 In contrast, there are strong temporal patterns in mortality
during childhood, as shown in Figure OA.10. Starting at age 12, there is a rapid acceleration
in mortality rates, especially for males, that levels out around age 19. At age 19, the male
mortality rate of 0.10% is more than double the female mortality rate of 0.04%.
The contemporaneous mortality coefficients are generally imprecise, and it is hard to
discern temporal patterns. However, we observe cumulative mortality reductions over adult-
hood that are statistically significant at least at the 10% level from ages 25–28, and at the
9To facilitate comparison with our cumulative mortality results, we include individuals in our estimationsample even if they have died at previous ages. Figure 6.1 and Table OA.16 present comparable results thatexclude individuals who have died in previous years, and the results are extremely similar.
15
Figure 2c: Contemporaneous and Cumulative Mortality (%)
-.02
-.01
0.0
1.0
2 C
oeffi
cien
ts (
%)
19 22 25 28
Female
-.02
-.01
0.0
1.0
2
19 22 25 28Age
Male
-.02
-.01
0.0
1.0
2
19 22 25 28
All
0.0
5.1
.15
Mea
ns (
%)
19 22 25 28
0.0
5.1
.15
19 22 25 28Age
0.0
5.1
.15
19 22 25 28
Contemporaneous Mortality
-.06
-.04
-.02
0.0
2 C
oeffi
cien
ts (
%)
19 22 25 28
Female
-.06
-.04
-.02
0.0
2
19 22 25 28Age
Male-.
06-.
04-.
020
.02
19 22 25 28
All
0.5
11.
5M
eans
(%
)
19 22 25 28
0.5
11.
5
19 22 25 28Age
0.5
11.
5
19 22 25 28
Cumulative Mortality
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous mortality indicates mortality at a given age, measured using SSA death records. Cumulative mortalityindicates mortality by a given age, starting at age 19. Coefficients for each age are obtained from separate reduced formregressions of mortality on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by monthand for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Standard errors areclustered by state. Dashed lines show 95% confidence intervals. Table OA.4 contains corresponding results.
16
5% level from ages 26–27. We focus on the point estimate at age 28 for comparison to other
outcomes. On a base of 81.2 cumulative deaths per 10,000 from ages 19–28, each additional
year of childhood Medicaid eligibility saves 2.0 lives per 10,000 in aggregate, an average of
0.20 lives per 10,000 each year.
The magnitude of our adult mortality estimate is plausible in the context of previous
infant, child, and teen mortality estimates from the Medicaid literature. As shown in Figure
OA.10, infants have relatively high death rates. Currie and Gruber (1996b) find a large
infant mortality impact; an additional year of eligibility at birth saves 30.31 infant lives per
10,000. Considering children, who have lower death rates, Currie and Gruber (1996a) find
that each additional year of Medicaid eligibility during childhood saves 1.28 child lives per
10,000. Considering teens, who have higher death rates, Wherry and Meyer (2016) find that
each additional year of Medicaid eligibility during childhood saves 0.16 teens per 10,000 per
year from ages 15–18. As we show in Section 5.1, even though the absolute number of lives
saved varies across studies, estimates of cost per life saved are similar.
3.4 Wage Income
We measure wage income using Line 1 of Form W-2, summed over all employers in a given
tax year and adjusted to 2011 dollars using the CPI-U. Individuals who do not file Form
W-2 have zero wage income. The frequency of zero contemporaneous wage income ranges
from 12.4% at age 23 to 17.9% at age 28. Chetty et al. (2011) show that wages at age 28
are a good predictor of future wages, which supports our focus on wage income at age 28.
As shown in Figure 2d and Table OA.5, average wage income grows with age, and the
impact of Medicaid on wage income also tends to grow with age. At a few ages, estimates
are statistically significant at the 10% level in the full sample. Females with more years of
Medicaid eligibility during childhood have higher contemporaneous wage income starting at
age 23, and the increases get larger with age. Cumulative impacts on wage income magnify
contemporaneous impacts, gaining magnitude with age. By age 28, each additional year of
childhood Medicaid for females results in $1,784 of cumulative wage income on a base of
$136,600. Male increases are smaller and imprecise. Results presented in Online Appendix
7 show imprecise impacts on log wages and on self-employment.
It is unclear why wage income gains are larger for females. Increases in college enrollment
and decreases in fertility are indistinguishable for females and males. However, it is possible
that these factors have a disproportionate impact on wage income for females, especially
since we start to see gains in wage income around age 23, presumably after graduation from
college.
To put our wage results in the context of a finding from the small existing literature on
long-term wage impacts of interventions during childhood, Chetty et al. (2011) find that a
one standard deviation increase in teacher value-added in a given grade increases earnings
17
Figure 2d: Contemporaneous and Cumulative Wage Income ($000)
-.5
0.5
1 C
oeffi
cien
ts
19 22 25 28
Female
-.5
0.5
1
19 22 25 28Age
Male
-.5
0.5
1
19 22 25 28
All
010
2030
Mea
ns
19 22 25 28
010
2030
19 22 25 28Age
010
2030
19 22 25 28
Contemporaneous Wage Income ($000)
-10
12
3 C
oeffi
cien
ts
19 22 25 28
Female
-10
12
3
19 22 25 28Age
Male-1
01
23
19 22 25 28
All
050
100
150
Mea
ns
19 22 25 28
050
100
150
19 22 25 28Age
050
100
150
19 22 25 28
Cumulative Wage Income ($000)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous wage income indicates wages earned at a given age, obtained from Form W-2, adjusted to 2011dollars and censored at $10 million. Cumulative wage income indicates wage income earned by a given age, starting at age 19.Coefficients for each age are obtained from separate reduced form regressions of wage income on simulated years eligible, ages0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest ageat which we observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidenceintervals. Table OA.5 contains corresponding results.
18
at age 28 by 1.3%. Our estimate is of the same order of magnitude. In the full sample, a
one standard deviation increase in Medicaid eligibility (5.59 years) results in a 6.0% increase
(=(280*5.59)/26,013) in wage income at age 28.
3.5 Earned Income Tax Credit (EITC)
Since the EITC is administered through the tax system, we measure EITC receipt directly
using Form 1040. We examine EITC receipt at the household level, as eligibility and benefit
levels are determined at that level. EITC receipt is zero for a large fraction of the sample,
so we examine EITC participation as a supplemental outcome. Although EITC generosity
expanded during the period of study, we do not adjust our estimates because actual EITC
receipts are relevant for the fiscal return to Medicaid spending.
The coefficients shown in Figure 2e and Table OA.6 show that individuals with greater
Medicaid eligibility during childhood collect less from the EITC at all ages from 19–22, and
the decreases generally get more pronounced over time. Cumulatively by age 28, for each
additional year of Medicaid eligibility during childhood, adults collect $182 less on a base
of $3,044. In addition to reducing EITC benefits, Table OA.20 shows that each additional
year of Medicaid eligibility reduces the probability of EITC participation from ages 19–28
by 0.69 percentage points on a base of 47.5%. These decreases are particularly notable given
that EITC benefits tend to grow with age within our data.
The effect of Medicaid eligibility on EITC receipts is approximately twice as large for
women, and the 95% confidence intervals for women and men shown in Figures 2e and OA.13
often do not overlap. EITC eligibility does not explicitly depend on gender—it only depends
on income, number of children, and marital status. Therefore, our wage income, fertility,
and marital status results can shed light on mechanisms through which Medicaid can affect
EITC receipt. Of those potential mechanisms, our results suggest that Medicaid likely affects
EITC through increases in wage income, which are pronounced for women but minimal and
imprecise for men.
3.6 Total Taxes
Our administrative tax data are especially well-suited to the examination of tax payments.
Tax payments are relevant for the fiscal return to Medicaid spending, and they are also
relevant as a summary measure that reflects the other five main outcomes (college enrollment,
fertility, mortality, wage income, and EITC). We construct a measure of total federal income
and payroll taxes at the household level. We start with tax payments reported on Form
1040 for the household, from which we deduct refundable tax credits—such as the Earned
Income Tax Credit (EITC), the Additional Child Tax Credit, and credits refundable through
the American Opportunity Tax Credit. Next, for each individual in the household, we add
payroll tax payments reported by employers on Form W-2 and by the self-employed on
19
Figure 2e: Contemporaneous and Cumulative EITC ($000)
-.06
-.04
-.02
0 C
oeffi
cien
ts
19 22 25 28
Female
-.06
-.04
-.02
0
19 22 25 28Age
Male
-.06
-.04
-.02
0
19 22 25 28
All
0.2
.4.6
.8M
eans
19 22 25 28
0.2
.4.6
.8
19 22 25 28Age
0.2
.4.6
.8
19 22 25 28
Contemporaneous EITC ($000)
-.3
-.2
-.1
0 C
oeffi
cien
ts
19 22 25 28
Female
-.3
-.2
-.1
0
19 22 25 28Age
Male-.
3-.
2-.
10
19 22 25 28
All
01
23
4M
eans
19 22 25 28
01
23
4
19 22 25 28Age
01
23
4
19 22 25 28
Cumulative EITC ($000)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous EITC indicates EITC earned at a given age, obtained from Form 1040, adjusted to 2011 dollars.Cumulative EITC indicates EITC earned by a given age, starting at age 19. Coefficients for each age are obtained fromseparate reduced form regressions of EITC on simulated years eligible, ages 0–18. The specification includes fixed effects forbirth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Table OA.6 contains corresponding results.
20
Schedule SE. We adjust total taxes to 2011 dollars using the CPI-U.
The results in Figure 2f and Table OA.7 show that the positive impact of Medicaid on
total taxes increase with age. Cumulatively by age 28, each additional year of Medicaid
eligibility during childhood increases total taxes by $533 on a base of $20,623. Therefore,
a one standard deviation increase in Medicaid eligibility during childhood (5.61 years) in-
creases total taxes by $2,990 (=533*5.61), a 14.5% increase (=2,990/20,623). Cumulative
coefficients are significant at the 5% level at ages 19–22 and the 1% level at ages 23–28.
Female coefficients are slightly larger and more precise than male coefficients.
A natural question is how the increase in total taxes relates to our findings of an increase in
wage income and a decrease in EITC receipts. More broadly, we are interested in how much of
the increase in total taxes stems from changes in payments to vs. from the government. It is
hard to separate these factors from a causal perspective because income affects EITC receipts,
but we can separate them from an accounting perspective. We decompose total taxes into
three components: EITC, payroll taxes (a transformation of wage income), and income taxes
plus EITC (gross income taxes). Total taxes are equal to payroll taxes plus gross income
taxes minus EITC. We perform the decomposition in this way so that the EITC results
have the same sign in the main results, even though EITC receipts enter negatively into the
government budget. Online Appendix 9 presents figures that examine each component of
total taxes as separate outcomes in equation (1), as well as tables that also report the percent
change in total taxes due to each component. As shown in Table OA.22, at age 19, each
additional year of Medicaid eligibility during childhood decreases EITC by $5 and increases
total taxes by $12. Therefore, 42% (=-(-5)/12) of the change in cumulative total taxes is due
to a decrease in EITC. By similar calculations, the increase in payroll taxes explains 25%,
and the increase in gross income taxes explains the remaining 33%. Further into adulthood,
the absolute impact of each component on total taxes grows, but the decomposition shows
that the relative impact changes—the role of EITC decreases dramatically and the role of
income taxes increases dramatically. At age 28, 24% of the $88 increase in contemporaneous
total taxes is due to a decrease in EITC and 83% is due to an increase in gross income taxes.
4 Heterogeneity and Robustness
4.1 Heterogeneous Effects by Childhood Household FPL:
Dose-Response Exercise
Medicaid is targeted at the poor. Therefore, we should see the greatest impact of Medicaid on
individuals who lived in the poorest households during childhood. We examine the reduced
form impact of simulated Medicaid eligibility on our main outcomes in three samples: a “high
impact” sample of children whose families were below 200% of the Federal Poverty Level
(FPL) in every year of our longitudinal data during childhood, an “intermediate impact”
21
Figure 2f: Contemporaneous and Cumulative Total Taxes ($000)
-.05
0.0
5.1
.15
.2 C
oeffi
cien
ts
19 22 25 28
Female
-.05
0.0
5.1
.15
.2
19 22 25 28Age
Male
-.05
0.0
5.1
.15
.2
19 22 25 28
All
01
23
4M
eans
19 22 25 28
01
23
4
19 22 25 28Age
01
23
4
19 22 25 28
Contemporaneous Total Taxes ($000)
0.2
.4.6
.81
Coe
ffici
ents
19 22 25 28
Female
0.2
.4.6
.81
19 22 25 28Age
Male0
.2.4
.6.8
1
19 22 25 28
All
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
Cumulative Total Taxes ($000)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous total taxes indicate taxes paid at a given age, defined as household federal tax payments plus individualpayroll tax payments less EITC, adjusted to 2011 dollars. Cumulative total taxes indicate taxes paid by a given age, startingat age 19. Coefficients for each age are obtained from separate reduced form regressions of total taxes on simulated yearseligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (theyoungest age at which we observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95%confidence intervals. Table OA.7 contains corresponding results.
22
sample between 200% and 500% FPL, and a “low impact” sample greater than 500% FPL.
We exclude 32.2% of the sample belonging to multiple FPL categories in the longitudinal
data. Because children are often born poor, and their household income increases over time,
we cannot be sure that children in our “low impact” sample had no exposure to Medicaid
during their childhoods before our sample begins in 1996, but we expect that there should
be a dose-response relationship whereby individuals with lower observed household FPL as
children should experience greater benefits from Medicaid. Boudreaux et al. (2016) and
Hoynes et al. (2012) also stratify their samples to examine dose-response relationships in
their settings. In our setting, to the extent that we see a dose-response relationship, we can
rule out the impact of policies or economic changes coincident with Medicaid expansions
that affected all children born in the same month who resided in the same state at age 15 in
the same way regardless of household FPL.
We see a general dose-response relationship for total taxes in Figure 3 and Table OA.30,
and for all other main outcomes in Online Appendix 10.10 For each additional year of
Medicaid eligibility during childhood, cumulative total taxes by age 28 increase by $1,779
in the high impact sample, $1,253 in the intermediate impact sample, and $656 in the low
impact sample. The dose-response relationship in the coefficients is especially striking given
that the means show the opposite relationship, consistent with inter-generational persistence
in household FPL absent Medicaid eligibility.
4.2 Heterogeneous Distributional Effects Within the High Impact Sample
To examine the impact of Medicaid on upward mobility, we focus on the high impact sample
of children with low household FPL during childhood. On this sample, we estimate versions
of equation (1) with outcomes representing the quartiles of the distribution of total taxes
and wage income in the full sample. The means in Table OA.32 show that 17% of children
from below 200% of the FPL end up in the top quartile of the distribution of cumulative
total taxes at age 28. For comparison, if there were no inter-generational persistence, 25% of
children would end up in the top quartile.11 The coefficients increase as the quartiles increase,
suggesting that Medicaid eligibility induces upward mobility among some children in the high
impact sample. The coefficients in Table OA.32 show that an additional year of Medicaid
eligibility during childhood increases the probability of being in the highest quartile of total
taxes by age 28 by 1.6 percentage points. Therefore, a one standard deviation increase
in Medicaid eligibility (5.61 years) closes the gap between the underlying rate of inter-
10In Online Appendix 10.7, we examine heterogeneous impacts of Medicaid using filing status as a proxyfor whether children resided in one vs. two parent households. This exercise is directly related to our dose-response exercise insofar as household FPL is higher for children whose parents file jointly. The results tella similar story.
11For another comparison, Chetty et al. (2014), who find a 7.5% probability that a child from the bottomquintile of the income distribution will end up in the top quintile.
23
Figure 3: Cumulative Total Taxes ($000) by Family FPL at Ages 15–18
0.5
11.
52
Coe
ffici
ents
19 22 25 28
Female
0.5
11.
52
19 22 25 28Age
Male
0.5
11.
52
19 22 25 28
All
<200% FPL 200% - 500% FPL >500% FPL
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
010
2030
40M
eans
19 22 25 28
010
2030
40
19 22 25 28Age
010
2030
40
19 22 25 28
<200% FPL 200% - 500% FPL >500% FPL
Cumulative Total Taxes ($000)
Note. Cumulative total taxes indicate taxes paid by a given age starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients for each age are obtained from separatereduced form regressions of total taxes on simulated years eligible, ages 0–18. Children are assigned to an % FPL bin if theirhousehold remained in that bin at every age from 15–18. We exclude children with heterogeneity in their observed % FPL bin(32.2% of the sample). The specification includes fixed effects for birth cohort by month and for state of residence at age 15(the youngest age at which we observe all individuals in our sample). Standard errors are clustered by state. Table OA.30contains corresponding results.
generational persistence and zero inter-generational persistence ((0.766*5.61)/(25-16.635)).
The wage income results tell a similar story.
4.3 Heterogeneous Effects of Medicaid Eligibility at Different Ages
Examining which periods of childhood Medicaid eligibility drive our results, we find that
Medicaid eligibility from ages 15 to 18 results in the largest increase in cumulative total taxes
starting at age 22.12 Though eligibility during teenage years seems to drive our results, we
also find positive though imprecise results for Medicaid eligibility from ages 0–3 starting after
age 25. These results align with results from the literature that emphasize the importance of
intervening early in childhood and results from Cohodes et al. (2016) that find that Medicaid
eligibility during teenage years has the most important impact on college completion. We
interpret our result with caution because eligibility in any of the age bins could be collinear
12We divide Medicaid eligibility into four ranges—ages 0–3, 4–7, 8–14, and 15–18. We then estimateequation (1), replacing simulated Medicaid eligibility from birth to age 18 with a vector of simulated Medicaideligibilities for each age range. We present the results in Online Appendix 12.
24
with eligibility at other ages. Furthermore, ages 15–18 are the only ages at which we observe
longitudinal data on all children in our sample.
4.4 Robustness to Gender as an Outcome: Falsification Exercise
As a falsification exercise, we estimate our main specification using gender as an outcome
and present the results in Online Appendix 13. We do not expect an impact of simulated
Medicaid eligibility on gender, which is fixed across time for each individual in our data. The
estimated coefficient is not statistically different from zero, and the standard error is small
enough to rule out meaningful changes in gender, which lends credibility to our specification.
4.5 Robustness to Assumptions in Early Childhood
Because our data do not begin until 1996, we make assumptions about household FPL and
state of residence in early childhood; we impute household FPL using household FPL in the
year of parent-child linkage, and we assume that the child resides in the first observed state
of residence. We are not particularly concerned about the imputation of household FPL
before the tax data begin because we focus on reduced form estimates, which do not rely on
variation in simulated Medicaid eligibility. We construct simulated eligibility by running a
nationally-representative sample through our Medicaid calculator, so measurement error that
results from holding FPL constant in years before the tax data began should be addressed
by cohort fixed effects. However, to be sure that national trends in household FPL that
occurred before our tax data begin do not drive our results, we construct simulated Medicaid
eligibility in the CPS using a different national sample in each year. We estimate reduced
form specifications following equation (1) with simulated eligibility from the CPS in lieu
of simulated eligibility from the tax data, assigning longitudinal state of residence during
childhood from the tax data. We report the results in Figure OA.26 and Table OA.35. We
also report results for ages 19, 22, and 18 in Table A.3, which facilitates comparisons across
several robustness exercises and our main results. As shown, results that use the CPS to
simulate Medicaid eligibility are very similar to our main results, suggesting that our tax
data are broadly representative compared to the nationally representative CPS and that the
inability to observe longitudinal household FPL in the tax data before 1996 does not drive
our results.
To address our inability to observe state of residence before the tax data begins, we
examine how important interstate moves that we can observe during childhood are to our
results. Figure OA.27 presents results in which we separately examine results for children
who reside in one state from ages 15–18 and results for children who reside in multiple. The
estimates that do not exploit variation from the state vector are similar to the results that
do, although the coefficients are less precise and smaller in magnitude.
We also implement two exercises that use sibling variation in Medicaid eligibility to
25
control for potential unobserved characteristics across households, where one potential un-
observed characteristic is household state of residence before the tax data begin.13 The first
exercise controls for the sibling’s tax outcome. As shown in Figure OA.28, this exercise gen-
erates estimates that are very similar to those from our main specification. The estimates
are slightly attenuated, which we expect due to Medicaid eligibility being correlated across
siblings, such that controlling for the sibling’s outcome is conceptually similar to controlling
for a lagged dependent variable. The second exercise, which is more restrictive than the
sibling control approach, incorporates family fixed effects. These estimates, presented in
Figure OA.28, are attenuated further and are no longer statistically significant, but they
remain positive and display a similar age profile as our main results. It should be noted
that the identifying variation remaining in this specification is low, and the 95% confidence
intervals contain our main coefficients at each age in adulthood. The attenuation is also
consistent with parental investments that compensate for differences in Medicaid eligibility
across children, which amounts to a treatment spillover that would bias our coefficients to
zero.
4.6 Robustness to Sample Selection
To assess how the filing sample restriction affects our results, we examine robustness to
including children whose parents claim them in 1997 but do not file in every year from 1996
through age 18. In our expanded sample that includes non-filers, we impute income and state
of residence using the nearest filing year. Figure OA.30 and Table OA.37 compare results
from our main sample to results from the expanded sample. Average cumulative total taxes
by age 28 are nearly indistinguishable for the children in our sample, regardless of whether
their parents filed in each year.
4.7 Robustness to OLS, IV, and Income Controls
We compare reduced form, OLS and IV specifications with and without income controls in
Figure OA.31 and Table OA.38.14 We do not control for household income in equation (1)
because household income at age 15, the earliest age we observe it for all children, could
reflect Medicaid eligibility at earlier ages. However, we examine robustness to the inclusion
of income controls. OLS estimates without income controls show that individuals with
13We perform these exercises in the subsample of households with two children born in our samplingwindow from 1981 to 1984, and we pool across genders to allow for comparison of siblings of different genders.As shown in Figure OA.29, the effect of Medicaid eligibility on cumulative taxes paid is consistent acrossone-child households (N=7,002,034) and two-children households (N=2,526,911). The estimates attenuateto zero for households with three or more children (N=208,035), potentially due to the small sample sizeand to the unobserved characteristics of households who had three-or-more children in our short four-yearsampling window. We therefore focus on the sample of two-children households, which makes controlling forsibling outcomes easier and the identification of our specifications more transparent.
14We present tables and figures that report IV results with income controls for all of our main outcomesin Online Appendices 3 and 4.
26
greater Medicaid eligibility during childhood have lower cumulative total taxes in adulthood,
which is to be expected because Medicaid is targeted at the poor. Controlling for income
attenuates the OLS estimates, but they remain negative. In contrast, IV and reduced form
estimates show positive impacts of Medicaid eligibility on cumulative total taxes in adulthood
regardless of income controls. The inclusion of income controls attenuates the reduced form
estimate of the impact of an additional year of Medicaid eligibility on cumulative total taxes
by age 28 from $533 to $326 and the IV estimate from $568 to $303. This attenuation is to
be expected if household income reflects Medicaid eligibility at earlier ages.15
5 Medicaid Takeup, Spending, and Fiscal Return on Investment
5.1 Medicaid Takeup and Spending
We supplement the tax data with administrative data on Medicaid takeup and spending
obtained from the Medicaid Statistical Information System (MSIS). Because our MSIS data
are aggregated over all children under twenty-one at the state-by-year level, we incorporate
additional data and assumptions to further disaggregate the data by age.16 For each in-
dividual in our tax data, we assign cumulative measures of Medicaid takeup and spending
from birth to age 18 as outcomes in our main IV specification. We focus on IV rather than
reduced form estimates because we want to ensure the highest degree of accuracy when we
compare our coefficients for Medicaid spending and total taxes.
Column 1 of Table 1 shows that each additional year of Medicaid eligibility during child-
hood increases Medicaid takeup by almost seven months (0.59 years) on a base of almost
three years. The implied 59% takeup per year of eligibility is higher than almost all of the
estimates from the literature discussed in Section 1, which generally range from 5 to 24
percent. However, studies that use different sources of variation and different covariates will
find different estimates if there is heterogeneity in takeup rates. Card and Shore-Sheppard
(2004) even find different takeup rates for the two expansions that they examine within the
same study. Furthermore, our takeup estimate differs from those in the literature because
we consider aggregate takeup over childhood, rather than contemporaneous takeup.
We do our best to identify takeup using the same variation that we use to identify
our other outcomes because heterogeneity in takeup is likely related to heterogeneity in
other outcomes. By scaling estimates for other outcomes by similarly obtained estimates of
15The inclusion of richer income controls in Table OA.39 further attenuates the reduced form estimatefrom $325 to $286. The inclusion of richer income controls is so computationally intensive that we onlyprovide reduced form estimates for cumulative total taxes at age 28.
16To disaggregate the MSIS data, we apply our calculator to the Current Population Survey (CPS) todetermine the share of children eligible for Medicaid by year, state, and age. We apply these shares tointercensal population estimates by year, state, and birth year to obtain the population of eligibles by year,state, and age. We allocate takeup and spending in proportion to eligibility. Finally, we adjust spending to2011 dollars using the CPI-U.
27
takeup, we can assess the impact of enrollment rather than eligibility, assuming that impacts
of Medicaid are zero for those who are not enrolled. For example, using our IV coefficient for
total taxes, we find that each additional year of Medicaid enrollment from birth to age 18
increases cumulative total tax payments by age 28 by $963 (=568/0.59). If we had simply
scaled by a takeup estimate in the literature instead of estimating takeup using the same
variation, we would have obtained a much larger enrollment impact (through division by a
smaller number).
Table 1: Takeup, Spending, Taxes, and Fiscal Return on Investment (ROI)
(1) (2) (3) (4)Years ofMedicaidTakeup,Age 0-18
Medicaid Spending($000),
Age 0-18
Cumulative Total Taxes
($000),Age 19-28
Fiscal ROIby Age 28
= (3)/(2) - 100%
Discount rate = 0%0.591*** 0.636*** 0.568** -10.69%(0.037) (0.059) (0.221)
Mean 2.894 1.804 20.623
Discount rate = 1%0.558*** 0.430** -22.94%(0.051) (0.167)
Mean 1.584 15.609
Discount rate = 2%0.491*** 0.326** -33.60%(0.045) (0.127)
Mean 1.396 11.846
Discount rate = 3%0.433*** 0.248** -42.73%(0.040) (0.096)
Mean 1.234 9.014
Observations 9,876,591 9,876,591 10,045,162
Years Eligible, Age 0-18
Years Eligible, Age 0-18
Years Eligible, Age 0-18
Years Eligible, Age 0-18
-
-
-
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative Medicaidtakeup and spending for ages 0–18 are estimated in the full sample using administrative data from the Medicaid StatisticalInformation System (MSIS), adjusted to 2011 dollars. Cumulative total taxes indicate taxes paid in the full sample from ages19–28, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars.Coefficients are obtained from an IV regression of the given outcome on years eligible, ages 0–18. The specification includesfixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individualsin our sample).
Column 2 of Table 1 shows that Medicaid spending during childhood increased by $636
on a base of $1,804 for each year of eligibility. The comparison of spending and takeup
means implies that each year of enrollment costs $623 (=1,804/2.894) on average, and the
comparison of spending and takeup coefficients shows that each additional year of enrollment
28
costs $1,078 (=636/0.59). Therefore, the additional children who enroll due to the expansions
that we study cost more to cover than the previously enrolled children.
We can also compare the impact on Medicaid spending with the impact on another
outcome to obtain the cost of achieving that outcome through Medicaid, assuming that no
benefits accrue through other outcomes. For example, the IV estimate in Table OA.11 shows
that each year of Medicaid eligibility during childhood saves 2.1 lives per 10,000 (0.021 per-
centage points) from ages 19–28. Therefore, the cost per life saved through expanded child-
hood Medicaid eligibility is approximately $3.0 million (=636/0.021%), which is at the lower
bound of the traditional $3–7 million value of a statistical life (Cutler, 2005). Our estimate
for cost per life saved is similar to estimates from the Medicaid literature.17 However, as
we have shown, decreased mortality is not the only benefit of childhood Medicaid, so the
effective cost of saving these lives is likely much lower.
5.2 Fiscal Return on Investment
Increased tax revenue lowers the effective cost of childhood Medicaid. Our IV estimates
show that each additional year of Medicaid eligibility during childhood costs $636 and yields
$568 in future tax revenue by age 28, suggesting that the government recoups 0.89 cents on
each dollar spent on childhood Medicaid by age 28. However, to take into account that the
spending occurs well before the tax payments, we discount both to birth at 1%, 2%, and 3%
rates in the data before estimating the IV results presented in Table 1.18 At a 3% discount
rate, each additional year of Medicaid eligibility increases spending by $433 and taxes by
$248. The ratio of $248 to $433 implies that the government recoups 57 cents of each dollar
it spends on childhood Medicaid by age 28. Therefore, the fiscal return on investment in
childhood Medicaid is -43% (=0.57-1) by age 28. Forecasts in Online Appendix 18 indicate
that Medicaid pays for itself by age 32 and delivers positive fiscal returns thereafter.
The actual return to Medicaid is likely much larger. From the perspective of the federal
government, the fiscal return is larger because approximately 50% of Medicaid spending
was done by states in the period under consideration (Centers for Medicare & Medicaid
Services, 2015). The actual return is also larger if we consider benefits that accrue to the
children themselves. For example, if we add an implied value of life saved to the fiscal return,
17Currie and Gruber (1996b) report a $840,000 (in 1986 dollars, $1.7 million in 2011 dollars) cost per lifesaved through targeted eligibility changes but a much higher $4.2 million (in 1986 dollars, $8.6 million in2011 dollars) cost per life saved through broad eligibility changes. Currie and Gruber (1996a) report a costper life saved of $1.61 million (in 1992 dollars, $2.58 million in 2011 dollars). Similarly, Wherry and Meyer(2016) report a $1.77 million (in 2011 dollars) cost per life saved, and Goodman-Bacon (2018) report a costper life saved of $1.83 million (in 2012 dollars, $1.79 million in 2011 dollars).
18The Office of Management and Budget recommends a real discount rate of 0.8% for cost-effectivenessprojects of a 30-year duration (US Office of Management & Budget, 2016), which is within the range of our0% and 1% discount rates. The Department of Commerce recommends a 3% real discount rate for use inlife-cycle projects (Lavappa and Kneifel, 2016). We prefer 3% because it is the most conservative.
29
Medicaid delivers benefits equal to three times its costs by age 28.19
6 Conclusion
Looking forward to future decisions regarding whether to expand Medicaid, our research
shows that Medicaid generally has favorable long-term impacts on children. Using adminis-
trative data from the IRS, we see that children with greater exposure to Medicaid enroll in
college at higher rates, delay their fertility, and have lower rates of adult mortality. Females
have higher wage income, and both genders collect less from the earned income tax credit.
Moreover, the government recoups much of its investment in childhood Medicaid over time
in the form of higher future tax payments.
References
Baicker, K., A. Finkelstein, J. Song, and S. Taubman (2014). The impact of medicaid
on labor market activity and program participation: Evidence from the oregon health
insurance experiment. American Economic Review 104 (5), 322–28.
Baicker, K., S. L. Taubman, H. L. Allen, M. Bernstein, J. H. Gruber, J. P. Newhouse, E. C.
Schneider, B. J. Wright, A. M. Zaslavsky, and A. N. Finkelstein (2013). The oregon experi-
ment?effects of medicaid on clinical outcomes. New England Journal of Medicine 368 (18),
1713–1722.
Baird, S., J. Hamory Hicks, M. Kremer, and E. Miguel (2016). Worms at work: Long-run
impacts of a child health investment. The Quarterly Journal of Economics .
Bansak, C. and S. Raphael (2006). The effect of state policy design features on take up
and crowd out rates for the state children’s health insurance program. Journal of Policy
Analysis and Management 26 (1), 149–175.
Blank, R. M., C. C. George, and R. A. London (1996). State abortion rates: The impact of
policies, providers, politics, demographics, and economic environment. Journal of Health
Economics 15, 513–553.
Blumberg, L. J., L. Dubay, and S. A. Norton (2000). Did the medicaid expansions for
children displace private insurance? an analysis using the SIPP. Journal of Health Eco-
nomics 19 (1), 33 – 60.
19Using a conservative $3 million dollar value of a statistical life from Cutler (2005) and our IV mortalityresult by age 28, we estimate that the value of life saved by each additional year of Medicaid eligibilityduring childhood is $630 (=0.021%*$3 million). Combining this estimate with our comparable tax revenueand spending IV estimates, the benefits ($568+$630) are roughly double the cost ($636), implying an ROIfrom increased tax revenue and decreased mortality by age 28 of 88% (=(568 + 630 - 636)/636).
30
Boudreaux, M. H., E. Golberstein, and D. D. McAlpine (2016). The long-term impacts of
medicaid exposure in early childhood: Evidence from the program’s origin. Journal of
health economics 45, 161–175.
Buchmueller, T. C., L. S. A. T., and W. K. N. (2008). How did SCHIP affect the insurance
coverage of immigrant children? The B.E. Journal of Economic Analysis & Policy 8 (2),
1–25.
Card, D. and L. D. Shore-Sheppard (2004). Using discontinuous eligibility rules to identify
the effects of the federal medicaid expansions on low-income children. The Review of
Economics and Statistics 86 (3), 752–766.
Centers for Medicare & Medicaid Services (2015). NHE fact sheet. 28.
Chetty, R., J. N. Friedman, N. Hilger, E. Saez, D. W. Schazenbach, and D. Yagan (2011).
How does your kindergarten classroom affect your earnings? evidence from project star.
Quarterly Journal of Economics 126 (4), 1593–1660.
Chetty, R., J. N. Friedman, and J. E. Rockoff (2014). Measuring the impacts of teachers
ii: Teacher value-added and student outcomes in adulthood. The American Economic
Review 104 (9), 2633–2679.
Chetty, R., J. N. Friedman, and E. Saez (2013). Using differences in knowledge across
neighborhoods to uncover the impacts of the eitc on earnings. American Economic Re-
view 103 (7), 2683–2721.
Chetty, R., N. Hendren, and L. F. Katz (2016). The effects of exposure to better neigh-
borhoods on children: New evidence from the moving to opportunity experiment. The
American Economic Review 106 (4), 855–902.
Chetty, R., N. Hendren, P. Kline, and E. Saez (2014). Where is the land of Opportunity?
The Geography of Intergenerational Mobility in the United States. The Quarterly Journal
of Economics 129 (4), 1553–1623.
Cohodes, S. R., D. S. Grossman, S. A. Kleiner, and M. F. Lovenheim (2016). The effect
of child health insurance access on schooling: Evidence from public insurance expansions.
Journal of Human Resources 51 (3), 727–759.
Cunningham, P. J., J. Hadley, and J. Reschovsky (2002). The effects of SCHIP on children’s
health insurance coverage: Early evidence from the community tracking study. Medical
Care Research and Review 59 (4), 359–383.
31
Cunningham, P. J., J. D. Reschovsky, and J. Hadley (2002). SCHIP, medicaid expan-
sions lead to shifts in children’s coverage. Issue brief (Center for Studying Health System
Change) (59), 1–6.
Currie, J., S. Decker, and W. Lin (2008). Has public health insurance for older children
reduced disparities in access to care and health outcomes? Journal of health Eco-
nomics 27 (6), 1567–1581.
Currie, J. and J. Gruber (1996a). Health insurance eligibility, utilization of medical care,
and child health. The Quarterly Journal of Economics 111 (2), 431–466.
Currie, J. and J. Gruber (1996b). Saving babies: The efficacy and cost of recent expansions of
medicaid eligibility for pregnant women. Journal of Political Economy 104 (6), 1263–1296.
Cutler, D. (2005). Your Money Or Your Life: Strong Medicine for America’s Health Care
System. Oxford University Press.
Cutler, D. M. and J. Gruber (1996). Does public insurance crowd out private insurance?.
Quarterly Journal of Economics 111 (2), 391 – 430.
Deshpande, M. (2016, November). Does welfare inhibit success? the long-term effects of
removing low-income youth from the disability rolls. American Economic Review 106 (11),
3300–3330.
Finkelstein, A. F., S. Taubman, B. J. Wright, M. Bernstein, J. Gruber, J. P. Newhouse,
H. L. Allen, K. Baicker, and the Oregon Health Study Group (2012). The oregon health
insurance experiment: Evidence from the first year. The Quarterly Journal of Eco-
nomics 127 (3), 1057–1106.
Finkelstein, A. N., S. L. Taubman, H. L. Allen, B. J. Wright, and K. Baicker (2016). Effect of
medicaid coverage on ed use — further evidence from oregon’s experiment. New England
Journal of Medicine 375 (16), 1505–1507. PMID: 27797307.
Goodman-Bacon, A. (2018). Public insurance and mortality: evidence from medicaid im-
plementation. Journal of Political Economy 126 (1), 216–262.
Gruber, J. and K. Simon (2008). Crowd-out ten years later: Have recent expansions of
public insurance crowded out private health insurance? Journal of Health Economics 27,
201–217.
Gruber, J. and A. Yelowitz (1999). Public health insurance and private savings. Journal of
Political Economy 107 (6), 1249–1274.
32
Ham, J. C. and L. Shore-Sheppard (2005). The effect of medicaid expansions for low-income
children on medicaid participation and private insurance coverage: evidence from the
SIPP. Journal of Public Economics 89, 57–83.
Heim, B., I. Lurie, and K. I. Simon (2017, January). The impact of the affordable care act
young adult provision on childbearing, marriage, and tax filing behavior: Evidence from
tax data. NBER Working Paper 23092 (23092).
Helmchen, L. A., D. W. Brown, I. Z. Lurie, and A. T. L. Sasso (2015). Health savings
accounts: growth concentrated among high-income households and large employers. Health
Affairs 34 (9), 1594–1598.
Hotz, V. J., S. W. McElroy, and S. G. Sanders (2005). Teenage childbearing and its life cycle
consequences: Exploiting a natural experiment. Journal of Human Resources XL(3), 683–
715.
Hotz, V. J., C. H. Mullin, and S. G. Sanders (1997). Bounding causal effects using data
from a contaminated natural experiment: Analyzing the effects of teenage childbearing.
The Review of Economic Studies 6 (4), 575–603.
Hoynes, H., D. W. Schanzenbach, and D. Almond (2016). Long-run impacts of childhood
access to the safety net. The American Economic Review 106 (4), 903–934.
Hoynes, H. W., D. W. Schazenback, and D. Almond (2012). Long run impacts of childhood
access to the safety net. NBER Working Paper 18535 .
Hudson, J. L., T. M. Selden, and J. S. Banthin (2005). The impact of SCHIP on insurance
coverage of children. Inquiry 42 (3), 232–254.
Joyce, T. and A. Racine (2003). Chip shots: Association between the state children’s health
insurance programs and immunization coverage and delivery. NBER Working Paper 9831 .
Lavappa, P. D. and J. D. Kneifel (2016). Energy price indices and discount factors for
life-cycle cost analysis–2016.
Levine, P. B. and D. Schanzenbach (2009). The impact of children’s public health insurance
expansions on educational outcomes. Forum for Health Economics & Policy 12 (1), Article
1.
Lindrooth, R. C. and J. S. McCullough (2007). The effect of medicaid family planning
expansions on unplanned births. Women’s Health Issues 17, 66–74.
33
Lo Sasso, A. T. and T. C. Buchmueller (2004). The effect of the state children’s health
insurance program on health insurance coverage. Journal of Health Economics 23 (5),
1059–1082.
Lurie, I. Z. (2009). Differential effect of the state children’s health insurance program ex-
pansions by children’s age. Health Services Research 44 (5p1), 1504–1520.
Miller, S. and L. R. Wherry (2016). The long-term health effects of early life medicaid
coverage. Available at SSRN: https://ssrn.com/abstract=2466691.
Rosenbach, M., M. Ellwood, J. Czajka, C. Irvin, W. Coupe, and B. Quinn (2001). Insurance
program: Momentum is increasing after a modest start, first annual report.
Sommers, B. D., K. Baicker, and A. M. Epstein (2012). Mortality and access to care among
adults after state medicaid expansions. New England Journal of Medicine 367 (11), 1025–
1034.
Taubman, S. L., H. L. Allen, B. J. Wright, K. Baicker, and A. N. Finkelstein (2014). Medicaid
increases emergency-department use: Evidence from oregon’s health insurance experiment.
Science 343 (6168), 263–268.
US Office of Management & Budget (2016). OMB Circular A-94, Appendix C.
Wherry, L. R. and B. D. Meyer (2016). Saving teens: Using a policy discontinuity to estimate
the effects of medicaid eligibility. Journal of Human Resources 51 (3), 556 – 588.
Wherry, L. R., S. Miller, R. Kaestner, and B. D. Meyer (2015). Childhood medicaid coverage
and later life health care utilization. Review of Economics and Statistics (0).
Yagan, D. (2016). Is the great recession really over? longitudinal evidence of enduring
employment impacts. Working Paper .
Yelowitz, A. S. (1998). Will extending medicaid to two-parent families encourage marriage?
The Journal of Human Resources 33 (4), pp. 833–865.
Zuckerman, S. and A. W. Lutzky (2001). Medicaid demonstration project in los angeles
county, 1995-2000 progress but room for improvement.
34
Appendix A Main Results Tables, Selected Ages
Table A.1: Contemporaneous Outcomes at Age 19, 22, and 28
Female Male All Female Male All Female Male All
College (Currently Enrolled; %)1.750*** 1.637*** 1.690*** 0.718 0.646* 0.678* -0.026 -0.092 -0.062(0.539) (0.568) (0.549) (0.435) (0.342) (0.384) (0.157) (0.154) (0.143)
Mean 57.617 47.684 52.542 50.040 40.454 45.143 20.062 14.461 17.201
Fertility (First Had Dependent Child; %)-0.119** -0.051 -0.085* -0.088 -0.042 -0.065 -0.063 -0.072** -0.068*(-0.057) (-0.042) (0.047) (0.054) (0.048) (0.045) (0.050) (0.029) (0.034)
Mean 4.848 2.488 3.642 3.971 3.077 3.514 3.294 2.852 3.068
Mortality (%)-0.003 -0.001 -0.002 -0.005** 0.006 0.000 0.006* -0.009 -0.001(0.003) (0.004) (0.003) (0.002) (0.005) (0.003) (0.003) (0.006) (0.004)
Mean 0.037 0.098 0.068 0.040 0.125 0.084 0.051 0.121 0.087
Wage Income ($000)0.059* 0.061 0.061* 0.077 -0.045 0.015 0.414*** 0.149 0.280*(0.031) (0.041) (0.033) (0.061) (0.075) (0.064) (0.148) (0.183) (0.150)
Mean 4.198 4.864 4.538 8.729 10.461 9.614 23.336 28.577 26.013
EITC ($000)-0.006*** -0.003*** -0.005*** -0.023*** -0.009*** -0.016*** -0.033*** -0.009 -0.021***(0.002) (0.001) (0.001) (0.006) (0.003) (0.004) (0.010) (0.006) (0.008)
Mean 0.095 0.039 0.066 0.319 0.137 0.226 0.717 0.357 0.533
Total Taxes ($000)0.013*** 0.010* 0.012** 0.042*** 0.010 0.026** 0.115** 0.061 0.088*(0.004) (0.006) (0.005) (0.014) (0.011) (0.012) (0.047) (0.051) (0.048)
Mean 0.391 0.555 0.475 0.815 1.271 1.048 3.640 4.364 4.010
Observations 4,913,139 5,132,023 10,045,162 4,913,139 5,132,023 10,045,162 4,913,139 5,132,023 10,045,162
Simulated Years Eligible, Age 0-18
(1)By Age 19
(2)By Age 22
(3)By Age 28
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneouscollege enrollment indicates current enrollment in college at a given age, observed through Form 1098-T, filed by educationalinstitutions. Contemporaneous fertility indicates if a first dependent child is born at a given age. If an individual ever claimsa dependent child on a Form 1040, SSA records yield age at birth. Contemporaneous mortality indicates mortality at a givenage, measured using SSA death records. Contemporaneous wage income indicates wages earned at a given age, obtained fromForm W-2, adjusted to 2011 dollars and censored at $10 million. Contemporaneous EITC indicates EITC earned at a given age,obtained from Form 1040, adjusted to 2011 dollars. Contemporaneous total taxes indicate taxes paid at a given age, definedas household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients foreach age are obtained from separate reduced form regressions of the given outcome at that age on simulated years eligible, ages0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest ageat which we observe all individuals in our sample).
35
Table A.2: Cumulative Outcomes at Ages 19, 22, and 28
Female Male All Female Male All Female Male All
College (Ever Enrolled; %)
1.261** 1.305* 1.281** 0.813** 0.805* 0.806* 0.458 0.519 0.486
(0.608) (0.652) (0.629) (0.380) (0.450) (0.415) (0.278) (0.339) (0.307)
Mean 62.209 51.593 56.785 73.562 62.858 68.094 80.888 69.501 75.070
Fertility (Ever Had Dependent Child; %)
-0.512** -0.187 -0.348** -0.870** -0.387* -0.625** -1.177*** -0.721** -0.948***
(0.212) (0.119) (0.159) (0.344) (0.215) (0.271) (0.374) (0.313) (0.332)
Mean 15.863 8.572 12.138 28.763 17.442 22.979 50.573 36.103 43.180
Mortality (%)
-0.003 -0.001 -0.002 -0.010* 0.007 -0.001 -0.009 -0.031* -0.020*
(0.003) (0.004) (0.003) (0.006) (0.009) (0.006) (0.010) (0.017) (0.011)
Mean 0.037 0.098 0.068 0.152 0.454 0.306 0.417 1.191 0.812
Wage Income ($000)
0.059* 0.061 0.061* 0.152 -0.042 0.055 1.784*** 0.581 1.177
(0.031) (0.041) (0.033) (0.145) (0.189) (0.160) (0.662) (0.885) (0.715)
Mean 4.198 4.864 4.538 25.262 30.147 27.758 136.600 161.350 149.245
EITC ($000)
-0.006*** -0.003*** -0.005*** -0.059*** -0.026*** -0.042*** -0.263*** -0.103*** -0.182***
(0.002) (0.001) (0.001) (0.015) (0.008) (0.011) (0.063) (0.034) (0.046)
Mean 0.095 0.039 0.066 0.831 0.351 0.586 4.188 1.948 3.044
Total Taxes ($000)
0.013*** 0.010* 0.012** 0.101*** 0.039 0.069** 0.689*** 0.380* 0.533***
(0.004) (0.006) (0.005) (0.034) (0.029) (0.031) (0.200) (0.200) (0.192)
Mean 0.391 0.555 0.475 2.263 3.535 2.913 18.115 23.025 20.623
Observations 4,913,139 5,132,023 10,045,162 4,913,139 5,132,023 10,045,162 4,913,139 5,132,023 10,045,162
(1)
By Age 19
(2)
By Age 22
(3)
By Age 28
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative collegeenrollment indicates ever having enrolled in college by a given age, starting at age 19, observed through Form 1098-T, filedby educational institutions. Cumulative fertility indicates if a dependent child is ever born by a given age, starting at age19. If an individual ever claims a dependent child on a Form 1040, SSA records yield age at birth. Cumulative mortalityindicates mortality by a given age, starting at age 19, measured using SSA death records. Cumulative wage income indicateswage income earned by a given age, starting at age 19, obtained from Form W-2, adjusted to 2011 dollars and censored at $10million. Cumulative EITC indicates EITC earned by a given age, starting at age 19, obtained from Form 1040, adjusted to2011 dollars. Cumulative total taxes indicate taxes paid by a given age, starting at age 19, defined as household federal taxpayments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients for each age are obtained fromseparate reduced form regressions of the given outcome at that age on simulated years eligible, ages 0–18. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample).
36
Table A.3: Robustness of Cumulative Total Tax ($000) Results to Alternative Specifications
Female Male All Female Male All Female Male All
0.013*** 0.010* 0.012** 0.101*** 0.039 0.069** 0.689*** 0.380* 0.533***(0.004) (0.006) (0.005) (0.034) (0.029) (0.031) (0.200) (0.200) (0.192)
Mean 0.391 0.555 0.475 2.263 3.535 2.913 18.115 23.025 20.623
Instrument: Simulated Eligibility in the CPS0.015*** 0.012* 0.014** 0.114*** 0.045 0.079** 0.731*** 0.395* 0.560***(0.005) (0.006) (0.005) (0.039) (0.033) (0.035) (0.216) (0.220) (0.208)
Mean 0.391 0.555 0.475 2.263 3.535 2.913 18.115 23.025 20.623
0.013** 0.015* 0.014** 0.078** 0.040 0.059 0.376** 0.164 0.269(0.006) (0.008) (0.007) (0.038) (0.035) (0.036) (0.172) (0.180) (0.167)
Mean 0.392 0.556 0.476 2.274 3.547 2.924 18.254 23.153 20.757
Specification: Inclusion of Sibling Controls0.013** 0.064* 0.312*(0.005) (0.034) (0.172)
Mean 0.494 3.029 21.537
Specification: Inclusion of Family Fixed Effects0.014 0.052 0.035
(0.012) (0.063) (0.303)Mean 0.494 3.029 21.537
Sample: Parents Filing Jointly0.009** 0.009 0.009* 0.065** 0.013 0.039 0.481** 0.222 0.350*(0.004) (0.006) (0.005) (0.031) (0.030) (0.030) (0.200) (0.226) (0.207)
Mean 0.436 0.595 0.517 2.680 3.865 3.288 22.396 26.452 24.477
Sample: Parents Not Filing Jointly0.020*** 0.012** 0.016*** 0.168*** 0.084** 0.125*** 0.854*** 0.459*** 0.651***(0.006) (0.005) (0.005) (0.044) (0.033) (0.037) (0.229) (0.163) (0.183)
Mean 0.276 0.451 0.364 1.203 2.669 1.944 7.234 14.036 10.671
Sample: Non-filers0.015*** 0.012** 0.013** 0.109*** 0.038 0.074** 0.669*** 0.322* 0.494***(0.005) (0.006) (0.005) (0.036) (0.030) (0.032) (0.184) (0.188) (0.176)
Mean 0.369 0.538 0.455 2.102 3.419 2.773 16.365 21.612 19.037
Specification: Inclusion of Income Controls0.012*** 0.010* 0.011** 0.082** 0.032 0.057* 0.451** 0.207 0.326*(0.004) (0.006) (0.005) (0.031) (0.028) (0.029) (0.170) (0.187) (0.172)
Mean 0.391 0.555 0.475 2.263 3.535 2.913 18.115 23.025 20.623
Sample: Constant State of ResidenceSimulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18 - - - - - -
Simulated Years Eligible using CPS, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
(1)By Age 19
(2)By Age 22
(3)By Age 28
Simulated Years Eligible, Age 0-18
Main Results
- -
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18 - - - -
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxesindicate taxes paid by a given age, starting at age 19, defined as household federal tax payments plus individual payroll taxpayments less EITC, adjusted to 2011 dollars. Coefficients for each age are obtained from separate reduced form regressions ofthe given outcome at that age on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohortby month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Thespecifications that include sibling controls and family fixed effects are estimated in the sample of two-child households for thepooled-gender samples only. Observation counts for each specification are available in the Online Appendix.
37
Online Appendix
Long-Term Impacts of Childhood Medicaid Expansions onOutcomes in Adulthood
by David W. Brown, Amanda E. Kowalski, and Ithai Z. Lurie
Contents
1 State Variation in Medicaid Eligibility 4
2 Main Results Tables 5
2.1 College Enrollment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3 Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.4 Wage Income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.5 Earned Income Tax Credit (EITC) . . . . . . . . . . . . . . . . . . . . . . . 10
2.6 Total Taxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 Main IV Results Tables 12
3.1 College Enrollment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
3.2 Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.3 Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.4 Wage Income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.5 Earned Income Tax Credit (EITC) . . . . . . . . . . . . . . . . . . . . . . . 17
3.6 Total Taxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
4 Main IV Results Figures 19
4.1 College Enrollment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.2 Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.3 Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.4 Wage Income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.5 Earned Income Tax Credit (EITC) . . . . . . . . . . . . . . . . . . . . . . . 23
4.6 Total Taxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
5 Supplemental College Enrollment Results 25
5.1 Supplemental College Enrollment Results Figure . . . . . . . . . . . . . . . . 25
5.2 Supplemental College Enrollment Results Table . . . . . . . . . . . . . . . . 26
1
6 Supplemental Mortality Results 27
6.1 Mortality Results in Surviving Sample . . . . . . . . . . . . . . . . . . . . . 27
6.2 Mortality at Younger Ages . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
7 Supplemental Wage Income Results 31
7.1 Self-employment Results Figure . . . . . . . . . . . . . . . . . . . . . . . . . 31
7.2 Self-employment Results Table . . . . . . . . . . . . . . . . . . . . . . . . . . 32
7.3 Log of Wage Income Results Figure . . . . . . . . . . . . . . . . . . . . . . . 33
7.4 Log of Wage Income Results Table . . . . . . . . . . . . . . . . . . . . . . . 34
8 Supplemental EITC Results 35
8.1 Any EITC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
9 Supplemental Total Taxes Results 37
9.1 Components of Total Taxes: Tables . . . . . . . . . . . . . . . . . . . . . . . 37
9.2 Components of Total Taxes: Combined Figures . . . . . . . . . . . . . . . . 41
9.3 Components of Total Taxes: Separate Figures . . . . . . . . . . . . . . . . . 42
10 Heterogeneous Effects by Childhood Household FPL 45
10.1 College Enrollment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
10.2 Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
10.3 Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
10.4 Wage Income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
10.5 Earned Income Tax Credit (EITC) . . . . . . . . . . . . . . . . . . . . . . . 53
10.6 Total Taxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
10.7 Heterogeneous Effects by Parental Filing Status . . . . . . . . . . . . . . . . 57
11 Heterogeneous Distributional Effects in the High Impact Sample 59
12 Heterogeneous Effects of Medicaid Eligibility at Different Ages 60
13 Robustness to Gender as an Outcome: Falsification Exercise 62
14 Robustness to Assumptions in Early Childhood 63
14.1 Robustness to Simulated Eligibility in the CPS . . . . . . . . . . . . . . . . 63
14.2 Robustness to Restricting Variation in State of Residence . . . . . . . . . . . 65
15 Robustness to Sibling Controls and Family Fixed Effects 67
16 Robustness to Sample Selection 69
2
17 Robustness to OLS, IV, and Income Controls 71
17.1 OLS, IV, and Income Controls . . . . . . . . . . . . . . . . . . . . . . . . . . 71
17.2 OLS, IV, and Income Controls: Table at Age 28 . . . . . . . . . . . . . . . . 73
17.3 Robustness to Richer Income Controls . . . . . . . . . . . . . . . . . . . . . 74
18 Forecast of Fiscal Return on Investment 74
19 First Stage Results 79
20 Filing and Marriage Results 79
20.1 Filing Results Figure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
20.2 Filing Results Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
20.3 Marriage Results Figure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
20.4 Marriage Results Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
21 Regression Discontinuity Results 84
21.1 Regression Discontinuity Figures . . . . . . . . . . . . . . . . . . . . . . . . 86
21.2 Regression Discontinuity Table . . . . . . . . . . . . . . . . . . . . . . . . . . 94
3
Appendix 1 State Variation in Medicaid Eligibility
Figure OA.1: State Variation in Actual Years Eligible for Medicaid, Ages 0–18
7.07 − 7.175.35 − 7.074.30 − 5.353.38 − 4.302.55 − 3.380.68 − 2.55
Born Jan '81Eligibility
7.07 − 9.765.35 − 7.074.30 − 5.353.38 − 4.302.55 − 3.381.57 − 2.55
Born Dec '84Eligibility
Note. Bins reflect the sextiles of the distribution for the cohort born in December 1984. We present theJanuary 1981 and December 1984 cohorts because they are the oldest and youngest cohorts in our sample.
4
Ap
pen
dix
2M
ain
Resu
ltsT
ab
les
2.1
Colle
ge
Enro
llment
Table OA.1: Contemporaneous and Cumulative College Enrollment (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Female1.750*** 1.171** 0.767 0.718 0.583 0.655*** 0.285 0.270* 0.073 -0.026(0.539) (0.489) (0.476) (0.435) (0.438) (0.228) (0.245) (0.161) (0.166) (0.157)
Mean 57.617 57.535 55.003 50.040 38.253 30.240 26.617 24.229 22.150 20.062
Male1.637*** 0.945* 0.644* 0.646* 0.382 0.292 0.099 0.094 -0.034 -0.092(0.568) (0.484) (0.379) (0.342) (0.354) (0.223) (0.241) (0.145) (0.158) (0.154)
Mean 47.684 47.512 44.558 40.454 31.936 23.910 19.793 17.472 15.848 14.461
All1.690*** 1.053** 0.701* 0.678* 0.479 0.466** 0.187 0.177 0.016 -0.062(0.549) (0.476) (0.418) (0.384) (0.392) (0.221) (0.236) (0.146) (0.154) (0.143)
Mean 52.542 52.414 49.667 45.143 35.025 27.006 23.130 20.777 18.930 17.201
Cumulative College (Ever Enrolled; %)Female
1.261** 1.054** 0.876** 0.813** 0.785** 0.744** 0.609* 0.545* 0.473 0.458(0.608) (0.452) (0.394) (0.380) (0.360) (0.342) (0.331) (0.319) (0.298) (0.278)
Mean 62.209 68.004 71.339 73.562 75.161 76.539 77.788 78.944 79.982 80.888
Male1.305* 0.996* 0.817* 0.805* 0.802* 0.792* 0.737* 0.632* 0.576 0.519(0.652) (0.541) (0.471) (0.450) (0.425) (0.399) (0.389) (0.370) (0.357) (0.339)
Mean 51.593 57.531 60.727 62.858 64.315 65.524 66.641 67.663 68.623 69.501
All1.281** 1.022** 0.843* 0.806* 0.791** 0.766** 0.672* 0.586* 0.522 0.486(0.629) (0.495) (0.433) (0.415) (0.392) (0.369) (0.359) (0.344) (0.326) (0.307)
Mean 56.785 62.654 65.917 68.094 69.620 70.911 72.093 73.181 74.179 75.070
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Contemporaneous College (Currently Enrolled; %)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous college enrollment indicatescurrent enrollment in college at a given age, observed through Form 1098-T, filed by educational institutions. Cumulative college enrollment indicatesever having enrolled in college by a given age, starting at age 19. Coefficients for each age are obtained from separate reduced form regressions of collegeenrollment on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15(the youngest age at which we observe all individuals in our sample).
5
2.2
Fertility
Table OA.2: Contemporaneous and Cumulative Fertility (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Contemporaneous Fertility (First Dependent Child Born; %)Female
-0.119** -0.130** -0.139** -0.088 -0.022 -0.057 -0.070** -0.009 -0.085** -0.063(-0.057) (0.060) (0.062) (0.054) (0.036) (0.041) (0.031) (0.032) (0.033) (0.050)
Mean 4.848 4.709 4.220 3.971 3.726 3.654 3.710 3.705 3.721 3.294
Male-0.051 -0.051 -0.107** -0.042 -0.049 -0.090** -0.040 -0.058* -0.026 -0.072**
(-0.042) (0.047) (0.041) (0.048) (0.039) (0.037) (0.030) (0.030) (0.030) (0.029)Mean 2.488 2.834 2.958 3.077 3.134 3.177 3.180 3.157 3.162 2.852
All-0.085* -0.090* -0.123** -0.065 -0.036 -0.074** -0.055** -0.035 -0.055** -0.068*(0.047) (0.047) (0.047) (0.045) (0.033) (0.037) (0.023) (0.023) (0.022) (0.034)
Mean 3.642 3.751 3.575 3.514 3.423 3.410 3.439 3.425 3.435 3.068
Female-0.512** -0.642** -0.781** -0.870** -0.892** -0.949** -1.019** -1.028** -1.114*** -1.177***(0.212) (0.250) (0.300) (0.344) (0.362) (0.391) (0.400) (0.399) (0.399) (0.374)
Mean 15.863 20.572 24.792 28.763 32.489 36.143 39.854 43.559 47.279 50.573
Male-0.187 -0.238 -0.345* -0.387* -0.436* -0.526* -0.566* -0.624* -0.649** -0.721**(0.119) (0.157) (0.189) (0.215) (0.245) (0.274) (0.293) (0.313) (0.313) (0.313)
Mean 8.572 11.407 14.364 17.442 20.575 23.752 26.932 30.088 33.250 36.103
All-0.348** -0.438** -0.560** -0.625** -0.662** -0.736** -0.790** -0.825** -0.880** -0.948***(0.159) (0.196) (0.237) (0.271) (0.293) (0.322) (0.336) (0.346) (0.345) (0.332)
Mean 12.138 15.890 19.465 22.979 26.402 29.812 33.252 36.677 40.112 43.180
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Cumulative Fertility (Dependent Child Ever Born; %)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous fertility indicates if a firstdependent child is born at a given age, and cumulative fertility indicates if a dependent child is ever born by a given age, starting at age 19. If anindividual ever claims a dependent child on a Form 1040, SSA records yield age at birth. Coefficients for each age are obtained from separate reducedform regressions of fertility on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state ofresidence at age 15 (the youngest age at which we observe all individuals in our sample).
6
Table OA.3: Contemporaneous and Cumulative Fertility (%)
(1) (2) (3) (4)Age 15 Age 16 Age 17 Age 18
Female-0.039* -0.055 -0.062 -0.133**(-0.021) (-0.034) (-0.044) (-0.065)
Mean 1.056 1.806 2.805 3.880
Male0.003 -0.003 0.006 -0.011
(-0.013) (-0.013) (-0.017) (-0.031)Mean 0.642 0.865 1.290 1.883
All-0.018 -0.029 -0.028 -0.071(0.015) (0.019) (0.028) (0.044)
Mean 0.844 1.325 2.031 2.860
Female-0.038 -0.117* -0.197* -0.393**
(-0.035) (-0.069) (-0.099) (-0.163)Mean 2.523 4.330 7.135 11.015
Male-0.042 -0.056 -0.075 -0.136
(-0.032) (-0.034) (-0.052) (-0.083)Mean 2.048 2.912 4.202 6.084
All-0.040 -0.087* -0.135* -0.263**
(-0.027) (-0.044) (-0.071) (-0.118)Mean 2.280 3.606 5.637 8.496
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162
Contemporaneous Fertility (First Dependent Child Born; %)
Cumulative Fertility (Dependent Child Ever Born; %)
Simulated Years Eligible, Birth to Given Age
Simulated Years Eligible, Birth to Given Age
Simulated Years Eligible, Birth to Given Age
Simulated Years Eligible, Birth to Given Age
Simulated Years Eligible, Birth to Given Age
Simulated Years Eligible, Birth to Given Age
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous fertilityindicates if a first dependent child is born at a given age, and cumulative fertility indicates if a dependent child is ever born bya given age, starting at age 15. If an individual ever claims a dependent child on a Form 1040, SSA records yield age at birth.Coefficients for each age are obtained from separate reduced form regressions of fertility on simulated years eligible from birththrough the given age. The specification includes fixed effects for birth cohort by month and for state of residence at age 15(the youngest age at which we observe all individuals in our sample).
7
2.3
Morta
lity
Table OA.4: Contemporaneous and Cumulative Mortality (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Contemporaneous Mortality (%)Female
-0.003 0.001 -0.004 -0.005** -0.001 -0.001 -0.005 0.000 0.001 0.006*(0.003) (0.003) (0.004) (0.002) (0.003) (0.004) (0.003) (0.003) (0.004) (0.003)
Mean 0.037 0.037 0.038 0.040 0.039 0.041 0.042 0.046 0.046 0.051
Male-0.001 0.004 -0.001 0.006 -0.009** -0.013** 0.001 -0.002 -0.005 -0.009(0.004) (0.005) (0.004) (0.005) (0.004) (0.005) (0.004) (0.005) (0.005) (0.006)
Mean 0.098 0.111 0.120 0.125 0.126 0.129 0.125 0.121 0.120 0.121
All-0.002 0.003 -0.003 0.000 -0.005* -0.007** -0.002 -0.001 -0.002 -0.001(0.003) (0.003) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.004) (0.004)
Mean 0.068 0.075 0.080 0.084 0.083 0.086 0.084 0.084 0.084 0.087
Female-0.003 -0.001 -0.005 -0.010* -0.011 -0.012 -0.017* -0.016* -0.015* -0.009(0.003) (0.004) (0.006) (0.006) (0.007) (0.008) (0.009) (0.008) (0.009) (0.010)
Mean 0.037 0.074 0.112 0.152 0.191 0.232 0.274 0.320 0.367 0.417
Male-0.001 0.003 0.002 0.007 -0.002 -0.015 -0.015 -0.017 -0.022 -0.031*(0.004) (0.007) (0.008) (0.009) (0.010) (0.012) (0.013) (0.013) (0.014) (0.017)
Mean 0.098 0.209 0.329 0.454 0.579 0.707 0.831 0.951 1.070 1.191
All-0.002 0.001 -0.001 -0.001 -0.006 -0.013* -0.015* -0.016** -0.018** -0.020*(0.003) (0.004) (0.005) (0.006) (0.007) (0.008) (0.008) (0.008) (0.008) (0.011)
Mean 0.068 0.143 0.223 0.306 0.389 0.475 0.559 0.643 0.726 0.812
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Cumulative Mortality (%)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous mortality indicates mortality ata given age, measured using SSA death records. Cumulative mortality indicates mortality by a given age, starting at age 19. Coefficients for each ageare obtained from separate reduced form regressions of mortality on simulated years eligible, ages 0–18. The specification includes fixed effects for birthcohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).
8
2.4
Wage
Inco
me
Table OA.5: Contemporaneous Wage Income ($000)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Female
0.059* 0.045 -0.029 0.077 0.213*** 0.306*** 0.259** 0.208 0.232 0.414***
(0.031) (0.043) (0.039) (0.061) (0.073) (0.090) (0.121) (0.142) (0.144) (0.148)
Mean 4.198 5.566 6.769 8.729 12.234 15.684 18.137 20.106 21.842 23.336
Male
0.061 0.024 -0.082 -0.045 0.069 0.130 0.197 0.066 0.012 0.149
(0.041) (0.047) (0.067) (0.075) (0.110) (0.146) (0.168) (0.170) (0.167) (0.183)
Mean 4.864 6.619 8.204 10.461 14.038 18.026 20.988 23.519 26.055 28.577
All
0.061* 0.035 -0.055 0.015 0.140* 0.217* 0.228 0.136 0.121 0.280*
(0.033) (0.038) (0.051) (0.064) (0.083) (0.109) (0.138) (0.147) (0.149) (0.150)
Mean 4.538 6.104 7.502 9.614 13.156 16.880 19.593 21.850 23.994 26.013
Female
0.059* 0.104 0.076 0.152 0.366* 0.672** 0.930*** 1.139*** 1.370** 1.784***
(0.031) (0.069) (0.094) (0.145) (0.206) (0.255) (0.324) (0.424) (0.539) (0.662)
Mean 4.198 9.763 16.532 25.262 37.496 53.180 71.316 91.422 113.264 136.600
Male
0.061 0.085 0.003 -0.042 0.027 0.157 0.354 0.420 0.432 0.581
(0.041) (0.083) (0.131) (0.189) (0.271) (0.358) (0.482) (0.609) (0.728) (0.885)
Mean 4.864 11.483 19.687 30.147 44.186 62.212 83.199 106.718 132.774 161.350
All
0.061* 0.095 0.040 0.055 0.195 0.411 0.639* 0.776 0.896 1.177
(0.033) (0.069) (0.104) (0.160) (0.226) (0.282) (0.372) (0.480) (0.591) (0.715)
Mean 4.538 10.642 18.144 27.758 40.914 57.794 77.387 99.237 123.231 149.245
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Contemporaneous Wage Income ($000)
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Cumulative Wage Income ($000)
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous wage income indicates wagesearned at a given age, obtained from Form W-2, adjusted to 2011 dollars and censored at $10 million. Cumulative wage income indicates wage incomeearned by a given age, starting at age 19. Coefficients for each age are obtained from separate reduced form regressions of wage income on simulatedyears eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at whichwe observe all individuals in our sample).
9
2.5
Earn
ed
Inco
me
Tax
Cre
dit
(EIT
C)
Table OA.6: Contemporaneous and Cumulative EITC ($000)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Contemporaneous EITC ($000)Female
-0.006*** -0.013*** -0.017*** -0.023*** -0.026*** -0.030*** -0.037*** -0.040*** -0.039*** -0.033***(0.002) (0.003) (0.005) (0.006) (0.006) (0.007) (0.008) (0.009) (0.010) (0.010)
Mean 0.095 0.170 0.248 0.319 0.388 0.453 0.538 0.600 0.660 0.717
Male-0.003*** -0.006*** -0.008*** -0.009*** -0.012*** -0.010*** -0.015*** -0.017*** -0.015** -0.009(0.001) (0.002) (0.002) (0.003) (0.004) (0.004) (0.005) (0.005) (0.006) (0.006)
Mean 0.039 0.070 0.105 0.137 0.167 0.197 0.257 0.292 0.326 0.357
All-0.005*** -0.009*** -0.012*** -0.016*** -0.019*** -0.020*** -0.026*** -0.028*** -0.026*** -0.021***(0.001) (0.002) (0.003) (0.004) (0.005) (0.005) (0.006) (0.007) (0.007) (0.008)
Mean 0.066 0.119 0.175 0.226 0.275 0.323 0.395 0.443 0.489 0.533
Female-0.006*** -0.019*** -0.036*** -0.059*** -0.084*** -0.114*** -0.151*** -0.191*** -0.230*** -0.263***(0.002) (0.005) (0.009) (0.015) (0.022) (0.028) (0.035) (0.044) (0.053) (0.063)
Mean 0.095 0.264 0.512 0.831 1.219 1.672 2.210 2.810 3.470 4.188
Male-0.003*** -0.009*** -0.017*** -0.026*** -0.037*** -0.048*** -0.063*** -0.080*** -0.094*** -0.103***(0.001) (0.003) (0.005) (0.008) (0.011) (0.015) (0.018) (0.023) (0.029) (0.034)
Mean 0.039 0.109 0.214 0.351 0.519 0.716 0.973 1.265 1.591 1.948
All-0.005*** -0.014*** -0.026*** -0.042*** -0.061*** -0.080*** -0.106*** -0.135*** -0.161*** -0.182***(0.001) (0.004) (0.007) (0.011) (0.016) (0.020) (0.026) (0.032) (0.039) (0.046)
Mean 0.066 0.185 0.360 0.586 0.861 1.184 1.578 2.021 2.510 3.044
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Cumulative EITC ($000)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous EITC indicates EITC earned at agiven age, obtained from Form 1040, adjusted to 2011 dollars. Cumulative EITC indicates EITC earned by a given age, starting at age 19. Coefficientsfor each age are obtained from separate reduced form regressions of EITC on simulated years eligible, ages 0–18. The specification includes fixed effectsfor birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).
10
2.6
Tota
lT
axes
Table OA.7: Contemporaneous and Cumulative Total Taxes ($000)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Contemporaneous Total Taxes ($000)Female
0.013*** 0.021*** 0.025** 0.042*** 0.066*** 0.087*** 0.110*** 0.116*** 0.093** 0.115**(0.004) (0.007) (0.010) (0.014) (0.018) (0.024) (0.030) (0.038) (0.042) (0.047)
Mean 0.391 0.483 0.574 0.815 1.408 2.057 2.513 2.948 3.286 3.640
Male0.010* 0.011 0.007 0.010 0.031 0.053* 0.074** 0.074* 0.049 0.061(0.006) (0.007) (0.009) (0.011) (0.019) (0.031) (0.035) (0.038) (0.039) (0.051)
Mean 0.555 0.758 0.952 1.271 1.864 2.591 3.110 3.594 3.967 4.364
All0.012** 0.016** 0.016* 0.026** 0.048*** 0.070*** 0.092*** 0.094** 0.071* 0.088*(0.005) (0.007) (0.009) (0.012) (0.017) (0.026) (0.031) (0.037) (0.039) (0.048)
Mean 0.475 0.623 0.767 1.048 1.641 2.330 2.818 3.278 3.634 4.010
Female0.013*** 0.034*** 0.059*** 0.101*** 0.167*** 0.255*** 0.365*** 0.481*** 0.574*** 0.689***(0.004) (0.011) (0.021) (0.034) (0.050) (0.068) (0.093) (0.125) (0.160) (0.200)
Mean 0.391 0.874 1.447 2.263 3.671 5.728 8.241 11.189 14.475 18.115
Male0.010* 0.021* 0.028 0.039 0.069 0.122* 0.196** 0.270** 0.319** 0.380*(0.006) (0.012) (0.020) (0.029) (0.042) (0.063) (0.092) (0.125) (0.157) (0.200)
Mean 0.555 1.313 2.264 3.535 5.399 7.989 11.100 14.693 18.661 23.025
All0.012** 0.028** 0.044** 0.069** 0.118*** 0.187*** 0.279*** 0.374*** 0.445*** 0.533***(0.005) (0.011) (0.020) (0.031) (0.044) (0.061) (0.087) (0.119) (0.152) (0.192)
Mean 0.475 1.098 1.865 2.913 4.554 6.883 9.701 12.980 16.613 20.623
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Cumulative Total Taxes ($000)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous total taxes indicate taxes paid ata given age, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Cumulative total taxesindicate taxes paid by a given age, starting at age 19. Coefficients for each age are obtained from separate reduced form regressions of total taxes onsimulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngestage at which we observe all individuals in our sample).
11
Ap
pen
dix
3M
ain
IVR
esu
ltsT
ab
les
3.1
Colle
ge
Enro
llment
Table OA.8: Cumulative College Enrollment (%): IV Results and Main Results
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
IV Results
Female
1.358* 1.135** 0.943** 0.876** 0.846** 0.802** 0.656* 0.587 0.509 0.493
(0.731) (0.540) (0.457) (0.435) (0.413) (0.392) (0.376) (0.361) (0.335) (0.314)
Mean 62.209 68.004 71.339 73.562 75.161 76.539 77.788 78.944 79.982 80.888
Male
1.381* 1.054* 0.865 0.851* 0.849* 0.839* 0.780* 0.669 0.609 0.550
(0.763) (0.619) (0.531) (0.507) (0.481) (0.453) (0.441) (0.415) (0.399) (0.378)
Mean 51.593 57.531 60.727 62.858 64.315 65.524 66.641 67.663 68.623 69.501
All
1.367* 1.091* 0.900* 0.860* 0.844* 0.817* 0.717* 0.626 0.557 0.519
(0.745) (0.578) (0.494) (0.471) (0.446) (0.421) (0.407) (0.388) (0.366) (0.344)
Mean 56.785 62.654 65.917 68.094 69.620 70.911 72.093 73.181 74.179 75.070
Main Results
Female
1.261** 1.054** 0.876** 0.813** 0.785** 0.744** 0.609* 0.545* 0.473 0.458
(0.608) (0.452) (0.394) (0.380) (0.360) (0.342) (0.331) (0.319) (0.298) (0.278)
Mean 62.209 68.004 71.339 73.562 75.161 76.539 77.788 78.944 79.982 80.888
Male
1.305* 0.996* 0.817* 0.805* 0.802* 0.792* 0.737* 0.632* 0.576 0.519
(0.652) (0.541) (0.471) (0.450) (0.425) (0.399) (0.389) (0.370) (0.357) (0.339)
Mean 51.593 57.531 60.727 62.858 64.315 65.524 66.641 67.663 68.623 69.501
All
1.281** 1.022** 0.843* 0.806* 0.791** 0.766** 0.672* 0.586* 0.522 0.486
(0.629) (0.495) (0.433) (0.415) (0.392) (0.369) (0.359) (0.344) (0.326) (0.307)
Mean 56.785 62.654 65.917 68.094 69.620 70.911 72.093 73.181 74.179 75.070
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Cumulative College (Ever Enrolled; %)
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative college enrollment indicatesever having enrolled in college by a given age, starting at age 19. Coefficients are obtained from an IV regression of college enrollment onyears eligible, ages 0–18. The instrument represents simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort bymonth and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Figure OA.2 presents this table graphically.
12
3.2
Fertility
Table OA.9: Cumulative Fertility (%): IV Results and Main Results
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
IV Results
Female
-0.551** -0.692** -0.842** -0.937** -0.961** -1.022** -1.097** -1.107** -1.199** -1.267***
(0.249) (0.299) (0.361) (0.413) (0.431) (0.463) (0.478) (0.474) (0.479) (0.454)
Mean 15.863 20.572 24.792 28.763 32.489 36.143 39.854 43.559 47.279 50.573
Male
-0.198 -0.252 -0.365* -0.410* -0.462* -0.557* -0.598* -0.660* -0.687* -0.763**
(0.134) (0.177) (0.215) (0.243) (0.274) (0.308) (0.329) (0.350) (0.352) (0.354)
Mean 8.572 11.407 14.364 17.442 20.575 23.752 26.932 30.088 33.250 36.103
All
-0.371** -0.467** -0.598** -0.668** -0.706** -0.785** -0.843** -0.880** -0.939** -1.012**
(0.185) (0.230) (0.279) (0.318) (0.341) (0.375) (0.392) (0.401) (0.403) (0.391)
Mean 12.138 15.890 19.465 22.979 26.402 29.812 33.252 36.677 40.112 43.180
Main Results
Female
-0.512** -0.642** -0.781** -0.870** -0.892** -0.949** -1.019** -1.028** -1.114*** -1.177***
(0.212) (0.250) (0.300) (0.344) (0.362) (0.391) (0.400) (0.399) (0.399) (0.374)
Mean 15.863 20.572 24.792 28.763 32.489 36.143 39.854 43.559 47.279 50.573
Male
-0.187 -0.238 -0.345* -0.387* -0.436* -0.526* -0.566* -0.624* -0.649** -0.721**
(0.119) (0.157) (0.189) (0.215) (0.245) (0.274) (0.293) (0.313) (0.313) (0.313)
Mean 8.572 11.407 14.364 17.442 20.575 23.752 26.932 30.088 33.250 36.103
All
-0.348** -0.438** -0.560** -0.625** -0.662** -0.736** -0.790** -0.825** -0.880** -0.948***
(0.159) (0.196) (0.237) (0.271) (0.293) (0.322) (0.336) (0.346) (0.345) (0.332)
Mean 12.138 15.890 19.465 22.979 26.402 29.812 33.252 36.677 40.112 43.180
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Cumulative Fertility (Dependent Child Ever Born; %)
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative fertility indicates if a dependentchild is ever born by a given age, starting at age 19. If an individual ever claims a dependent child on a Form 1040, SSA records yield age at birth.Coefficients are obtained from an IV regression of fertility on years eligible, ages 0–18. The instrument represents simulated years eligible, ages 0–18.The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample). Figure OA.3 presents this table graphically.
13
Table OA.10: Cumulative Fertility (%): IV Results and Main Results
(1) (2) (3) (4)Age 15 Age 16 Age 17 Age 18
IV ResultsFemale
-0.040 -0.128 -0.212* -0.423**(-0.038) (-0.079) (-0.113) (-0.192)
Mean 2.523 4.330 7.135 11.015
Male-0.044 -0.060 -0.079 -0.144
(-0.033) (-0.038) (-0.058) (-0.094)Mean 2.048 2.912 4.202 6.084
All-0.043 -0.094* -0.144* -0.280**
(-0.029) (-0.050) (-0.080) (-0.137)Mean 2.280 3.606 5.637 8.496
Main ResultsFemale
-0.038 -0.117* -0.197* -0.393**(-0.035) (-0.069) (-0.099) (-0.163)
Mean 2.523 4.330 7.135 11.015
Male-0.042 -0.056 -0.075 -0.136
(-0.032) (-0.034) (-0.052) (-0.083)Mean 2.048 2.912 4.202 6.084
All-0.040 -0.087* -0.135* -0.263**
(-0.027) (-0.044) (-0.071) (-0.118)Mean 2.280 3.606 5.637 8.496
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162
Cumulative Fertility (Dependent Child Ever Born; %)
Simulated Years Eligible, Age 0-18
Years Eligible, Age 0-18
Years Eligible, Age 0-18
Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative fertilityindicates if a dependent child is ever born by a given age, starting at age 15. If an individual ever claims a dependent child ona Form 1040, SSA records yield age at birth. Coefficients are obtained from an IV regression of fertility on years eligible. Theinstrument is defined as simulated years eligible. We measure Medicaid eligibility and simulated Medicaid through the givenage. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age atwhich we observe all individuals in our sample). Figure OA.3 presents this table graphically.
14
3.3
Morta
lity
Table OA.11: Cumulative Mortality (%): IV Results and Main Results
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
IV Results
Female
-0.003 -0.001 -0.005 -0.011 -0.012 -0.013 -0.018* -0.018* -0.016* -0.010
(0.003) (0.004) (0.007) (0.007) (0.008) (0.009) (0.010) (0.009) (0.010) (0.011)
Mean 0.037 0.074 0.112 0.152 0.191 0.232 0.274 0.320 0.367 0.417
Male
-0.001 0.003 0.002 0.008 -0.002 -0.016 -0.016 -0.018 -0.023 -0.032*
(0.004) (0.007) (0.008) (0.010) (0.011) (0.013) (0.013) (0.014) (0.015) (0.019)
Mean 0.098 0.209 0.329 0.454 0.579 0.707 0.831 0.951 1.070 1.191
All
-0.002 0.001 -0.002 -0.001 -0.007 -0.014* -0.016* -0.018** -0.020** -0.021*
(0.003) (0.004) (0.005) (0.006) (0.007) (0.008) (0.009) (0.008) (0.009) (0.012)
Mean 0.068 0.143 0.223 0.306 0.389 0.475 0.559 0.643 0.726 0.812
Main Results
Female
-0.003 -0.001 -0.005 -0.011 -0.012 -0.013 -0.018* -0.018* -0.016* -0.010
(0.003) (0.004) (0.007) (0.007) (0.008) (0.009) (0.010) (0.009) (0.010) (0.011)
Mean 0.037 0.074 0.112 0.152 0.191 0.232 0.274 0.320 0.367 0.417
Male
-0.001 0.003 0.002 0.008 -0.002 -0.016 -0.016 -0.018 -0.023 -0.032*
(0.004) (0.007) (0.008) (0.010) (0.011) (0.013) (0.013) (0.014) (0.015) (0.019)
Mean 0.098 0.209 0.329 0.454 0.579 0.707 0.831 0.951 1.070 1.191
All
-0.002 0.001 -0.002 -0.001 -0.007 -0.014* -0.016* -0.018** -0.020** -0.021*
(0.003) (0.004) (0.005) (0.006) (0.007) (0.008) (0.009) (0.008) (0.009) (0.012)
Mean 0.068 0.143 0.223 0.306 0.389 0.475 0.559 0.643 0.726 0.812
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Cumulative Mortality (%)
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative mortality indicates mor-tality by a given age, starting at age 19, measured using SSA death records. Coefficients are obtained from an IV regression of mortality onyears eligible, ages 0–18. The instrument represents simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort bymonth and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Figure OA.4 presents this table graphically.
15
3.4
Wage
Inco
me
Table OA.12: Cumulative Wage Income ($000): IV Results and Main Results
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
IV Results
Female
0.064* 0.112 0.082 0.164 0.394 0.723** 1.002** 1.226** 1.475** 1.921**
(0.034) (0.074) (0.103) (0.160) (0.236) (0.301) (0.380) (0.487) (0.614) (0.760)
Mean 4.198 9.763 16.532 25.262 37.496 53.180 71.316 91.422 113.264 136.600
Male
0.065 0.090 0.004 -0.045 0.029 0.166 0.375 0.445 0.457 0.615
(0.045) (0.091) (0.139) (0.199) (0.287) (0.383) (0.520) (0.655) (0.780) (0.950)
Mean 4.864 11.483 19.687 30.147 44.186 62.212 83.199 106.718 132.774 161.350
All
0.065* 0.102 0.043 0.058 0.208 0.439 0.682 0.828 0.957 1.256
(0.036) (0.075) (0.112) (0.173) (0.248) (0.315) (0.417) (0.533) (0.651) (0.793)
Mean 4.538 10.642 18.144 27.758 40.914 57.794 77.387 99.237 123.231 149.245
Main Results
Female
0.059* 0.104 0.076 0.152 0.366* 0.672** 0.930*** 1.139*** 1.370** 1.784***
(0.031) (0.069) (0.094) (0.145) (0.206) (0.255) (0.324) (0.424) (0.539) (0.662)
Mean 4.198 9.763 16.532 25.262 37.496 53.180 71.316 91.422 113.264 136.600
Male
0.061 0.085 0.003 -0.042 0.027 0.157 0.354 0.420 0.432 0.581
(0.041) (0.083) (0.131) (0.189) (0.271) (0.358) (0.482) (0.609) (0.728) (0.885)
Mean 4.864 11.483 19.687 30.147 44.186 62.212 83.199 106.718 132.774 161.350
All
0.061* 0.095 0.040 0.055 0.195 0.411 0.639* 0.776 0.896 1.177
(0.033) (0.069) (0.104) (0.160) (0.226) (0.282) (0.372) (0.480) (0.591) (0.715)
Mean 4.538 10.642 18.144 27.758 40.914 57.794 77.387 99.237 123.231 149.245
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Cumulative Wage Income ($000)
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative wage income indicates wage incomeearned by a given age, starting at age 19, obtained from Form W-2, adjusted to 2011 dollars and censored at $10 million. Coefficients for each ageare obtained from separate IV regressions of wage income on years eligible, ages 0–18. The instrument is defined as simulated years eligible, ages0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample).Figure OA.5 presents this table graphically.
16
3.5
Earn
ed
Inco
me
Tax
Cre
dit
(EIT
C)
Table OA.13: Cumulative EITC ($000): IV Results and Main Results
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
IV Results
Female
-0.007*** -0.018*** -0.032*** -0.052*** -0.075*** -0.104*** -0.133*** -0.165*** -0.200*** -0.240***
(0.001) (0.004) (0.008) (0.013) (0.019) (0.025) (0.033) (0.041) (0.051) (0.060)
Mean 0.095 0.264 0.512 0.831 1.219 1.672 2.210 2.810 3.470 4.188
Male
-0.003*** -0.007*** -0.015*** -0.024*** -0.036*** -0.048*** -0.060*** -0.074*** -0.087*** -0.105***
(0.001) (0.002) (0.004) (0.007) (0.010) (0.013) (0.018) (0.024) (0.030) (0.037)
Mean 0.039 0.109 0.214 0.351 0.519 0.716 0.973 1.265 1.591 1.948
All
-0.005*** -0.012*** -0.022*** -0.037*** -0.054*** -0.073*** -0.093*** -0.114*** -0.137*** -0.165***
(0.001) (0.003) (0.005) (0.009) (0.014) (0.018) (0.024) (0.031) (0.039) (0.047)
Mean 0.066 0.185 0.360 0.586 0.861 1.184 1.578 2.021 2.510 3.044
Main Results
Female
-0.006*** -0.019*** -0.036*** -0.059*** -0.084*** -0.114*** -0.151*** -0.191*** -0.230*** -0.263***
(0.002) (0.005) (0.009) (0.015) (0.022) (0.028) (0.035) (0.044) (0.053) (0.063)
Mean 0.095 0.264 0.512 0.831 1.219 1.672 2.210 2.810 3.470 4.188
Male
-0.003*** -0.009*** -0.017*** -0.026*** -0.037*** -0.048*** -0.063*** -0.080*** -0.094*** -0.103***
(0.001) (0.003) (0.005) (0.008) (0.011) (0.015) (0.018) (0.023) (0.029) (0.034)
Mean 0.039 0.109 0.214 0.351 0.519 0.716 0.973 1.265 1.591 1.948
All
-0.005*** -0.014*** -0.026*** -0.042*** -0.061*** -0.080*** -0.106*** -0.135*** -0.161*** -0.182***
(0.001) (0.004) (0.007) (0.011) (0.016) (0.020) (0.026) (0.032) (0.039) (0.046)
Mean 0.066 0.185 0.360 0.586 0.861 1.184 1.578 2.021 2.510 3.044
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Cumulative EITC ($000)
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative EITC indicates EITC earned by agiven age, starting at age 19, obtained from Form 1040, adjusted to 2011 dollars. Coefficients for each age are obtained from separate IV regressionsof EITC on years eligible, ages 0–18. The instrument is defined as simulated years eligible, ages 0–18. The specification includes fixed effects for birthcohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Figure OA.6 presents thistable graphically.
17
3.6
Tota
lT
axes
Table OA.14: Cumulative Total Taxes ($000): IV Results and Main Results
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
IV Results
Female
0.014*** 0.036*** 0.063** 0.108** 0.180*** 0.274*** 0.393*** 0.518*** 0.618*** 0.742***
(0.005) (0.013) (0.025) (0.041) (0.062) (0.086) (0.117) (0.157) (0.197) (0.243)
Mean 0.391 0.874 1.447 2.263 3.671 5.728 8.241 11.189 14.475 18.115
Male
0.011* 0.023 0.030 0.041 0.073 0.129* 0.208** 0.285** 0.337* 0.402*
(0.006) (0.014) (0.023) (0.033) (0.047) (0.070) (0.103) (0.139) (0.174) (0.219)
Mean 0.555 1.313 2.264 3.535 5.399 7.989 11.100 14.693 18.661 23.025
All
0.012** 0.029** 0.047** 0.074** 0.126** 0.200*** 0.298*** 0.399*** 0.475*** 0.568**
(0.005) (0.013) (0.023) (0.036) (0.052) (0.073) (0.103) (0.140) (0.177) (0.221)
Mean 0.475 1.098 1.865 2.913 4.554 6.883 9.701 12.980 16.613 20.623
Main Results
Female
0.013*** 0.034*** 0.059*** 0.101*** 0.167*** 0.255*** 0.365*** 0.481*** 0.574*** 0.689***
(0.004) (0.011) (0.021) (0.034) (0.050) (0.068) (0.093) (0.125) (0.160) (0.200)
Mean 0.391 0.874 1.447 2.263 3.671 5.728 8.241 11.189 14.475 18.115
Male
0.010* 0.021* 0.028 0.039 0.069 0.122* 0.196** 0.270** 0.319** 0.380*
(0.006) (0.012) (0.020) (0.029) (0.042) (0.063) (0.092) (0.125) (0.157) (0.200)
Mean 0.555 1.313 2.264 3.535 5.399 7.989 11.100 14.693 18.661 23.025
All
0.012** 0.028** 0.044** 0.069** 0.118*** 0.187*** 0.279*** 0.374*** 0.445*** 0.533***
(0.005) (0.011) (0.020) (0.031) (0.044) (0.061) (0.087) (0.119) (0.152) (0.192)
Mean 0.475 1.098 1.865 2.913 4.554 6.883 9.701 12.980 16.613 20.623
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Cumulative Total Taxes ($000)
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxes indicate taxes paid by agiven age, starting at age 19, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars.Coefficients for each age are obtained from separate IV regressions of total taxes on years eligible, ages 0–18. The instrument is defined as simulatedyears eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age atwhich we observe all individuals in our sample). Figure OA.7 presents this table graphically.
18
Appendix 4 Main IV Results Figures
4.1 College Enrollment
Figure OA.2: Cumulative College Enrollment (%): IV Results0
.51
1.5
22.
5IV
Coe
ffici
ents
(%
)
19 22 25 28
Female
0.5
11.
52
2.5
19 22 25 28Age
Male
0.5
11.
52
2.5
19 22 25 28
All
020
4060
80M
eans
(%
)
19 22 25 28
020
4060
80
19 22 25 28Age
020
4060
80
19 22 25 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative college enrollment indicates ever having enrolled in college by a given age, starting at age 19, observedthrough Form 1098-T, filed by educational institutions. Coefficients for each age are obtained from separate IV regressions ofcollege enrollment on years eligible, ages 0–18. The instrument is defined as simulated years eligible, ages 0–18. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Table OA.8contains corresponding results.
19
4.2 Fertility
Figure OA.3: Cumulative Fertility (%): IV Results
-2-1
.5-1
-.5
0IV
Coe
ffici
ents
(%
)
14 16 18 20 22 24 26 28
Female
-2-1
.5-1
-.5
0
14 16 18 20 22 24 26 28Age
Male
-2-1
.5-1
-.5
0
14 16 18 20 22 24 26 28
All0
1020
3040
50M
eans
(%
)
14 16 18 20 22 24 26 28
010
2030
4050
14 16 18 20 22 24 26 28Age
010
2030
4050
14 16 18 20 22 24 26 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative fertility indicates if a dependent child is ever born by a given age, starting at age 15. If an individual everclaims a dependent child on a Form 1040, SSA records yield age at birth. Coefficients for each age are obtained from separate IVregressions of fertility on years eligible. The instrument is defined as simulated years eligible. We measure Medicaid eligibilityand simulated Medicaid through the given age or through age 18, whichever is younger. The specification includes fixed effectsfor birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in oursample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Table OA.9 and Table OA.10contain corresponding results.
20
4.3 Mortality
Figure OA.4: Cumulative Mortality (%): IV Results
-.1
-.05
0.0
5IV
Coe
ffici
ents
(%
)
19 22 25 28
Female
-.1
-.05
0.0
5
19 22 25 28Age
Male
-.1
-.05
0.0
5
19 22 25 28
All0
.51
1.5
Mea
ns (
%)
19 22 25 28
0.5
11.
5
19 22 25 28Age
0.5
11.
5
19 22 25 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative mortality indicates mortality by a given age, starting at age 19, measured using SSA death records. Co-efficients for each age are obtained from separate IV regressions of mortality on years eligible, ages 0–18. The instrument isdefined as simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for stateof residence at age 15 (the youngest age at which we observe all individuals in our sample). Standard errors are clustered bystate. Dashed lines show 95% confidence intervals. Table OA.11 contains corresponding results.
21
4.4 Wage Income
Figure OA.5: Cumulative Wage Income ($000): IV Results
-10
12
34
IV C
oeffi
cien
ts
19 22 25 28
Female
-10
12
34
19 22 25 28
Age
Male
-10
12
34
19 22 25 28
All0
5010
015
0M
eans
19 22 25 28
050
100
150
19 22 25 28Age
050
100
150
19 22 25 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative wage income indicates wage income earned by a given age, starting at age 19, obtained from Form W-2,adjusted to 2011 dollars and censored at $10 million. Coefficients for each age are obtained from separate IV regressions ofwage income on years eligible, ages 0–18. The instrument is defined as simulated years eligible, ages 0–18. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Table OA.12contains corresponding results.
22
4.5 Earned Income Tax Credit (EITC)
Figure OA.6: Cumulative EITC ($000): IV Results
-.4
-.3
-.2
-.1
0IV
Coe
ffici
ents
19 22 25 28
Female
-.4
-.3
-.2
-.1
0
19 22 25 28Age
Male
-.4
-.3
-.2
-.1
0
19 22 25 28
All0
12
34
Mea
ns
19 22 25 28
01
23
4
19 22 25 28Age
01
23
4
19 22 25 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative EITC indicates EITC earned by a given age, starting at age 19, obtained from Form 1040, adjusted to 2011dollars. Coefficients for each age are obtained from separate IV regressions of EITC on years eligible, ages 0–18. The instrumentis defined as simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for stateof residence at age 15 (the youngest age at which we observe all individuals in our sample). Standard errors are clustered bystate. Dashed lines show 95% confidence intervals. Table OA.13 contains corresponding results.
23
4.6 Total Taxes
Figure OA.7: Cumulative Total Taxes ($000): IV Results
0.5
11.
5IV
Coe
ffici
ents
19 22 25 28
Female
0.5
11.
5
19 22 25 28Age
Male
0.5
11.
5
19 22 25 28
All0
510
1520
25M
eans
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative total taxes indicate taxes paid by a given age, starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients for each age are obtained from separateIV regressions of total taxes on years eligible, ages 0–18. The instrument is defined as simulated years eligible, ages 0–18. Thespecification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at whichwe observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals.Table OA.14 contains corresponding results.
24
Appendix 5 Supplemental College Enrollment Results
5.1 Supplemental College Enrollment Results Figure
Figure OA.8: Contemporaneous College Enrollment, Including at Least Half-Time (%)
0.5
11.
52
Coe
ffici
ents
(%
)
19 22 25 28
Female
0.5
11.
52
19 22 25 28
Age
Male
0.5
11.
52
19 22 25 28
All
Currently Enrolled Currently Enrolled, at Least Half-Time
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
1020
3040
5060
Mea
ns (
%)
19 22 25 28
1020
3040
5060
19 22 25 28Age
1020
3040
5060
19 22 25 28Age
Currently Enrolled Currently Enrolled, at Least Half-Time
Contemporaneous College Enrollment (%)
Note. Contemporaneous college enrollment indicates if Form 1098-T was returned by any educational institution for the taxyear corresponding to each age. Contemporaneous college enrollment, at least half time, indicates whether a Form 1098-Twas returned with the “at least half-time” box checked. Coefficients for each age are obtained from separate reduced formregressions of the given outcome on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohortby month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Standarderrors are clustered by state. Table OA.15 contains corresponding results.
25
5.2
Supple
menta
lC
olle
ge
Enro
llment
Resu
ltsT
ab
le
Table OA.15: Contemporaneous College Enrollment, at Least Half-Time (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Female1.374** 0.479 0.688 0.911* 0.471 0.225 0.068 0.279 0.172 -0.042(0.652) (0.606) (0.449) (0.462) (0.331) (0.181) (0.165) (0.171) (0.161) (0.154)
Mean 53.014 52.820 49.703 44.127 31.571 23.171 20.166 18.565 17.326 16.121
Male1.216* 0.410 0.735* 0.820** 0.259 0.022 -0.051 0.067 0.052 -0.111(0.672) (0.611) (0.388) (0.404) (0.284) (0.160) (0.162) (0.144) (0.174) (0.153)
Mean 43.588 43.431 40.090 35.656 26.776 18.667 15.163 13.473 12.458 11.692
All1.291* 0.442 0.710* 0.862** 0.361 0.119 0.005 0.169 0.108 -0.079(0.660) (0.603) (0.408) (0.426) (0.299) (0.161) (0.156) (0.151) (0.163) (0.147)
Mean 48.198 48.023 44.792 39.799 29.121 20.870 17.610 15.964 14.839 13.859
Female1.750*** 1.171** 0.767 0.718 0.583 0.655*** 0.285 0.270* 0.073 -0.026(0.539) (0.489) (0.476) (0.435) (0.438) (0.228) (0.245) (0.161) (0.166) (0.157)
Mean 57.617 57.535 55.003 50.040 38.253 30.240 26.617 24.229 22.150 20.062
Male1.637*** 0.945* 0.644* 0.646* 0.382 0.292 0.099 0.094 -0.034 -0.092(0.568) (0.484) (0.379) (0.342) (0.354) (0.223) (0.241) (0.145) (0.158) (0.154)
Mean 47.684 47.512 44.558 40.454 31.936 23.910 19.793 17.472 15.848 14.461
All1.690*** 1.053** 0.701* 0.678* 0.479 0.466** 0.187 0.177 0.016 -0.062(0.549) (0.476) (0.418) (0.384) (0.392) (0.221) (0.236) (0.146) (0.154) (0.143)
Mean 52.542 52.414 49.667 45.143 35.025 27.006 23.130 20.777 18.930 17.201
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Contemporaneous College (Currently Enrolled, at Least Half Time; %)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Contemporaneous College (Currently Enrolled, %)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous college enrollmentindicates if Form 1098-T was returned by any educational institution for the tax year corresponding to each age. Contemporaneous collegeenrollment, at least half time, indicates whether a Form 1098-T was returned with the “at least half-time” box checked. Coefficients for eachage are obtained from separate reduced form regressions of the given outcome on simulated years eligible, ages 0–18. The specification includesfixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).Figure OA.8 presents this table graphically.
26
Appendix 6 Supplemental Mortality Results
6.1 Mortality Results in Surviving Sample
Figure OA.9: Contemporaneous Mortality in Surviving Sample (%)
-.02
-.01
0.0
1.0
2 C
oeffi
cien
ts (
%)
19 22 25 28
Female
-.02
-.01
0.0
1.0
2
19 22 25 28Age
Male
-.02
-.01
0.0
1.0
2
19 22 25 28
All
0.0
5.1
.15
Mea
ns (
%)
19 22 25 28
0.0
5.1
.15
19 22 25 28Age
0.0
5.1
.15
19 22 25 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous mortality indicates mortality at a given age, measured using SSA death records. Whereas our mainsample conditions on surviving only until age 18, the surviving sample conditions on surviving until the given age of the outcome.Coefficients for each age are obtained from separate reduced form regressions of mortality on simulated years eligible, ages 0–18.The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at whichwe observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals.Table OA.16 contains corresponding results.
27
Table OA.16: Contemporaneous Mortality in Surviving Sample (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Female-0.003 0.001 -0.004 -0.005** -0.001 -0.001 -0.005 0.000 0.001 0.006*(0.003) (0.003) (0.004) (0.002) (0.003) (0.004) (0.003) (0.003) (0.004) (0.003)
Mean 0.037 0.037 0.038 0.040 0.039 0.041 0.042 0.046 0.046 0.051
Male-0.001 0.004 -0.001 0.006 -0.009** -0.013** 0.001 -0.002 -0.005 -0.009(0.004) (0.005) (0.004) (0.005) (0.004) (0.005) (0.004) (0.005) (0.005) (0.006)
Mean 0.098 0.111 0.120 0.125 0.126 0.129 0.125 0.121 0.120 0.121
All-0.002 0.003 -0.003 0.000 -0.005* -0.007** -0.002 -0.001 -0.002 -0.001(0.003) (0.003) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.004) (0.004)
Mean 0.068 0.075 0.080 0.084 0.083 0.086 0.084 0.084 0.084 0.087
Female Observations 4,913,139 4,911,340 4,909,502 4,907,631 4,905,658 4,903,748 4,901,740 4,899,659 4,897,398 4,895,129Male Observations 5,132,023 5,126,990 5,121,313 5,115,146 5,108,739 5,102,313 5,095,729 5,089,380 5,083,208 5,077,093All Observations 10,045,162 10,038,330 10,030,815 10,022,777 10,014,397 10,006,061 9,997,469 9,989,039 9,980,606 9,972,222
Contemporaneous Mortality (%)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous mortality indicates mortality ata given age, measured using SSA death records. Whereas our main sample conditions on surviving only until age 18, the surviving sample conditionson surviving until the given age of the outcome. Coefficients for each age are obtained from separate reduced form regressions of mortality on simulatedyears eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age atwhich we observe all individuals in our sample). Figure OA.9 presents this table graphically.
28
6.2 Mortality at Younger Ages
Examining the impact of Medicaid on mortality at ages younger than 19 would require
expanding our sample to include children who died during childhood, which would necessitate
changes to our instrument and specification because of data limitations.20 Therefore, because
we are interested in making comparisons by age across several outcomes holding the sample
and specification constant, we do not present impacts of Medicaid on mortality before the
age of 19. However, we do observe the Social Security Administration (SSA) date of death
for all children with a social security number (SSN), so we do report mean mortality by age
at ages younger than 19 to provide context for our results.
We present mean morality by age in Figure OA.10 and in Table OA.17. These mortality
rates are consistent with rates reported in SSA death tables. However, they understate
mortality from birth to age 1, which occurs before many children have an SSN. As shown,
there are very few deaths until age 12 or so, and then mortality rates increase dramatically
into adulthood.
Figure OA.10: Contemporaneous Mortality Over a Wide Age Range
Female Male All
0.0
5.1
.15
Mea
ns (
%)
0 4 8 12 16 20 24 28
0.0
5.1
.15
0 4 8 12 16 20 24 28Age
0.0
5.1
.15
0 4 8 12 16 20 24 28
Note. Contemporaneous mortality indicates mortality at a given age, measured using SSA death records. The sample differsfrom our main sample because we do not condition on survival until age 18. As in our main sample, the sample includes thedeceased so that it remains constant across all ages. Table OA.17 contains corresponding results.
20We never observe the linked parental tax records of children that died before 1996. Therefore, we cannotobserve several of the variables that we need to construct our instrument and covariates for children whodied before 1996, such as state of residence during childhood.
29
Table OA.17: Contemporaneous Mortality Over a Wide Age Range
(1) (2) (3) (4) (5) (6) (7) (8)Age 0 Age 1 Age 2 Age 3 Age 4 Age 5 Age 6 Age 7
Female Mean 0.028 0.017 0.013 0.012 0.012 0.012 0.013 0.013.Male Mean 0.034 0.020 0.017 0.015 0.015 0.016 0.017 0.017
All Mean 0.031 0.019 0.015 0.014 0.014 0.014 0.015 0.015
(9) (10) (11) (12) (13) (14) (15) (16)Age 8 Age 9 Age 10 Age 11 Age 12 Age 13 Age 14 Age 15
Female Mean 0.012 0.012 0.011 0.013 0.015 0.017 0.021 0.026
Male Mean 0.018 0.017 0.018 0.020 0.023 0.030 0.037 0.049
All Mean 0.015 0.015 0.015 0.016 0.019 0.023 0.030 0.038
(17) (18) (19) (20) (21) (22) (23) (24)Age 16 Age 17 Age 18 Age 19 Age 20 Age 21 Age 22 Age 23
Female Mean 0.037 0.040 0.043 0.043 0.044 0.045 0.046 0.046
Male Mean 0.071 0.088 0.112 0.129 0.130 0.142 0.142 0.140
All Mean 0.054 0.064 0.078 0.086 0.087 0.094 0.094 0.094
(25) (26) (27) (28) (29) (-) (-) (-)Age 24 Age 25 Age 26 Age 27 Age 28 - - -
Female Mean 0.050 0.050 0.054 0.055 0.061
Male Mean 0.140 0.136 0.132 0.131 0.136 - - -
All Mean 0.095 0.093 0.093 0.093 0.099
Female Observations 7,642,798 7,642,798 7,642,798 7,642,798 7,642,798 7,642,798 7,642,798 7,642,798Male Observations 7,831,277 7,831,277 7,831,277 7,831,277 7,831,277 7,831,277 7,831,277 7,831,277All Observations 15,474,075 15,474,075 15,474,075 15,474,075 15,474,075 15,474,075 15,474,075 15,474,075
Contemporaneous Mortality (%)
Note. Contemporaneous mortality indicates mortality at a given age, measured using SSA death records. The sample differsfrom our main sample because we do not condition on survival until age 18. As in our main sample, the sample includes thedeceased so that it remains constant across all ages. Figure OA.10 presents this table graphically.
30
Appendix 7 Supplemental Wage Income Results
7.1 Self-employment Results Figure
Figure OA.11: Self-employment (%)
-.3
-.2
-.1
0.1
.2 C
oeffi
cien
ts
19 22 25 28
Female
-.3
-.2
-.1
0.1
.2
19 22 25 28Age
Male
-.3
-.2
-.1
0.1
.2
19 22 25 28
All
02
46
8M
eans
19 22 25 28
02
46
8
19 22 25 28Age
02
46
8
19 22 25 28
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Self-employment indicates earning self-employment income contemporaneously at a given age, observed using ScheduleSE. Coefficients for each age are obtained from separate reduced form regressions of self-employment on simulated years eligible,ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngestage at which we observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidenceintervals. Table OA.18 contains corresponding results.
31
7.2
Self-e
mplo
ym
ent
Resu
ltsT
able
Table OA.18: Self-employment (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Self-employed (%)Female
-0.001 -0.009 0.004 0.025 -0.030 -0.023 -0.087 -0.126* -0.120 -0.072(0.036) (0.044) (0.060) (0.061) (0.048) (0.050) (0.068) (0.075) (0.072) (0.085)
Mean 1.419 1.949 2.549 3.334 4.109 4.750 5.345 5.894 6.394 6.889
Male-0.075* -0.029 -0.078 -0.041 -0.049 -0.039 -0.051 -0.025 -0.004 -0.031(0.038) (0.050) (0.053) (0.054) (0.065) (0.070) (0.073) (0.075) (0.076) (0.056)
Mean 2.159 2.698 3.263 4.085 4.976 5.678 6.214 6.635 6.947 7.308
All-0.038 -0.019 -0.038 -0.009 -0.039 -0.031 -0.068 -0.074 -0.060 -0.050(0.031) (0.043) (0.051) (0.053) (0.052) (0.053) (0.062) (0.068) (0.067) (0.058)
Mean 1.797 2.332 2.914 3.718 4.552 5.224 5.789 6.273 6.676 7.103
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Self-employment indicates earning self-employment incomecontemporaneously at a given age, observed using Schedule SE. Coefficients for each age are obtained from separate reduced form regressions of self-employment onsimulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at whichwe observe all individuals in our sample). Figure OA.11 presents this table graphically.
32
7.3 Log of Wage Income Results Figure
Figure OA.12: Log of Contemporaneous and Cumulative Wage Income
-.02
-.01
0.0
1.0
2.0
3 C
oeffi
cien
ts
19 22 25 28
Female
-.02
-.01
0.0
1.0
2.0
3
19 22 25 28Age
Male
-.02
-.01
0.0
1.0
2.0
3
19 22 25 28
All
02
46
810
Mea
ns
19 22 25 28
02
46
810
19 22 25 28Age
02
46
810
19 22 25 28
Contemporaneous Log of Wage Income
-.01
0.0
1.0
2.0
3 C
oeffi
cien
ts
19 22 25 28
Female
-.01
0.0
1.0
2.0
3
19 22 25 28Age
Male
-.01
0.0
1.0
2.0
3
19 22 25 28
All
05
1015
Mea
ns
19 22 25 28
05
1015
19 22 25 28Age
05
1015
19 22 25 28
Cumulative Log of Wage Income
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Log of contemporaneous wage income indicates the log of wages earned at a given age, obtained from Form W-2, adjustedto 2011 dollars and censored at $10 million. Log of cumulative wage income indicates the log of cumulative wage income earnedby a given age, starting at age 19. Individuals with zero wage income are excluded. Coefficients for each age are obtained fromseparate reduced form regressions of log of wage income on simulated years eligible, ages 0–18. The specification includes fixedeffects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individualsin our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Table OA.19 containscorresponding results.
33
7.4
Log
of
Wage
Inco
me
Resu
ltsT
able
Table OA.19: Log of Contemporaneous and Cumulative Wage Income
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Log of Contemporaneous Wage Income
Female
0.010 0.001 -0.002 0.004 0.009* 0.011 0.003 0.002 0.005 0.005
(0.007) (0.006) (0.005) (0.005) (0.005) (0.006) (0.008) (0.008) (0.007) (0.006)
Mean 8.022 8.290 8.486 8.766 9.117 9.380 9.540 9.655 9.750 9.827
Observations 4,296,498 4,335,999 4,319,558 4,328,621 4,333,409 4,309,312 4,240,579 4,165,911 4,086,575 4,012,090
Male
0.010 0.004 -0.005 -0.004 -0.000 0.001 0.006 0.004 -0.000 -0.001
(0.008) (0.006) (0.005) (0.005) (0.007) (0.009) (0.009) (0.009) (0.007) (0.006)
Mean 8.156 8.462 8.677 8.934 9.248 9.518 9.684 9.804 9.909 10.005
Observations 4,391,523 4,412,714 4,420,788 4,448,912 4,468,202 4,463,929 4,403,088 4,339,380 4,282,934 4,240,077
All
0.010 0.002 -0.003 0.000 0.004 0.006 0.005 0.003 0.002 0.002
(0.007) (0.006) (0.005) (0.005) (0.006) (0.007) (0.008) (0.008) (0.007) (0.006)
Mean 8.090 8.377 8.583 8.851 9.183 9.451 9.613 9.731 9.831 9.919
Observations 8,688,021 8,748,713 8,740,346 8,777,533 8,801,611 8,773,241 8,643,667 8,505,291 8,369,509 8,252,167
Log of Cumulative Wage Income
Female
0.010 0.006 0.003 0.004 0.006 0.008* 0.009* 0.009 0.009 0.010
(0.007) (0.007) (0.007) (0.006) (0.006) (0.005) (0.005) (0.006) (0.006) (0.007)
Mean 8.022 8.798 9.312 9.755 10.177 10.541 10.834 11.076 11.280 11.453
Observations 4,296,498 4,610,984 4,723,766 4,784,337 4,819,101 4,839,134 4,850,907 4,858,830 4,864,073 4,868,092
Male
0.010 0.005 -0.000 -0.002 -0.001 -0.000 0.002 0.003 0.003 0.002
(0.008) (0.008) (0.007) (0.006) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005)
Mean 8.156 8.932 9.451 9.883 10.285 10.643 10.937 11.180 11.388 11.570
Observations 4,391,523 4,749,414 4,886,041 4,960,541 5,004,965 5,032,195 5,048,486 5,059,544 5,067,718 5,074,117
All
0.010 0.006 0.001 0.001 0.002 0.004 0.006 0.006 0.006 0.006
(0.007) (0.007) (0.006) (0.006) (0.005) (0.004) (0.005) (0.005) (0.005) (0.005)
Mean 8.090 8.866 9.383 9.820 10.232 10.593 10.886 11.129 11.335 11.513
Observations 8,688,021 9,360,398 9,609,807 9,744,878 9,824,066 9,871,329 9,899,393 9,918,374 9,931,791 9,942,209
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Log of contemporaneous wage income indicates thelog of wages earned at a given age, obtained from Form W-2, adjusted to 2011 dollars and censored at $10 million. Log of cumulative wage incomeindicates the log of cumulative wage income earned by a given age, starting at age 19. Individuals with zero wage income are excluded. Coefficients foreach age are obtained from separate reduced form regressions of log of wage income on simulated years eligible, ages 0–18. The specification includesfixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).Figure OA.19 presents this table graphically.
34
Appendix 8 Supplemental EITC Results
8.1 Any EITC
Figure OA.13: Contemporaneous and Cumulative Any EITC (%)
-1.5
-1-.
50
.5 C
oeffi
cien
ts
19 22 25 28
Female
-1.5
-1-.
50
.5
19 22 25 28Age
Male
-1.5
-1-.
50
.5
19 22 25 28
All0
1020
30M
eans
19 22 25 28
0
1020
30
19 22 25 28Age
010
2030
19 22 25 28
Contemporaneous Any EITC
-2-1
.5-1
-.5
0 C
oeffi
cien
ts
19 22 25 28
Female
-2-1
.5-1
-.5
0
19 22 25 28Age
Male
-2-1
.5-1
-.5
0
19 22 25 28
All
010
2030
4050
Mea
ns
19 22 25 28
010
2030
4050
19 22 25 28Age
010
2030
4050
19 22 25 28
Cumulative Any EITC
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous EITC indicates whether the individual earned any EITC at a given age, obtained from Form 1040.Cumulative EITC indicates whether the individual earned any EITC by a given age, starting at age 19. Coefficients for eachage are obtained from separate reduced form regressions of any EITC on simulated years eligible, ages 0–18. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Table OA.20contains corresponding results.
35
Table OA.20: Log of Contemporaneous and Cumulative Any EITC (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Contemporaneous Any EITC (%)Female
-0.215* -0.508*** -0.604*** -0.705*** -0.722*** -0.779*** -0.855*** -0.792*** -0.728*** -0.671**(0.114) (0.152) (0.189) (0.253) (0.256) (0.242) (0.221) (0.258) (0.254) (0.264)
Mean 6.233 10.239 13.893 16.714 18.922 20.641 29.436 29.706 29.698 29.697
Male-0.096* -0.179** -0.248** -0.238* -0.289* -0.231 -0.496** -0.491** -0.396* -0.212(0.056) (0.079) (0.108) (0.139) (0.159) (0.173) (0.234) (0.218) (0.226) (0.239)
Mean 2.368 4.132 5.910 7.364 8.575 9.571 21.221 21.335 21.075 20.794
All-0.155* -0.341*** -0.424*** -0.469** -0.503** -0.501** -0.673*** -0.640*** -0.561** -0.438*(0.080) (0.108) (0.140) (0.187) (0.195) (0.193) (0.214) (0.224) (0.232) (0.241)
Mean 4.259 7.119 9.815 11.937 13.636 14.985 25.239 25.429 25.293 25.149
Cumulative Any EITC (%)
-0.215* -0.536*** -0.751*** -0.908*** -1.013*** -1.106*** -1.061*** -0.929*** -0.787** -0.748**(0.114) (0.172) (0.227) (0.293) (0.338) (0.356) (0.318) (0.321) (0.313) (0.316)
Mean 6.233 11.542 16.666 21.215 25.218 28.743 38.498 43.878 47.754 50.760
Male-0.096* -0.220** -0.359** -0.455** -0.523** -0.580** -0.737** -0.788** -0.716** -0.635*(0.056) (0.098) (0.142) (0.182) (0.223) (0.244) (0.278) (0.315) (0.342) (0.342)
Mean 2.368 4.880 7.729 10.622 13.476 16.223 28.634 35.615 40.571 44.352
All-0.155* -0.376*** -0.553*** -0.679*** -0.765*** -0.840*** -0.898*** -0.859*** -0.753** -0.692**(0.080) (0.127) (0.175) (0.229) (0.271) (0.289) (0.287) (0.309) (0.321) (0.323)
Mean 4.259 8.138 12.100 15.803 19.219 22.346 33.459 39.656 44.084 47.486
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous EITC indicates whether theindividual earned any EITC at a given age, obtained from Form 1040. Cumulative EITC indicates whether the individual earned any EITC by agiven age, starting at age 19. Coefficients for each age are obtained from separate reduced form regressions of any EITC on simulated years eligible,ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which weobserve all individuals in our sample). Figure OA.13 presents this table graphically.
36
Ap
pen
dix
9S
up
ple
menta
lT
ota
lT
axes
Resu
lts
9.1
Com
ponents
of
Tota
lT
axes:
Tab
les
Table OA.21: Contemporaneous Total Tax Components ($000)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
FemaleEITC
-0.006*** -0.013*** -0.017*** -0.023*** -0.026*** -0.030*** -0.037*** -0.040*** -0.039*** -0.033***(0.002) (0.003) (0.005) (0.006) (0.006) (0.007) (0.008) (0.009) (0.010) (0.010)
Mean 0.095 0.170 0.248 0.319 0.388 0.453 0.538 0.600 0.660 0.717% Change in Total Taxes 46% 62% 68% 55% 39% 34% 34% 34% 42% 29%
Payroll Taxes0.002 0.000 -0.001 0.006 0.016*** 0.023*** 0.020** 0.017 -0.004 -0.003
(0.002) (0.002) (0.003) (0.004) (0.005) (0.007) (0.009) (0.010) (0.011) (0.010)Mean 0.310 0.413 0.508 0.665 0.936 1.203 1.394 1.549 1.584 1.583% Change in Total Taxes 15% 0% - 4% 14% 24% 26% 18% 15% - 4% - 3%
Income Taxes + EITC0.004 0.008** 0.009** 0.013** 0.025** 0.035** 0.053*** 0.059** 0.059** 0.085**
(0.003) (0.004) (0.005) (0.006) (0.010) (0.015) (0.018) (0.023) (0.026) (0.032)Mean 0.175 0.240 0.314 0.469 0.859 1.308 1.657 1.999 2.361 2.775% Change in Total Taxes 31% 38% 36% 31% 38% 40% 48% 51% 63% 74%
MaleEITC
-0.003*** -0.006*** -0.008*** -0.009*** -0.012*** -0.010*** -0.015*** -0.017*** -0.015** -0.009(0.001) (0.002) (0.002) (0.003) (0.004) (0.004) (0.005) (0.005) (0.006) (0.006)
Mean 0.039 0.070 0.105 0.137 0.167 0.197 0.257 0.292 0.326 0.357% Change in Total Taxes 30% 55% 114% 90% 39% 19% 20% 23% 31% 15%
Payroll Taxes0.003 -0.001 -0.005 -0.005 0.001 0.008 0.011 0.009 -0.008 -0.010
(0.003) (0.003) (0.004) (0.005) (0.007) (0.010) (0.012) (0.012) (0.010) (0.011)Mean 0.362 0.499 0.626 0.806 1.082 1.392 1.624 1.818 1.882 1.915% Change in Total Taxes 30% - 9% - 71% - 50% 3% 15% 15% 12% - 16% - 16%
Income Taxes + EITC0.004 0.006 0.004 0.006 0.018 0.034* 0.048** 0.048** 0.043 0.062*
(0.003) (0.004) (0.005) (0.006) (0.011) (0.019) (0.021) (0.023) (0.026) (0.037)Mean 0.231 0.329 0.431 0.601 0.949 1.395 1.744 2.067 2.411 2.807% Change in Total Taxes 40% 55% 57% 60% 58% 64% 65% 65% 88% 102%
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous EITC indicates EITC earned at a givenage, obtained from Form 1040, adjusted to 2011 dollars. Contemporaneous payroll taxes indicate payroll taxes earned at a given age, defined as employeeportion of payroll taxes reported on Form W-2 across employers, only for the individuals of interest, and the taxes reported on Schedule SE for the selfemployed, both adjusted to 2011 dollars. Contemporaneous income taxes are defined as household federal tax payments less EITC at a given age, adjustedto 2011 dollars. Coefficients for each age are obtained from separate reduced form regressions of the given outcome on simulated years eligible, ages 0–18.The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals inour sample). Observation counts are reported in Table OA.22. The “% change in total taxes” due to each component is calculated as the ratio between thepoint estimate for the given component and the point estimate for total taxes at each age, adjusted by a factor of (-1) for the EITC component, which entersnegatively into the decomposition. For example, for women at age 28, 30% (=(-1)*(-0.041)/0.135) of the increase in contemporaneous total taxes due to anadditional year of Medicaid eligibility is due to a decrease in EITC. Figure OA.14 presents this table graphically.
37
Table OA.22: Contemporaneous Total Tax Components ($000), continued
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
AllEITC
-0.005*** -0.009*** -0.012*** -0.016*** -0.019*** -0.020*** -0.026*** -0.028*** -0.026*** -0.021***(0.001) (0.002) (0.003) (0.004) (0.005) (0.005) (0.006) (0.007) (0.007) (0.008)
Mean 0.066 0.119 0.175 0.226 0.275 0.323 0.395 0.443 0.489 0.533% Change in Total Taxes 42% 56% 75% 62% 40% 29% 28% 30% 37% 24%
Payroll Taxes0.003 -0.000 -0.003 0.000 0.008 0.015* 0.016 0.013 -0.006 -0.006
(0.002) (0.003) (0.003) (0.004) (0.005) (0.008) (0.010) (0.011) (0.010) (0.010)Mean 0.337 0.457 0.568 0.737 1.011 1.300 1.511 1.687 1.736 1.752% Change in Total Taxes 25% 0% - 19% 0% 17% 21% 17% 14% - 8% - 7%
Income Taxes + EITC0.004 0.007* 0.007 0.010 0.021** 0.035** 0.050** 0.053** 0.051* 0.073**
(0.003) (0.004) (0.004) (0.006) (0.010) (0.016) (0.019) (0.022) (0.026) (0.034)Mean 0.204 0.286 0.373 0.537 0.905 1.353 1.701 2.034 2.387 2.791% Change in Total Taxes 33% 44% 44% 38% 44% 50% 54% 56% 72% 83%
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Contemporaneous EITC indicates EITC earned ata given age, obtained from Form 1040, adjusted to 2011 dollars. Contemporaneous payroll taxes indicate payroll taxes earned at a given age, defined asemployee portion of payroll taxes reported on Form W-2 across employers, only for the individuals of interest, and the taxes reported on Schedule SEfor the self employed, both adjusted to 2011 dollars. Contemporaneous income taxes are defined as household federal tax payments less EITC at a givenage, adjusted to 2011 dollars. Coefficients for each age are obtained from separate reduced form regressions of the given outcome on simulated yearseligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which weobserve all individuals in our sample). The “% change in total taxes” due to each component is calculated as the ratio between the point estimate forthe given component and the point estimate for total taxes at each age, adjusted by a factor of (-1) for the EITC component, which enters negativelyinto the decomposition. For example, at age 28 in the full sample, 27% (=(-1)*(-0.030)/0.110) of the increase in contemporaneous total taxes due to anadditional year of Medicaid eligibility is due to decreases in EITC. Figure OA.14 presents this table graphically.
38
Table OA.23: Cumulative Total Tax Components ($000)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
FemaleEITC
-0.006*** -0.019*** -0.036*** -0.059*** -0.084*** -0.114*** -0.151*** -0.191*** -0.230*** -0.263***(0.002) (0.005) (0.009) (0.015) (0.022) (0.028) (0.035) (0.044) (0.053) (0.063)
Mean 0.095 0.264 0.512 0.831 1.219 1.672 2.210 2.810 3.470 4.188% Change in Total Taxes 46% 56% 61% 58% 50% 45% 41% 40% 40% 38%
Payroll Taxes0.002 0.002 0.002 0.007 0.023 0.046** 0.067*** 0.083** 0.079** 0.076*
(0.002) (0.004) (0.007) (0.011) (0.016) (0.019) (0.025) (0.032) (0.037) (0.042)Mean 0.310 0.722 1.230 1.895 2.832 4.034 5.428 6.977 8.562 10.144% Change in Total Taxes 15% 6% 3% 7% 14% 18% 18% 17% 14% 11%
Income Taxes + EITC0.004 0.012** 0.021** 0.035** 0.059** 0.094*** 0.147*** 0.206*** 0.265*** 0.350***
(0.003) (0.006) (0.010) (0.015) (0.023) (0.035) (0.051) (0.070) (0.092) (0.119)Mean 0.175 0.416 0.729 1.199 2.058 3.366 5.023 7.022 9.384 12.159% Change in Total Taxes 31% 35% 36% 35% 35% 37% 40% 43% 46% 51%
MaleEITC
-0.003*** -0.009*** -0.017*** -0.026*** -0.037*** -0.048*** -0.063*** -0.080*** -0.094*** -0.103***(0.001) (0.003) (0.005) (0.008) (0.011) (0.015) (0.018) (0.023) (0.029) (0.034)
Mean 0.039 0.109 0.214 0.351 0.519 0.716 0.973 1.265 1.591 1.948% Change in Total Taxes 30% 43% 61% 67% 54% 39% 32% 30% 29% 27%
Payroll Taxes0.003 0.003 -0.003 -0.008 -0.006 0.001 0.013 0.022 0.014 0.004
(0.003) (0.006) (0.009) (0.012) (0.017) (0.023) (0.031) (0.041) (0.047) (0.052)Mean 0.362 0.861 1.487 2.294 3.376 4.768 6.392 8.211 10.092 12.007% Change in Total Taxes 30% 14% - 11% - 21% - 9% 1% 7% 8% 4% 1%
Income Taxes + EITC0.004 0.010 0.015 0.021 0.038 0.073* 0.121** 0.168** 0.211** 0.273**
(0.003) (0.007) (0.011) (0.016) (0.024) (0.039) (0.058) (0.078) (0.100) (0.132)Mean 0.231 0.561 0.991 1.593 2.542 3.937 5.681 7.748 10.159 12.966% Change in Total Taxes 40% 48% 54% 54% 55% 60% 62% 62% 66% 72%
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative EITC indicates EITC earned by agiven age starting at age 19, obtained from Form 1040, adjusted to 2011 dollars. Cumulative payroll taxes indicate payroll taxes earned by a given agestarting at age 19, defined as employee portion of payroll taxes reported on Form W-2 across employers, only for the individuals of interest, and the taxesreported on Schedule SE for the self employed, both adjusted to 2011 dollars. Cumulative income taxes are defined as household federal tax paymentsless EITC by a given age starting at age 19, adjusted to 2011 dollars. Coefficients for each age are obtained from separate reduced form regressions ofthe given outcome on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residenceat age 15 (the youngest age at which we observe all individuals in our sample). Observation counts are reported in Table OA.24. The “% change intotal taxes” due to each component is calculated as the ratio between the point estimate for the given component and the point estimate for total taxesat each age, adjusted by a factor of (-1) for the EITC component, which enters negatively into the decomposition. For example, for women by age28, 40% (=(-1)*(-0.244)/0.603) of the increase in cumulative total taxes due to an additional year of Medicaid eligibility is due to decreases in EITC.Figure OA.14 presents this table graphically.
39
Table OA.24: Cumulative Total Tax Components ($000), continued
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
AllEITC
-0.005*** -0.014*** -0.026*** -0.042*** -0.061*** -0.080*** -0.106*** -0.135*** -0.161*** -0.182***(0.001) (0.004) (0.007) (0.011) (0.016) (0.020) (0.026) (0.032) (0.039) (0.046)
Mean 0.066 0.185 0.360 0.586 0.861 1.184 1.578 2.021 2.510 3.044% Change in Total Taxes 42% 50% 59% 61% 52% 43% 38% 36% 36% 34%
Payroll Taxes0.003 0.002 -0.001 -0.000 0.008 0.024 0.039 0.052 0.046 0.040
(0.002) (0.005) (0.008) (0.011) (0.015) (0.019) (0.026) (0.034) (0.039) (0.044)Mean 0.337 0.793 1.361 2.099 3.110 4.409 5.921 7.607 9.344 11.096% Change in Total Taxes 25% 7% - 2% 0% 7% 13% 14% 14% 10% 8%
Income Taxes + EITC0.004 0.011* 0.018* 0.028* 0.049** 0.083** 0.134** 0.187** 0.238** 0.311**
(0.003) (0.006) (0.010) (0.015) (0.023) (0.035) (0.053) (0.072) (0.094) (0.123)Mean 0.204 0.490 0.863 1.400 2.305 3.658 5.359 7.393 9.780 12.571% Change in Total Taxes 33% 39% 41% 41% 42% 44% 48% 50% 53% 58%
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative EITC indicates EITC earned by agiven age starting at age 19, obtained from Form 1040, adjusted to 2011 dollars. Cumulative payroll taxes indicate payroll taxes earned by a given agestarting at age 19, defined as employee portion of payroll taxes reported on Form W-2 across employers, only for the individuals of interest, and the taxesreported on Schedule SE for the self employed, both adjusted to 2011 dollars. Cumulative income taxes are defined as household federal tax paymentsless EITC by a given age starting at age 19, adjusted to 2011 dollars. Coefficients for each age are obtained from separate reduced form regressions ofthe given outcome on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence atage 15 (the youngest age at which we observe all individuals in our sample). The “% change in total taxes” due to each component is calculated as theratio between the point estimate for the given component and the point estimate for total taxes at each age, adjusted by a factor of (-1) for the EITCcomponent, which enters negatively into the decomposition. For example, by age 28 in the full sample, 37% (=(-1)*(-0.176)/0.471) of the increase incumulative total taxes due to an additional year of Medicaid eligibility is due to decreases in EITC. Figure OA.14 presents this table graphically.
40
9.2 Components of Total Taxes: Combined Figures
Figure OA.14: Contemporaneous and Cumulative Total Taxes and Total Tax Components ($000)
-.05
0.0
5.1
.15
Coe
ffici
ents
19 22 25 28
Female
-.05
0.0
5.1
.15
19 22 25 28Age
Male
-.05
0.0
5.1
.15
19 22 25 28
All
Total Taxes (Payroll+Income Taxes) EITC Payroll Taxes Income Taxes+EITC
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
01
23
4M
eans
19 22 25 28
01
23
4
19 22 25 28Age
01
23
4
19 22 25 28
Total Taxes (Payroll+Income Taxes) EITC Payroll Taxes Income Taxes+EITC
Contemporaneous Total Taxes and Total Tax Components ($000)
-.2
0.2
.4.6
.8C
oeffi
cien
ts
19 22 25 28
Female
-.2
0.2
.4.6
.8
19 22 25 28Age
Male
-.2
0.2
.4.6
.8
19 22 25 28
All
Total Taxes (Payroll+Income Taxes) EITC Payroll Taxes Income Taxes+EITC
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
Total Taxes (Payroll+Income Taxes) EITC Payroll Taxes Income Taxes+EITC
Cumulative Total Taxes and Total Tax Components ($000)
Note. Contemporaneous outcomes are measured at a given age, and cumulative outcomes are measured by a given age, startingat age 19. EITC was obtained from Form 1040, adjusted to 2011 dollars. Payroll taxes are defined as employee portion ofpayroll taxes reported on Form W-2 across employers, only for the individuals of interest, and the taxes reported on ScheduleSE for the self employed, both adjusted to 2011 dollars. Income taxes are defined as household federal tax payments lessEITC, adjusted to 2011 dollars. Coefficients for each age are obtained from separate reduced form regressions of the givenoutcome on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for stateof residence at age 15 (the youngest age at which we observe all individuals in our sample). Standard errors are clustered bystate. Tables OA.21, OA.22, OA.23, OA.24 contain corresponding results.
41
9.3 Components of Total Taxes: Separate Figures
Figure OA.15: Contemporaneous and Cumulative EITC ($000)
-.06
-.04
-.02
0 C
oeffi
cien
ts
19 22 25 28
Female
-.06
-.04
-.02
0
19 22 25 28Age
Male
-.06
-.04
-.02
0
19 22 25 28
All
0.2
.4.6
.8M
eans
19 22 25 28
0.2
.4.6
.8
19 22 25 28Age
0.2
.4.6
.8
19 22 25 28
Contemporaneous EITC ($000)
-.3
-.2
-.1
0 C
oeffi
cien
ts
19 22 25 28
Female
-.3
-.2
-.1
0
19 22 25 28Age
Male-.
3-.
2-.
10
19 22 25 28
All
01
23
4M
eans
19 22 25 28
01
23
4
19 22 25 28Age
01
23
4
19 22 25 28
Cumulative EITC ($000)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. We also present this figure as Figure 2e. Contemporaneous EITC indicates EITC earned at a given age, obtained fromForm 1040, adjusted to 2011 dollars. Cumulative EITC indicates EITC earned by a given age, starting at age 19. Coefficients foreach age are obtained from separate reduced form regressions of EITC on simulated years eligible, ages 0–18. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Table OA.6contains corresponding results.
42
Figure OA.16: Contemporaneous and Cumulative Payroll Taxes ($000)
-.01
0.0
1.0
2.0
3.0
4 C
oeffi
cien
ts
19 22 25 28
Female
-.01
0.0
1.0
2.0
3.0
4
19 22 25 28Age
Male
-.01
0.0
1.0
2.0
3.0
4
19 22 25 28
All
0.5
11.
52
Mea
ns
19 22 25 28
0.5
11.
52
19 22 25 28Age
0.5
11.
52
19 22 25 28
Contemporaneous Payroll Taxes ($000)
-.1
0.1
.2 C
oeffi
cien
ts
19 22 25 28
Female
-.1
0.1
.2
19 22 25 28Age
Male-.
10
.1.2
19 22 25 28
All
05
1015
Mea
ns
19 22 25 28
05
1015
19 22 25 28Age
05
1015
19 22 25 28
Cumulative Payroll Taxes ($000)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous payroll taxes indicate payroll taxes earned at a given age, defined as employee portion of payroll taxesreported on Form W-2 across employers, only for the individuals of interest, and the taxes reported on Schedule SE for theself employed, both adjusted to 2011 dollars. Cumulative payroll taxes indicate payroll taxes earned by a given age, startingat age 19. Coefficients for each age are obtained from separate reduced form regressions of payroll taxes on simulated yearseligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (theyoungest age at which we observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95%confidence intervals. Tables OA.21, OA.22, OA.23, OA.24 contain corresponding results.
43
Figure OA.17: Contemporaneous and Cumulative Income Taxes + EITC ($000)
0.0
5.1
.15
Coe
ffici
ents
19 22 25 28
Female
0.0
5.1
.15
19 22 25 28Age
Male
0.0
5.1
.15
19 22 25 28
All
01
23
Mea
ns
19 22 25 28
01
23
19 22 25 28Age
01
23
19 22 25 28
Contemporaneous Income Taxes + EITC ($000)
0.1
.2.3
.4.5
Coe
ffici
ents
19 22 25 28
Female
0.1
.2.3
.4.5
19 22 25 28Age
Male
0.1
.2.3
.4.5
19 22 25 28
All
05
1015
Mea
ns
19 22 25 28
05
1015
19 22 25 28Age
05
1015
19 22 25 28
Cumulative Income Taxes + EITC ($000)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Contemporaneous income taxes are defined as household federal tax payments less EITC at a given age, adjusted to 2011dollars. Cumulative income taxes indicate income taxes earned by a given age, starting at age 19. Coefficients for each ageare obtained from separate reduced form regressions of income taxes on simulated years eligible, ages 0–18. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe allindividuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals. Tables OA.21,OA.22, OA.23, OA.24 contain corresponding results.
44
Appendix 10 Heterogeneous Effects by Childhood Household FPL
10.1 College Enrollment
Figure OA.18: Cumulative College Enrollment (%) by Family FPL at Ages 15–18
01
23
4C
oeffi
cien
ts (
%)
19 22 25 28
Female
01
23
4
19 22 25 28Age
Male
01
23
4
19 22 25 28
All
<200% FPL 200% - 500% FPL >500% FPL
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
2040
6080
100
Mea
ns (
%)
19 22 25 28
2040
6080
100
19 22 25 28Age
2040
6080
100
19 22 25 28
<200% FPL 200% - 500% FPL >500% FPL
Cumulative Mortality
Note. Cumulative college enrollment indicates ever having enrolled in college by a given age, starting at age 19, observedthrough Form 1098-T, filed by educational institutions. Children are assigned to an % FPL bin if their household remainedin that bin at every age from 15–18. We exclude children with heterogeneity in their observed % FPL bin (32.2% of thesample). Coefficients for each age are obtained from separate reduced form regressions of college enrollment on simulated yearseligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (theyoungest age at which we observe all individuals in our sample). Standard errors are clustered by state. Table OA.25 containscorresponding results.
45
Table OA.25: Cumulative College Enrollment (%) by Family FPL at Ages 15–18
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Cumulative College (Ever Enrolled; %)High Impact Sample (< 200% FPL)
Female3.632*** 3.491*** 3.183*** 2.992*** 2.834*** 2.649*** 2.310*** 2.106*** 1.896*** 1.843***(0.765) (0.730) (0.703) (0.674) (0.644) (0.611) (0.570) (0.551) (0.520) (0.496)
Mean 44.417 51.237 55.584 58.696 61.052 63.116 65.017 66.779 68.380 69.769Observations 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145
Male3.743*** 3.668*** 3.344*** 3.297*** 3.221*** 3.161*** 2.971*** 2.715*** 2.576*** 2.482***(0.738) (0.733) (0.692) (0.681) (0.665) (0.639) (0.619) (0.589) (0.566) (0.548)
Mean 33.389 39.394 42.992 45.547 47.392 48.959 50.439 51.837 53.166 54.375Observations 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738
All3.675*** 3.565*** 3.247*** 3.128*** 3.011*** 2.888*** 2.624*** 2.393*** 2.218*** 2.145***(0.745) (0.721) (0.687) (0.668) (0.647) (0.617) (0.588) (0.565) (0.535) (0.514)
Mean 38.827 45.234 49.202 52.031 54.128 55.940 57.628 59.206 60.669 61.967Observations 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883
Female2.782*** 2.056*** 1.609*** 1.524*** 1.517*** 1.421*** 1.208*** 1.121*** 1.053*** 1.039***(0.437) (0.321) (0.320) (0.354) (0.320) (0.301) (0.282) (0.279) (0.270) (0.256)
Mean 72.139 77.517 80.319 82.045 83.212 84.187 85.059 85.871 86.573 87.188Observations 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380
Male3.338*** 2.519*** 2.134*** 2.040*** 2.006*** 1.948*** 1.867*** 1.749*** 1.646*** 1.584***(0.558) (0.464) (0.464) (0.481) (0.453) (0.426) (0.408) (0.399) (0.375) (0.360)
Mean 60.462 66.574 69.637 71.564 72.836 73.877 74.830 75.676 76.450 77.166Observations 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587
All3.069*** 2.294*** 1.879*** 1.790*** 1.769*** 1.691*** 1.546*** 1.444*** 1.358*** 1.319***(0.478) (0.376) (0.380) (0.411) (0.379) (0.355) (0.335) (0.328) (0.311) (0.296)
Mean 66.127 71.883 74.819 76.649 77.870 78.879 79.792 80.621 81.361 82.028Observations 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967
Female1.044*** 0.616*** 0.439*** 0.307** 0.306** 0.293** 0.246* 0.216* 0.207* 0.239**(0.275) (0.203) (0.144) (0.135) (0.132) (0.137) (0.127) (0.128) (0.123) (0.113)
Mean 89.482 92.902 94.412 95.104 95.493 95.784 96.022 96.242 96.424 96.584Observations 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259
Male0.856*** 0.602*** 0.477** 0.443** 0.440** 0.511*** 0.432** 0.363* 0.288 0.279(0.280) (0.216) (0.195) (0.191) (0.187) (0.185) (0.183) (0.186) (0.175) (0.168)
Mean 83.360 88.151 90.130 91.170 91.740 92.176 92.523 92.814 93.082 93.337Observations 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637
All0.936*** 0.601*** 0.452*** 0.370** 0.369** 0.399*** 0.336** 0.286** 0.244* 0.256**(0.261) (0.191) (0.152) (0.149) (0.144) (0.146) (0.142) (0.142) (0.133) (0.126)
Mean 86.360 90.479 92.228 93.098 93.579 93.944 94.238 94.494 94.720 94.928Observations 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Intermediate Impact Sample (200%-500% FPL)
Low Impact Sample (> 500% FPL)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulativecollege enrollment indicates ever having enrolled in college by a given age, starting at age 19, observed throughForm 1098-T, filed by educational institutions. Children are assigned to an % FPL bin if their household remainedin that bin at every age from 15–18. We exclude children with heterogeneity in their observed % FPL bin (32.2%of the sample). Coefficients for each age are obtained from separate reduced form regressions of college enrollmenton simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and forstate of residence at age 15 (the youngest age at which we observe all individuals in our sample). Figure OA.18presents this table graphically.
46
10.2 Fertility
Figure OA.19: Cumulative Fertility (%) by Family FPL at Ages 15–18-2
.5-2
-1.5
-1-.
50
Coe
ffici
ents
(%
)
19 22 25 28
Female
-2.5
-2-1
.5-1
-.5
0
19 22 25 28Age
Male
-2.5
-2-1
.5-1
-.5
0
19 22 25 28
All
<200% FPL 200% - 500% FPL >500% FPL
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
020
4060
Mea
ns (
%)
19 22 25 28
020
4060
19 22 25 28Age
020
4060
19 22 25 28
<200% FPL 200% - 500% FPL >500% FPL
Note. Cumulative fertility indicates if a dependent child is ever born by a given age, starting at age 19. If an individual everclaims a dependent child on a Form 1040, SSA records yield age at birth. Children are assigned to an % FPL bin if theirhousehold remained in that bin at every age from 15–18. We exclude children with heterogeneity in their observed % FPL bin(32.2% of the sample). Coefficients for each age are obtained from separate reduced form regressions of fertility on simulatedyears eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age15 (the youngest age at which we observe all individuals in our sample). Standard errors are clustered by state. Table OA.26contains corresponding results.
47
Table OA.26: Cumulative Fertility (%) by Family FPL at Ages 15–18
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
High Impact Sample (< 200% FPL)Female
-1.837*** -2.151*** -2.426*** -2.508*** -2.470*** -2.486*** -2.467*** -2.269*** -2.092*** -2.125***(0.349) (0.392) (0.410) (0.446) (0.479) (0.489) (0.491) (0.486) (0.467) (0.429)
Mean 24.642 31.138 36.611 41.425 45.534 49.214 52.577 55.599 58.353 60.579Observations 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145
Male-0.904*** -1.082*** -1.363*** -1.415*** -1.471*** -1.501*** -1.544*** -1.436*** -1.330*** -1.454***(0.200) (0.230) (0.271) (0.319) (0.351) (0.379) (0.391) (0.400) (0.389) (0.394)
Mean 13.247 17.263 21.276 25.227 29.014 32.557 35.785 38.668 41.274 43.414Observations 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738
All-1.380*** -1.627*** -1.907*** -1.975*** -1.985*** -2.009*** -2.022*** -1.871*** -1.731*** -1.811***(0.260) (0.293) (0.325) (0.368) (0.395) (0.414) (0.424) (0.424) (0.405) (0.389)
Mean 18.866 24.105 28.838 33.215 37.161 40.771 44.066 47.017 49.696 51.879Observations 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883
Female-0.699*** -1.041*** -1.320*** -1.566*** -1.768*** -1.856*** -1.988*** -2.087*** -2.224*** -2.219***(0.187) (0.244) (0.306) (0.341) (0.387) (0.408) (0.432) (0.444) (0.451) (0.491)
Mean 10.742 14.638 18.357 22.083 25.887 29.835 34.075 38.410 42.857 46.804Observations 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380
Male-0.235* -0.364** -0.574*** -0.735*** -0.843*** -1.021*** -1.148*** -1.258*** -1.307*** -1.273***(0.118) (0.142) (0.175) (0.205) (0.266) (0.322) (0.348) (0.375) (0.374) (0.343)
Mean 6.053 8.358 10.869 13.626 16.594 19.747 23.111 26.638 30.281 33.618Observations 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587
All-0.461*** -0.695*** -0.938*** -1.140*** -1.293*** -1.428*** -1.556*** -1.660*** -1.751*** -1.730***(0.143) (0.184) (0.229) (0.260) (0.314) (0.352) (0.376) (0.398) (0.399) (0.401)
Mean 8.327 11.404 14.502 17.729 21.102 24.641 28.430 32.349 36.382 40.015Observations 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967
Female-0.167 -0.262* -0.367* -0.456* -0.516* -0.655** -0.682** -0.811** -0.882** -0.908**(0.110) (0.153) (0.191) (0.252) (0.264) (0.290) (0.335) (0.385) (0.433) (0.443)
Mean 3.675 5.119 6.628 8.347 10.331 12.767 15.759 19.500 23.970 28.572Observations 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259
Male-0.078 -0.125 0.024 -0.023 -0.114 -0.277 -0.477** -0.578** -0.680*** -0.811***(0.083) (0.110) (0.120) (0.136) (0.169) (0.188) (0.196) (0.228) (0.242) (0.255)
Mean 2.196 3.023 4.001 5.162 6.568 8.335 10.491 13.124 16.327 19.781Observations 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637
All-0.120 -0.191* -0.167 -0.234 -0.310* -0.460** -0.575** -0.691** -0.780*** -0.860***(0.075) (0.105) (0.127) (0.160) (0.180) (0.203) (0.235) (0.265) (0.282) (0.304)
Mean 2.920 4.051 5.289 6.723 8.412 10.507 13.073 16.248 20.072 24.089Observations 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Low Impact Sample (> 500% FPL)
Simulated Years Eligible, Age 0-18
Cumulative Fertility (Dependent Child Ever Born; %)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Intermediate Impact Sample (200%-500% FPL)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulativefertility indicates if a dependent child is ever born by a given age, starting at age 19. If an individual ever claimsa dependent child on a Form 1040, SSA records yield age at birth. Children are assigned to an % FPL bin iftheir household remained in that bin at every age from 15–18. We exclude children with heterogeneity in theirobserved % FPL bin (32.2% of the sample). Coefficients for each age are obtained from separate reduced formregressions of fertility on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohortby month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).Figure OA.19 presents this table graphically.
48
10.3 Mortality
Figure OA.20: Cumulative Mortality (%) by Family FPL at Ages 15–18-.
1-.
050
.05
.1C
oeffi
cien
ts (
%)
19 22 25 28
Female
-.1
-.05
0.0
5.1
19 22 25 28
Age
Male
-.1
-.05
0.0
5.1
19 22 25 28
All
<200% FPL 200% - 500% FPL >500% FPL
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
0.5
11.
5M
eans
(%
)
19 22 25 28
0.5
11.
5
19 22 25 28Age
0.5
11.
5
19 22 25 28
<200% FPL 200% - 500% FPL >500% FPL
Cumulative Mortality
Note. Cumulative mortality indicates mortality by a given age, starting at age 19, measured using SSA death records. Childrenare assigned to an % FPL bin if their household remained in that bin at every age from 15–18. We exclude children withheterogeneity in their observed % FPL bin (32.2% of the sample). Coefficients for each age are obtained from separate reducedform regressions of mortality on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort bymonth and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Standarderrors are clustered by state. Table OA.27 contains corresponding results.
49
Table OA.27: Cumulative Mortality (%) by Family FPL at Ages 15–18
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Cumulative Mortality (%)High Impact Sample (< 200% FPL)
Female-0.014** -0.019*** -0.018 -0.024** -0.022 -0.026 -0.026 -0.028 -0.016 -0.006(0.006) (0.006) (0.011) (0.012) (0.014) (0.017) (0.017) (0.018) (0.020) (0.022)
Mean 0.040 0.081 0.126 0.171 0.216 0.265 0.316 0.374 0.427 0.490Observations 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145
Male-0.005 -0.001 -0.002 -0.010 -0.032* -0.057*** -0.060** -0.069*** -0.089*** -0.100***(0.008) (0.010) (0.011) (0.013) (0.016) (0.020) (0.023) (0.023) (0.025) (0.027)
Mean 0.112 0.240 0.377 0.523 0.669 0.820 0.967 1.109 1.254 1.393Observations 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738
All-0.009* -0.009 -0.010 -0.017** -0.026** -0.041*** -0.042*** -0.047*** -0.051*** -0.052***(0.005) (0.006) (0.008) (0.008) (0.011) (0.012) (0.014) (0.013) (0.014) (0.017)
Mean 0.076 0.162 0.253 0.349 0.446 0.546 0.646 0.746 0.846 0.948Observations 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883
Female0.003 0.007 -0.001 -0.006 -0.004 -0.016 -0.020 -0.026* -0.031* -0.022
(0.007) (0.009) (0.011) (0.012) (0.013) (0.014) (0.015) (0.014) (0.016) (0.016)Mean 0.036 0.070 0.104 0.142 0.178 0.212 0.251 0.293 0.336 0.379
Observations 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380
Male0.002 -0.010 -0.017 -0.015 -0.014 -0.031 -0.036 -0.030 -0.031 -0.048
(0.007) (0.015) (0.015) (0.021) (0.026) (0.030) (0.028) (0.032) (0.028) (0.033)Mean 0.091 0.191 0.302 0.414 0.528 0.641 0.750 0.855 0.959 1.066
Observations 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587
All0.003 -0.002 -0.009 -0.010 -0.009 -0.023 -0.028 -0.028 -0.031** -0.035**
(0.003) (0.009) (0.009) (0.011) (0.015) (0.018) (0.018) (0.019) (0.014) (0.017)Mean 0.065 0.132 0.206 0.282 0.358 0.433 0.508 0.582 0.657 0.733
Observations 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967
Female-0.000 0.012 0.002 -0.012 -0.006 -0.002 -0.001 -0.010 -0.014 -0.018(0.010) (0.012) (0.011) (0.013) (0.016) (0.019) (0.019) (0.017) (0.018) (0.016)
Mean 0.026 0.052 0.081 0.111 0.142 0.170 0.199 0.225 0.258 0.290Observations 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259
Male0.002 -0.001 -0.003 0.021 0.027 0.028 0.064** 0.081*** 0.068* 0.061
(0.009) (0.013) (0.015) (0.020) (0.025) (0.029) (0.028) (0.030) (0.035) (0.041)Mean 0.071 0.156 0.252 0.341 0.429 0.524 0.612 0.704 0.786 0.873
Observations 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637
All0.001 0.005 -0.001 0.005 0.011 0.013 0.032** 0.037** 0.028 0.023
(0.006) (0.008) (0.009) (0.013) (0.015) (0.017) (0.015) (0.017) (0.021) (0.023)Mean 0.049 0.105 0.168 0.228 0.288 0.351 0.410 0.469 0.527 0.587
Observations 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Intermediate Impact Sample (200%-500% FPL)
Low Impact Sample (> 500% FPL)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulativemortality indicates mortality by a given age, starting at age 19, measured using SSA death records. Children areassigned to an % FPL bin if their household remained in that bin at every age from 15–18. We exclude childrenwith heterogeneity in their observed % FPL bin (32.2% of the sample). Coefficients for each age are obtained fromseparate reduced form regressions of mortality on simulated years eligible, ages 0–18. The specification includesfixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observeall individuals in our sample). Figure OA.20 presents this table graphically.
50
10.4 Wage Income
Figure OA.21: Cumulative Wage Income ($000) by Family FPL at Ages 15–18-2
02
46
Coe
ffici
ents
19 22 25 28
Female
-20
24
6
19 22 25 28Age
Male
-20
24
6
19 22 25 28
All
<200% FPL 200% - 500% FPL >500% FPL
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
050
100
150
200
Mea
ns
19 22 25 28
050
100
150
200
19 22 25 28Age
050
100
150
200
19 22 25 28
<200% FPL 200% - 500% FPL >500% FPL
Cumulative Wage Income ($000)
Note. Cumulative wage income indicates wages earned by a given age, starting at age 19, obtained from Form W-2, adjustedto 2011 dollars and censored at $10 million. Children are assigned to an % FPL bin if their household remained in that bin atevery age from 15–18. We exclude children with heterogeneity in their observed % FPL bin (32.2% of the sample). Coefficientsfor each age are obtained from separate reduced form regressions of wage income on simulated years eligible, ages 0–18. Thespecification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which weobserve all individuals in our sample). Standard errors are clustered by state. Table OA.28 contains corresponding results.
51
Table OA.28: Cumulative Wage Income ($000) by Family FPL at Ages 15–18
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
High Impact Sample (< 200% FPL)Female
0.109 0.174 0.259 0.433 0.866** 1.559*** 2.308*** 3.014*** 3.773*** 4.711***(0.065) (0.122) (0.177) (0.258) (0.363) (0.471) (0.632) (0.843) (1.084) (1.319)
Mean 4.170 9.717 16.488 24.820 35.459 48.444 63.113 79.029 96.003 113.940Observations 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145
Male0.088 0.194 0.241 0.425 0.822** 1.536*** 2.424*** 3.288*** 4.215*** 5.274***
(0.064) (0.141) (0.207) (0.297) (0.399) (0.477) (0.622) (0.814) (1.060) (1.304)Mean 4.777 11.303 19.391 29.478 42.186 57.661 75.070 94.030 114.566 136.712
Observations 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738
All0.099 0.186 0.254 0.436 0.854** 1.562*** 2.383*** 3.170*** 4.018*** 5.025***
(0.061) (0.125) (0.186) (0.270) (0.366) (0.446) (0.588) (0.778) (1.012) (1.240)Mean 4.478 10.520 17.960 27.181 38.869 53.116 69.173 86.633 105.412 125.482
Observations 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883
Female-0.034 -0.096 -0.347** -0.343 0.073 0.758*** 1.417*** 2.077*** 2.891*** 4.130***(0.031) (0.084) (0.144) (0.212) (0.250) (0.269) (0.349) (0.497) (0.682) (0.921)
Mean 4.476 10.454 17.668 27.047 40.391 57.643 77.704 99.970 124.189 150.053Observations 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380
Male-0.016 -0.146 -0.466* -0.780* -0.784 -0.554 -0.034 0.286 0.492 1.214(0.050) (0.125) (0.262) (0.400) (0.510) (0.612) (0.797) (1.019) (1.212) (1.418)
Mean 5.240 12.408 21.293 32.630 47.869 67.529 90.509 116.326 145.002 176.423Observations 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587
All-0.025 -0.122 -0.408** -0.570* -0.371 0.080 0.669 1.154* 1.653* 2.624**(0.039) (0.085) (0.190) (0.295) (0.361) (0.406) (0.522) (0.683) (0.848) (1.040)
Mean 4.869 11.460 19.534 29.921 44.241 62.734 84.297 108.392 134.906 163.631Observations 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967
Female-0.037 -0.024 -0.175 -0.166 0.177 0.606* 0.620 0.544 0.550 1.226(0.037) (0.090) (0.137) (0.212) (0.263) (0.349) (0.482) (0.642) (0.812) (0.923)
Mean 3.029 6.975 11.856 19.568 33.665 53.620 77.522 105.020 135.968 170.040Observations 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259
Male0.010 -0.087 -0.285** -0.415** 0.023 0.458 0.537 -0.133 -0.089 1.044
(0.039) (0.075) (0.118) (0.164) (0.213) (0.377) (0.536) (0.635) (0.841) (1.428)Mean 3.515 8.235 14.191 22.773 37.249 58.566 84.958 116.023 152.031 193.235
Observations 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637
All-0.013 -0.056 -0.230** -0.292* 0.099 0.533* 0.584 0.214 0.250 1.174(0.035) (0.068) (0.108) (0.161) (0.200) (0.300) (0.416) (0.507) (0.629) (0.850)
Mean 3.277 7.618 13.046 21.202 35.492 56.142 81.314 110.631 144.159 181.868Observations 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Low Impact Sample (> 500% FPL)
Simulated Years Eligible, Age 0-18
Cumulative Wage Income ($000)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Intermediate Impact Sample (200%-500% FPL)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulativewage income indicates wages earned by a given age, starting at age 19, obtained from Form W-2, adjusted to2011 dollars and censored at $10 million. Children are assigned to an % FPL bin if their household remained inthat bin at every age from 15–18. We exclude children with heterogeneity in their observed % FPL bin (32.2%of the sample). Coefficients for each age are obtained from separate reduced form regressions of wage income onsimulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for stateof residence at age 15 (the youngest age at which we observe all individuals in our sample). Figure OA.21 presentsthis table graphically.
52
10.5 Earned Income Tax Credit (EITC)
Figure OA.22: Cumulative EITC ($000) by Family FPL at Ages 15–18-.
8-.
6-.
4-.
20
Coe
ffici
ents
19 22 25 28
Female
-.8
-.6
-.4
-.2
0
19 22 25 28Age
Male
-.8
-.6
-.4
-.2
0
19 22 25 28
All
<200% FPL 200% - 500% FPL >500% FPL
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
02
46
8M
eans
19 22 25 28
02
46
8
19 22 25 28Age
02
46
8
19 22 25 28
<200% FPL 200% - 500% FPL >500% FPL
Cumulative Mortality
Note. Cumulative EITC indicates EITC earned by a given age, starting at age 19, obtained from Form 1040, adjusted to 2011dollars. Children are assigned to an % FPL bin if their household remained in that bin at every age from 15–18. We excludechildren with heterogeneity in their observed % FPL bin (32.2% of the sample). Coefficients for each age are obtained fromseparate reduced form regressions of EITC on simulated years eligible, ages 0–18. The specification includes fixed effects forbirth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).Standard errors are clustered by state. Table OA.29 contains corresponding results.
53
Table OA.29: Cumulative EITC ($000) by Family FPL at Ages 15–18
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
High Impact Sample (< 200% FPL)Female
-0.019*** -0.057*** -0.109*** -0.176*** -0.255*** -0.344*** -0.444*** -0.550*** -0.658*** -0.767***(0.004) (0.011) (0.021) (0.034) (0.047) (0.061) (0.075) (0.092) (0.111) (0.130)
Mean 0.159 0.438 0.840 1.352 1.970 2.688 3.524 4.451 5.465 6.563Observations 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145
Male-0.010*** -0.030*** -0.059*** -0.093*** -0.133*** -0.173*** -0.218*** -0.264*** -0.309*** -0.349***(0.002) (0.007) (0.013) (0.019) (0.025) (0.032) (0.038) (0.047) (0.057) (0.064)
Mean 0.071 0.196 0.379 0.612 0.890 1.213 1.611 2.055 2.546 3.076Observations 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738
All-0.015*** -0.044*** -0.085*** -0.136*** -0.196*** -0.260*** -0.333*** -0.410*** -0.487*** -0.562***(0.003) (0.009) (0.017) (0.026) (0.036) (0.046) (0.056) (0.069) (0.083) (0.095)
Mean 0.114 0.316 0.606 0.977 1.423 1.941 2.554 3.236 3.985 4.796Observations 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883
Female-0.009*** -0.027*** -0.048*** -0.078*** -0.117*** -0.164*** -0.225*** -0.289*** -0.350*** -0.399***(0.002) (0.005) (0.010) (0.016) (0.023) (0.031) (0.041) (0.053) (0.066) (0.078)
Mean 0.054 0.157 0.315 0.524 0.783 1.089 1.463 1.884 2.349 2.859Observations 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380
Male-0.004*** -0.012*** -0.022*** -0.031*** -0.044*** -0.060*** -0.088*** -0.117*** -0.146*** -0.168***(0.001) (0.003) (0.005) (0.008) (0.012) (0.017) (0.023) (0.030) (0.036) (0.043)
Mean 0.019 0.057 0.118 0.201 0.306 0.435 0.617 0.828 1.067 1.333Observations 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587
All-0.007*** -0.019*** -0.034*** -0.054*** -0.079*** -0.110*** -0.154*** -0.200*** -0.244*** -0.280***(0.001) (0.004) (0.007) (0.011) (0.017) (0.023) (0.031) (0.040) (0.049) (0.059)
Mean 0.036 0.106 0.213 0.358 0.537 0.752 1.027 1.340 1.689 2.073Observations 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967
Female-0.001* -0.006*** -0.010*** -0.017*** -0.027*** -0.038*** -0.052*** -0.067*** -0.083*** -0.099***(0.001) (0.002) (0.003) (0.005) (0.008) (0.011) (0.015) (0.019) (0.024) (0.028)
Mean 0.013 0.038 0.080 0.138 0.214 0.305 0.434 0.581 0.746 0.928Observations 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259
Male-0.001* -0.002* -0.003 -0.003 -0.006 -0.009* -0.014** -0.025*** -0.035*** -0.043***(0.000) (0.001) (0.002) (0.003) (0.003) (0.005) (0.007) (0.008) (0.010) (0.011)
Mean 0.004 0.013 0.029 0.052 0.083 0.123 0.199 0.286 0.384 0.494Observations 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637
All-0.001** -0.004*** -0.006*** -0.010** -0.016*** -0.023*** -0.033*** -0.045*** -0.059*** -0.070***(0.001) (0.001) (0.002) (0.004) (0.005) (0.007) (0.009) (0.012) (0.015) (0.017)
Mean 0.008 0.026 0.054 0.094 0.147 0.212 0.314 0.431 0.561 0.706Observations 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Low Impact Sample (> 500% FPL)
Simulated Years Eligible, Age 0-18
Cumulative EITC ($000)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Intermediate Impact Sample (200%-500% FPL)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. CumulativeEITC indicates EITC earned by a given age, starting at age 19, obtained from Form 1040, adjusted to 2011 dollars.Children are assigned to an % FPL bin if their household remained in that bin at every age from 15–18. Weexclude children with heterogeneity in their observed % FPL bin (32.2% of the sample). Coefficients for eachage are obtained from separate reduced form regressions of EITC on simulated years eligible, ages 0–18. Thespecification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest ageat which we observe all individuals in our sample). Figure OA.22 presents this table graphically.
54
10.6 Total Taxes
Figure OA.23: Cumulative Total Taxes ($000) by Family FPL at Ages 15–180
.51
1.5
2C
oeffi
cien
ts
19 22 25 28
Female
0.5
11.
52
19 22 25 28
Age
Male
0.5
11.
52
19 22 25 28
All
<200% FPL 200% - 500% FPL >500% FPL
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
010
2030
40M
eans
19 22 25 28
010
2030
40
19 22 25 28Age
010
2030
40
19 22 25 28
<200% FPL 200% - 500% FPL >500% FPL
Cumulative Total Taxes ($000)
Note. We also present this figure as Figure 3. Cumulative total taxes indicate taxes paid by a given age, starting at age 19,defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Childrenare assigned to an % FPL bin if their household remained in that bin at every age from 15–18. We exclude children withheterogeneity in their observed % FPL bin (32.2% of the sample). Coefficients for each age are obtained from separate reducedform regressions of total taxes on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohortby month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Standarderrors are clustered by state. Table OA.30 contains corresponding results.
55
Table OA.30: Cumulative Total Taxes ($000) by Family FPL at Ages 15–18
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
High Impact Sample (< 200% FPL)Female
0.027*** 0.079*** 0.156*** 0.268*** 0.443*** 0.696*** 1.004*** 1.338*** 1.679*** 2.068***(0.009) (0.024) (0.043) (0.069) (0.102) (0.146) (0.201) (0.272) (0.353) (0.435)
Mean 0.302 0.646 1.015 1.490 2.233 3.285 4.491 5.817 7.174 8.588Observations 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145 1,711,145
Male0.020* 0.057** 0.110*** 0.186*** 0.304*** 0.492*** 0.719*** 0.960*** 1.198*** 1.473***(0.011) (0.024) (0.040) (0.057) (0.077) (0.107) (0.147) (0.204) (0.272) (0.343)
Mean 0.487 1.143 1.952 2.994 4.399 6.222 8.286 10.561 12.947 15.471Observations 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738 1,758,738
All0.024** 0.069*** 0.135*** 0.229*** 0.377*** 0.598*** 0.866*** 1.155*** 1.446*** 1.779***(0.010) (0.024) (0.042) (0.063) (0.089) (0.125) (0.171) (0.234) (0.308) (0.383)
Mean 0.396 0.898 1.490 2.252 3.331 4.774 6.414 8.222 10.100 12.076Observations 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883 3,469,883
Female0.011** 0.028** 0.039* 0.082** 0.204*** 0.397*** 0.647*** 0.920*** 1.186*** 1.551***(0.004) (0.011) (0.020) (0.031) (0.046) (0.067) (0.102) (0.153) (0.214) (0.295)
Mean 0.472 1.085 1.840 2.912 4.710 7.308 10.495 14.233 18.407 23.006Observations 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380 1,176,380
Male0.003 0.001 -0.020 -0.035 0.005 0.118 0.304** 0.498*** 0.695*** 0.974***
(0.008) (0.018) (0.033) (0.049) (0.065) (0.084) (0.119) (0.163) (0.212) (0.274)Mean 0.632 1.513 2.631 4.121 6.287 9.287 12.907 17.096 21.739 26.835
Observations 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587 1,248,587
All0.007 0.014 0.009 0.021 0.101** 0.252*** 0.470*** 0.702*** 0.932*** 1.253***
(0.006) (0.013) (0.023) (0.037) (0.049) (0.067) (0.101) (0.146) (0.200) (0.270)Mean 0.554 1.305 2.247 3.534 5.522 8.327 11.737 15.707 20.123 24.978
Observations 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967 2,424,967
Female-0.012** -0.008 0.002 0.046* 0.180*** 0.302*** 0.350*** 0.384** 0.470** 0.690***(0.005) (0.009) (0.016) (0.027) (0.044) (0.075) (0.107) (0.145) (0.183) (0.243)
Mean 0.369 0.825 1.408 2.456 4.793 8.460 13.145 18.922 25.755 33.781Observations 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259 452,259
Male-0.014*** -0.023** -0.035** -0.028 0.068 0.175** 0.224** 0.257* 0.370* 0.620**(0.005) (0.009) (0.015) (0.023) (0.045) (0.081) (0.111) (0.144) (0.191) (0.273)
Mean 0.457 1.057 1.838 3.047 5.378 9.134 13.966 19.859 26.752 34.786Observations 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637 470,637
All-0.013** -0.016* -0.017 0.009 0.123*** 0.238*** 0.287*** 0.321** 0.420** 0.656***(0.005) (0.008) (0.014) (0.022) (0.040) (0.071) (0.098) (0.127) (0.159) (0.220)
Mean 0.414 0.943 1.627 2.757 5.091 8.804 13.564 19.400 26.263 34.294Observations 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896 922,896
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Low Impact Sample (> 500% FPL)
Simulated Years Eligible, Age 0-18
Cumulative Total Taxes ($000)
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Intermediate Impact Sample (200%-500% FPL)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulativetotal taxes indicate taxes paid by a given age, starting at age 19, defined as household federal tax payments plusindividual payroll tax payments less EITC, adjusted to 2011 dollars. Children are assigned to an % FPL bin iftheir household remained in that bin at every age from 15–18. We exclude children with heterogeneity in theirobserved % FPL bin (32.2% of the sample). Coefficients for each age are obtained from separate reduced formregressions of total taxes on simulated years eligible, ages 0–18. The specification includes fixed effects for birthcohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in oursample). Figure 3 presents this table graphically.
56
10.7 Heterogeneous Effects by Parental Filing Status
The means in Figure OA.24 and Table OA.31 show that children whose parents file jointly pay
more taxes in adulthood, consistent with inter-generational persistence in income. However,
the coefficients show that children whose parents who do not file jointly experience impacts
of Medicaid that are almost twice as large. For each additional year of Medicaid eligibility
during childhood, cumulative total taxes by age 28 increase by $651 for children whose
parents do not file jointly, compared to $350 for children whose parents file jointly.
Figure OA.24: Cumulative Total Taxes ($000) by Parental Filing Status
0.2
.4.6
.8C
oeffi
cien
ts
19 22 25 28
Female0
.2.4
.6.8
19 22 25 28
Male
0.2
.4.6
.8
19 22 25 28
All
Main Results Parents Filing Jointly Parents Not Filing Jointly
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28
05
1015
2025
19 22 25 28
Main Results Parents Filing Jointly Parents Not Filing Jointly
Note. Cumulative total taxes indicate taxes paid by a given age, starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. We proxy for household structure using filing status,separately considering children with “parents filing jointly” at age 15—only those whose parents file as “married, filing jointly”—and all other children. Coefficients for each age are obtained from separate reduced form regressions of total taxes on simulatedyears eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age15 (the youngest age at which we observe all individuals in our sample). Standard errors are clustered by state. Table OA.31contains corresponding results.
57
Table OA.31: Cumulative Total Taxes ($000) by Parental Filing Status
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Joint Filing ParentsFemale
0.009** 0.025** 0.040** 0.065** 0.112** 0.173** 0.251*** 0.337** 0.399** 0.481**(0.004) (0.011) (0.019) (0.031) (0.048) (0.067) (0.093) (0.127) (0.162) (0.200)
Mean 0.436 0.996 1.684 2.680 4.407 6.929 10.028 13.686 17.801 22.396Observations 3,526,168 3,526,168 3,526,168 3,526,168 3,526,168 3,526,168 3,526,168 3,526,168 3,526,168 3,526,168
Male0.009 0.016 0.015 0.013 0.030 0.065 0.117 0.166 0.192 0.222
(0.006) (0.013) (0.020) (0.030) (0.046) (0.072) (0.107) (0.143) (0.180) (0.226)Mean 0.595 1.416 2.458 3.865 5.967 8.924 12.508 16.677 21.316 26.452
Observations 3,715,369 3,715,369 3,715,369 3,715,369 3,715,369 3,715,369 3,715,369 3,715,369 3,715,369 3,715,369
All0.009* 0.021* 0.027 0.039 0.071 0.119* 0.184* 0.251* 0.295* 0.350*(0.005) (0.011) (0.019) (0.030) (0.044) (0.065) (0.095) (0.130) (0.166) (0.207)
Mean 0.517 1.211 2.081 3.288 5.207 7.953 11.300 15.220 19.605 24.477Observations 7,241,537 7,241,537 7,241,537 7,241,537 7,241,537 7,241,537 7,241,537 7,241,537 7,241,537 7,241,537
Non-joint Filing ParentsFemale
0.020*** 0.050*** 0.097*** 0.168*** 0.254*** 0.367*** 0.507*** 0.639*** 0.743*** 0.854***(0.006) (0.015) (0.027) (0.044) (0.063) (0.088) (0.115) (0.148) (0.183) (0.229)
Mean 0.276 0.563 0.847 1.203 1.799 2.675 3.698 4.843 6.019 7.234Observations 1,386,971 1,386,971 1,386,971 1,386,971 1,386,971 1,386,971 1,386,971 1,386,971 1,386,971 1,386,971
Male0.012** 0.030** 0.053** 0.084** 0.124*** 0.181*** 0.265*** 0.348*** 0.396*** 0.459***(0.005) (0.013) (0.023) (0.033) (0.045) (0.064) (0.084) (0.105) (0.128) (0.163)
Mean 0.451 1.043 1.756 2.669 3.908 5.537 7.407 9.491 11.696 14.036Observations 1,416,654 1,416,654 1,416,654 1,416,654 1,416,654 1,416,654 1,416,654 1,416,654 1,416,654 1,416,654
All0.016*** 0.040*** 0.074*** 0.125*** 0.188*** 0.272*** 0.383*** 0.490*** 0.565*** 0.651***(0.005) (0.013) (0.024) (0.037) (0.052) (0.072) (0.094) (0.119) (0.146) (0.183)
Mean 0.364 0.805 1.306 1.944 2.865 4.121 5.572 7.192 8.888 10.671Observations 2,803,625 2,803,625 2,803,625 2,803,625 2,803,625 2,803,625 2,803,625 2,803,625 2,803,625 2,803,625
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxes indicate taxes paid by agiven age, starting at age 19, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars.We proxy for household structure using filing status, separately considering children with “parents filing jointly” at age 15—only those whose parentsfile as “married, filing jointly”—and all other children. Coefficients for each age are obtained from separate reduced form regressions of total taxeson simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (theyoungest age at which we observe all individuals in our sample). Standard errors are clustered by state. Figure OA.24 presents this table graphically.
58
Appendix 11 Heterogeneous Distributional Effects in the High
Impact Sample
Table OA.32: Heterogeneous Distributional Effects Within the High Impact Sample
(1)
Below Q1
%
(2)
Q1 to Q2
%
(3)
Q2 to Q3
%
(4)
Above Q3
%
Cumulative Total Taxes by Age 28
Female
-3.295** 0.475* 1.228** 1.593**
(0.676) (0.204) (0.283) (0.478)
Mean 43.917 21.532 19.723 14.829
Male
-2.384** -0.074 0.793** 1.665**
(0.475) (0.208) (0.185) (0.494)
Mean 27.531 30.501 23.574 18.393
All
-2.854** 0.209 1.011** 1.634**
(0.561) (0.179) (0.215) (0.479)
Mean 35.612 26.078 21.675 16.635
Cumulative Wage Income by Age 28
Female
-1.461* -0.283 0.155 1.589**
(0.567) (0.153) (0.288) (0.388)
Mean 33.081 28.588 23.186 15.146
Male
-1.504** -0.182 0.241 1.444**
(0.398) (0.175) (0.176) (0.415)
Mean 29.439 23.977 22.962 23.622
All-1.480*** -0.239* 0.193 1.526***
(0.470) (0.142) (0.211) (0.390)
Mean 31.235 26.251 23.072 19.442
Female Observations 1,711,145 1,711,145 1,711,145 1,711,145
Male Observations 1,758,738 1,758,738 1,758,738 1,758,738
All Observations 3,469,883 3,469,883 3,469,883 3,469,883
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. The outcomeis an indicator for being in the given quartile of the cumulative total taxes or wage income distribution for the fullsample at age 28. Cumulative total taxes indicate taxes paid by age 28 starting at age 19, defined as householdfederal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Cumulative wageincome indicates wages earned by age 28 starting at age 19, obtained from Form W-2, adjusted to 2011 dollarsand censored at $10 million. Coefficients are obtained from a reduced form regression of the outcome on simulatedyears eligible, ages 0–18, within the sample of children below 200% of the FPL from ages 15–18. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which weobserve all individuals in our sample).
59
Appendix 12 Heterogeneous Effects of Medicaid Eligibility at Dif-
ferent Ages
Figure OA.25: Heterogeneous Effects of Medicaid Eligibility at Different AgesCumulative Total Taxes ($000)
-.5
0.5
11.
5C
oeffi
cien
ts
19 22 25 28Age
05
1015
20M
eans
19 22 25 28Age
Ages 0-3 Ages 4-7 Ages 8-14 Ages 15-18
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Simulated Cumulative Eligibility:
Note. Cumulative total taxes indicate taxes paid by the given age, starting at age 19, defined as household federaltax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients for each agerange are obtained from a single reduced form regression of cumulative total taxes on the given vector of simulatedeligibility variables. The specification includes fixed effects for birth cohort by month and for state of residence atage 15 (the youngest age at which we observe all individuals in our sample). Table OA.33 contains correspondingresults.
60
Table OA.33: Heterogeneous Effects of Medicaid Eligibility at Different AgesCumulative Total Taxes ($000)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Main Specification0.012** 0.028** 0.044** 0.069** 0.118*** 0.187*** 0.279*** 0.374*** 0.445*** 0.533***(0.005) (0.011) (0.020) (0.031) (0.044) (0.061) (0.087) (0.119) (0.152) (0.192)
Exposure throughout childhood-0.015 -0.080 -0.164 -0.204 -0.125 0.095 0.361 0.570 0.827 1.299*(0.021) (0.052) (0.108) (0.152) (0.161) (0.217) (0.340) (0.437) (0.515) (0.653)0.044* 0.112** 0.170** 0.210 0.199 0.137 0.166 0.260 0.257 0.104(0.024) (0.051) (0.084) (0.130) (0.178) (0.226) (0.286) (0.340) (0.403) (0.551)0.004 0.016 0.027 0.037 0.056 0.079 0.114 0.156 0.184 0.217
(0.007) (0.015) (0.027) (0.044) (0.064) (0.083) (0.100) (0.113) (0.121) (0.137)0.019** 0.042*** 0.069** 0.115*** 0.195*** 0.309*** 0.446*** 0.581*** 0.683*** 0.810***(0.007) (0.016) (0.026) (0.042) (0.064) (0.090) (0.123) (0.160) (0.195) (0.236)
Mean 0.475 1.098 1.865 2.913 4.554 6.883 9.701 12.980 16.613 20.623Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-3Simulated Years Eligible, Age 4-7Simulated Years Eligible, Age 8-14Simulated Years Eligible, Age 15-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxes indicate taxes paid by the given age, starting atage 19, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients for each age range in “ChildhoodEligibility by Age” are obtained from a single reduced form regression of cumulative total taxes on the given vector of simulated eligibility variables. The specificationincludes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Figure OA.25presents this table graphically.
61
Appendix 13 Robustness to Gender as an Outcome: Falsification
Exercise
Table OA.34: Robustness to Gender as an Outcome
Female (%)-0.030(0.065)
Mean 48.911
Observations 10,045,162
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Coefficients are obtainedfrom a reduced form regression of an indicator for gender on simulated years eligible, ages 0–18. The specification includes fixedeffects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals inour sample).
62
Appendix 14 Robustness to Assumptions in Early Childhood
14.1 Robustness to Simulated Eligibility in the CPS
Figure OA.26: Robustness to Simulated Eligibility in the CPSCumulative Total Taxes ($000)
0.2
5.5
.75
11.
25C
oeffi
cien
ts
19 22 25 28
Female
0.2
5.5
.75
11.
25
19 22 25 28Age
Male
0.2
5.5
.75
11.
25
19 22 25 28
All
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
Simulated Years Eligible, age 0-18 Simulated Years Eligible using CPS, age 0-18
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative total taxes indicate taxes paid by the given age, starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtained from separate reduced formregressions of cumulative total taxes on simulated years eligible, ages 0–18, calculated in our main data and in the CPS sample.The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at whichwe observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals.
63
Table OA.35: Cumulative Total Taxes ($000): Robustness to Simulated Eligibility in the CPS
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Female0.015*** 0.039*** 0.068*** 0.114*** 0.184*** 0.275*** 0.391*** 0.512*** 0.609*** 0.731***(0.005) (0.013) (0.024) (0.039) (0.056) (0.077) (0.103) (0.137) (0.174) (0.216)
Mean 0.391 0.874 1.447 2.263 3.671 5.728 8.241 11.189 14.475 18.115
Male0.012* 0.025* 0.034 0.045 0.077 0.129* 0.206* 0.282** 0.332* 0.395*(0.006) (0.014) (0.022) (0.033) (0.047) (0.072) (0.104) (0.139) (0.173) (0.220)
Mean 0.555 1.313 2.264 3.535 5.399 7.989 11.100 14.693 18.661 23.025
All0.014** 0.032** 0.051** 0.079** 0.130** 0.201*** 0.297*** 0.395*** 0.469*** 0.560***(0.005) (0.013) (0.022) (0.035) (0.049) (0.069) (0.097) (0.130) (0.165) (0.208)
Mean 0.475 1.098 1.865 2.913 4.554 6.883 9.701 12.980 16.613 20.623
Female0.013*** 0.034*** 0.059*** 0.101*** 0.167*** 0.255*** 0.365*** 0.481*** 0.574*** 0.689***(0.004) (0.011) (0.021) (0.034) (0.050) (0.068) (0.093) (0.125) (0.160) (0.200)
Mean 0.391 0.874 1.447 2.263 3.671 5.728 8.241 11.189 14.475 18.115
Male0.010* 0.021* 0.028 0.039 0.069 0.122* 0.196** 0.270** 0.319** 0.380*(0.006) (0.012) (0.020) (0.029) (0.042) (0.063) (0.092) (0.125) (0.157) (0.200)
Mean 0.555 1.313 2.264 3.535 5.399 7.989 11.100 14.693 18.661 23.025
All0.012** 0.028** 0.044** 0.069** 0.118*** 0.187*** 0.279*** 0.374*** 0.445*** 0.533***(0.005) (0.011) (0.020) (0.031) (0.044) (0.061) (0.087) (0.119) (0.152) (0.192)
Mean 0.475 1.098 1.865 2.913 4.554 6.883 9.701 12.980 16.613 20.623
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Cumulative Total Taxes ($000)
Simulated Years Eligible using CPS, Age 0-18
Simulated Years Eligible using CPS, Age 0-18
Simulated Years Eligible using CPS, Age 0-18
Cumulative Total Taxes ($000)
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxes indicate taxes paid by the given age, starting atage 19, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtained from separate reducedform regressions of cumulative total taxes on simulated years eligible, ages 0–18, calculated in our main data and in the CPS sample. The specification includes fixed effectsfor birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Figure OA.26 presents this table graphically.
64
14.2 Robustness to Restricting Variation in State of Residence
Figure OA.27: Robustness to Restricting Variation in State of ResidenceCumulative Total Taxes ($000)
0.2
.4.6
.81
Coe
ffici
ents
19 22 25 28
Female
0.2
.4.6
.81
19 22 25 28
Male
0.2
.4.6
.81
19 22 25 28
All
Main Results >1 States of Residence Constant State of Residence
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28
05
1015
2025
19 22 25 28
Main Results >1 States of Residence Constant State of Residence
Note. Cumulative total taxes indicate taxes paid by the given age, starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtained from separate reduced formregressions of cumulative total taxes on simulated years eligible, ages 0–18, for those who lived in more than one state betweenages 15–18 (“>1 States of Residence”), for those who did not (“Constant State of Residence”), and for the full sample (“MainResults”). The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngestage at which we observe all individuals in our sample). Standard errors are clustered by state.
65
Table OA.36: Cumulative Total Taxes ($000): Robustness to Restricting Variation in State of Residence
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Female0.013** 0.031** 0.048* 0.078** 0.127** 0.190** 0.268*** 0.334*** 0.350** 0.376**(0.006) (0.014) (0.025) (0.038) (0.054) (0.072) (0.094) (0.122) (0.148) (0.172)
Mean 0.392 0.877 1.453 2.274 3.691 5.764 8.296 11.268 14.582 18.254Observations 187,631 187,631 187,631 187,631 187,631 187,631 187,631 187,631 187,631 187,631
Male0.015* 0.030* 0.036 0.040 0.057 0.089 0.138 0.173 0.168 0.164(0.008) (0.016) (0.025) (0.035) (0.050) (0.071) (0.098) (0.126) (0.151) (0.180)
Mean 0.556 1.316 2.271 3.547 5.419 8.023 11.151 14.767 18.760 23.153Observations 195,520 195,520 195,520 195,520 195,520 195,520 195,520 195,520 195,520 195,520
All0.014** 0.031** 0.043* 0.059 0.092* 0.139** 0.202** 0.253** 0.258* 0.269(0.007) (0.015) (0.024) (0.036) (0.050) (0.066) (0.089) (0.117) (0.142) (0.167)
Mean 0.476 1.101 1.871 2.924 4.574 6.918 9.755 13.056 16.717 20.757Observations 383,151 383,151 383,151 383,151 383,151 383,151 383,151 383,151 383,151 383,151
Female0.012*** 0.039*** 0.079*** 0.138*** 0.219*** 0.325*** 0.441*** 0.583*** 0.750*** 0.943***(0.003) (0.006) (0.010) (0.017) (0.028) (0.039) (0.055) (0.075) (0.102) (0.133)
Mean 0.362 0.798 1.296 1.985 3.151 4.831 6.858 9.208 11.777 14.625Observations 4,725,508 4,725,508 4,725,508 4,725,508 4,725,508 4,725,508 4,725,508 4,725,508 4,725,508 4,725,508
Male0.001 0.007 0.016 0.037* 0.074** 0.130*** 0.197*** 0.278*** 0.352*** 0.452***
(0.003) (0.007) (0.013) (0.019) (0.029) (0.039) (0.052) (0.067) (0.086) (0.110)Mean 0.526 1.230 2.098 3.240 4.883 7.133 9.791 12.834 16.152 19.789
Observations 4,936,503 4,936,503 4,936,503 4,936,503 4,936,503 4,936,503 4,936,503 4,936,503 4,936,503 4,936,503
All0.006** 0.022*** 0.046*** 0.085*** 0.143*** 0.224*** 0.314*** 0.424*** 0.543*** 0.688***(0.003) (0.006) (0.010) (0.016) (0.024) (0.032) (0.043) (0.059) (0.079) (0.105)
Mean 0.446 1.019 1.705 2.626 4.035 6.005 8.355 11.058 14.010 17.260Observations 9,662,011 9,662,011 9,662,011 9,662,011 9,662,011 9,662,011 9,662,011 9,662,011 9,662,011 9,662,011
Constant State of Residence
> 1 State of Residence
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxes indicate taxes paid by the given age, starting atage 19, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtained from separate reducedform regressions of cumulative total taxes on simulated years eligible, ages 0–18, for those who lived in more than one state between ages 15–18 (“>1 States of Residence”)and for those who did not (“Constant State of Residence”). The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngestage at which we observe all individuals in our sample). Figure OA.27 presents this table graphically.
66
Appendix 15 Robustness to Sibling Controls and Family Fixed
Effects
Figure OA.28: Robustness to Sibling Controls and Family Fixed Effectsfor Cumulative Total Taxes ($000)
-.5
0.5
1C
oeffi
cien
ts
19 22 25 28
Main Specification
-.5
0.5
1
19 22 25 28Age
Sibling Controls
-.5
0.5
1
19 22 25 28
Family FEs
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
05
1015
20M
eans
19 22 25 28
05
1015
20
19 22 25 28Age
05
1015
20
19 22 25 28
Note. Cumulative total taxes indicate taxes paid by the given age, starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtained from separate reduced formregressions of cumulative total taxes on simulated years eligible, ages 0–18, using the sample of households with two children.The “Sibling Controls” specification controls for the sibling’s tax outcome at the age equal to the age of the specificationoutcome. The “Family FEs” specification includes fixed effects for the household that claims both children. Standard errorsare clustered by state. Dashed lines show 95% confidence intervals.
67
Figure OA.29: Robustness to Size of Household for Cumulative Total Taxes ($000)
-.5
0.5
1C
oeffi
cien
ts
19 22 25 28
One Child
-.5
0.5
1
19 22 25 28Age
Two Children
-.5
0.5
1
19 22 25 28
≥ Three Children
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
05
1015
20M
eans
19 22 25 28
05
1015
20
19 22 25 28Age
05
1015
20
19 22 25 28
Note. Cumulative total taxes indicate taxes paid by the given age, starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtained from separate reduced formregressions of cumulative total taxes on simulated years eligible, ages 0–18. Standard errors are clustered by state. Dashedlines show 95% confidence intervals.
68
Appendix 16 Robustness to Sample Selection
Figure OA.30: Robustness to Sample SelectionCumulative Total Taxes ($000)
0.2
.4.6
.8C
oeffi
cien
ts
19 22 25 28
Female
0.2
.4.6
.8
19 22 25 28
Male
0.2
.4.6
.8
19 22 25 28
All
Main Results Non-filers
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28
05
1015
2025
19 22 25 28
Main Results Non-filers
Note. Cumulative total taxes indicate taxes paid by the given age, starting at age 19, defined as household federal tax paymentsplus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtained from separate reduced formregressions of cumulative total taxes on simulated years eligible, ages 0–18. Children in the non-filers sample were claimed bya parent in 1997 who did not file taxes at some point between the first observed age and 18. The specification includes fixedeffects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals inour sample). In the non-filers sample, we impute state at age 15, number of siblings at age 15, and family income at age 15 byusing values from the closest available filing year, and we include a control for non-filing. Table OA.37 contains correspondingresults. Standard errors are clustered by state.
69
Table OA.37: Cumulative Total Taxes ($000): Robustness to Sample Selection
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Non-Filers
Female
0.015*** 0.039*** 0.066*** 0.109*** 0.174*** 0.262*** 0.373*** 0.486*** 0.570*** 0.669***
(0.005) (0.013) (0.023) (0.036) (0.052) (0.069) (0.092) (0.121) (0.149) (0.184)
Mean 0.369 0.821 1.352 2.102 3.389 5.263 7.530 10.178 13.114 16.365
Observations 6,308,122 6,308,122 6,308,122 6,308,122 6,308,122 6,308,122 6,308,122 6,308,122 6,308,122 6,308,122
Male
0.012** 0.024* 0.031 0.038 0.065 0.113* 0.179* 0.244** 0.279* 0.322*
(0.006) (0.013) (0.021) (0.030) (0.041) (0.063) (0.091) (0.121) (0.149) (0.188)
Mean 0.538 1.271 2.192 3.419 5.199 7.648 10.558 13.900 17.573 21.612
Observations 6,544,866 6,544,866 6,544,866 6,544,866 6,544,866 6,544,866 6,544,866 6,544,866 6,544,866 6,544,866
All
0.013** 0.031** 0.048** 0.074** 0.119*** 0.187*** 0.275*** 0.364*** 0.424*** 0.494***
(0.005) (0.012) (0.022) (0.032) (0.044) (0.061) (0.085) (0.114) (0.141) (0.176)
Mean 0.455 1.050 1.780 2.773 4.311 6.477 9.072 12.074 15.385 19.037
Observations 12,852,988 12,852,988 12,852,988 12,852,988 12,852,988 12,852,988 12,852,988 12,852,988 12,852,988 12,852,988
Female
0.013*** 0.034*** 0.059*** 0.101*** 0.167*** 0.255*** 0.365*** 0.481*** 0.574*** 0.689***
(0.004) (0.011) (0.021) (0.034) (0.050) (0.068) (0.093) (0.125) (0.160) (0.200)
Mean 0.391 0.874 1.447 2.263 3.671 5.728 8.241 11.189 14.475 18.115
Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male
0.010* 0.021* 0.028 0.039 0.069 0.122* 0.196** 0.270** 0.319** 0.380*
(0.006) (0.012) (0.020) (0.029) (0.042) (0.063) (0.092) (0.125) (0.157) (0.200)
Mean 0.555 1.313 2.264 3.535 5.399 7.989 11.100 14.693 18.661 23.025
Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All
0.012** 0.028** 0.044** 0.069** 0.118*** 0.187*** 0.279*** 0.374*** 0.445*** 0.533***
(0.005) (0.011) (0.020) (0.031) (0.044) (0.061) (0.087) (0.119) (0.152) (0.192)
Mean 0.475 1.098 1.865 2.913 4.554 6.883 9.701 12.980 16.613 20.623
Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Main Results
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxes indicate taxes paid by the given age,starting at age 19, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Coefficients are obtainedfrom separate reduced form regressions of cumulative total taxes on simulated years eligible, ages 0–18. Children in the non-filers sample were claimed by a parentin 1997 who did not file taxes at some point between the first observed age and 18. The specification includes fixed effects for birth cohort by month and for stateof residence at age 15 (the youngest age at which we observe all individuals in our sample). In the non-filers sample, we impute state at age 15, number of siblingsat age 15, and family income at age 15 by using values from the closest available filing year, and we include a control for non-filing. Figure OA.30 presents this table graphically.
70
Appendix 17 Robustness to OLS, IV, and Income Controls
17.1 OLS, IV, and Income Controls
Figure OA.31: OLS and IV Results, Without and With Income ControlsCumulative Total Taxes ($000)
-1.5
-1.2
-.9
-.6
-.3
0 C
oeffi
cien
ts
19 22 25 28
Female
-1.5
-1.2
-.9
-.6
-.3
0
19 22 25 28Age
Male
-1.5
-1.2
-.9
-.6
-.3
0
19 22 25 28
All
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
OLS without Income Controls
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
-1.5
-1.2
-.9
-.6
-.3
0 C
oeffi
cien
ts
19 22 25 28
Female-1
.5-1
.2-.
9-.
6-.
30
19 22 25 28Age
Male
-1.5
-1.2
-.9
-.6
-.3
0
19 22 25 28
All
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
OLS with Income Controls
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
0.3
.6.9
1.2
1.5
C
oeffi
cien
ts
19 22 25 28
Female
0.3
.6.9
1.2
1.5
19 22 25 28Age
Male0
.3.6
.91.
21.
5
19 22 25 28
All
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
IV without Income Controls
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
0.3
.6.9
1.2
1.5
C
oeffi
cien
ts
19 22 25 28
Female
0.3
.6.9
1.2
1.5
19 22 25 28Age
Male
0.3
.6.9
1.2
1.5
19 22 25 28
All
05
1015
2025
Mea
ns
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
IV with Income Controls
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative total taxes indicate taxes paid by a given age, starting at age 19. Coefficients for each age are obtained fromthe given regression of total taxes on the respective measure of eligibility. All specifications includes fixed effects for birth cohortby month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). Standarderrors are clustered by state. Where indicated, specifications include “income controls”: birth year fixed effects interactedwith linear splines of total positive household income at age 15 on the parents’ tax return with knots at deciles of the sampledistribution, re-estimated for every sample. Standard errors are clustered by state. Dashed lines show 95% confidence intervals.
71
Figure OA.32: Main Results (Reduced Form), Without and With Income ControlsCumulative Total Taxes ($000)
0.2
.4.6
.81
Coefficients
19 22 25 28
Female
0.2
.4.6
.81
19 22 25 28Age
Male
0.2
.4.6
.81
19 22 25 28
All
05
1015
2025
Means
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
Cumulative Total Taxes ($000) without Income Controls
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
.2
0.2
.4.6
.8 C
oefficients
19 22 25 28
Female
.2
0.2
.4.6
.8
19 22 25 28Age
Male
.2
0.2
.4.6
.8
19 22 25 28
All
05
1015
2025
Means
19 22 25 28
05
1015
2025
19 22 25 28Age
05
1015
2025
19 22 25 28
Cumulative Total Taxes ($000) with Income Controls
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Cumulative total taxes indicate taxes paid by a given age, starting at age 19. Coefficients for each age are obtained fromseparate reduced form regressions of total taxes on simulated years eligible, ages 0–18. Both specifications include fixed effectsfor birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in oursample). Where indicated, specifications include “income controls”: birth year fixed effects interacted with linear splines of totalpositive household income at age 15 on the parents’ tax return with knots at deciles of the sample distribution, re-estimatedfor every sample. Standard errors are clustered by state. Dashed lines show 95% confidence intervals.
72
17.2 OLS, IV, and Income Controls: Table at Age 28
Table OA.38: Total Taxes ($000) by Age 28 across Income Control Sets and Specification
(1) (2)
Female Male All Female Male AllOLS
Years Eligible, Age 0-18 -1.352*** -1.068*** -1.211*** -0.149** -0.114** -0.133**(0.063) (0.050) (0.056) (0.032) (0.026) (0.029)
IVYears Eligible, Age 0-18 0.742*** 0.402* 0.568** 0.420* 0.191 0.303*
-0.243 -0.219 -0.221 (0.159) (0.172) (0.159)Reduced Form
0.689*** 0.380* 0.533*** 0.451* 0.207 0.326*(0.200) (0.200) (0.192) (0.170) (0.187) (0.172)
Mean 18.115 23.025 20.623 18.115 23.025 20.623Observations 4,913,139 5,132,023 10,045,162 4,913,139 5,132,023 10,045,162
No Income Controls Income Controls
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxesindicate taxes paid by a given age, starting at age 19. Coefficients are obtained from the given regression of cumulative totaltaxes by age 28 on the respective measure of eligibility. All specifications include fixed effects for birth cohort by month andfor state of residence at age 15 (the youngest age at which we observe all individuals in our sample). The specifications withincome controls incorporate the interaction of birth year with a linear spline of total positive household income at age 15 onthe parents’ tax return with knots at deciles of the sample distribution. The specification titled “Ages 15–18 Income Splines”incorporates the interaction of birth year with separate linear splines of total positive household income at ages 15–18 on theparents’ tax return with knots at deciles of the sample distribution, re-estimated for every sample.
73
17.3 Robustness to Richer Income Controls
Table OA.39: Robustness to Richer Income Controls Using Results for Cumulative Total Taxes($000)
(1) (2) (3)
Female Male All Female Male All Female Male AllReduced Form
0.689*** 0.380* 0.533*** 0.451* 0.207 0.326* 0.406** 0.171 0.286(0.200) (0.200) (0.192) (0.170) (0.187) (0.172) (0.173) (0.187) (0.173)
Mean 18.115 23.025 20.623 18.115 23.025 20.623 18.115 23.025 20.623Observations 4,913,139 5,132,023 10,045,162 4,913,139 5,132,023 10,045,162 4,913,139 5,132,023 10,045,162
No Income Controls Age 15 Income Splines Age 15-18 Income Splines
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative total taxesindicate taxes paid by a given age, starting at age 19. Coefficients are obtained from a reduced form regression of cumulativetotal taxes by age 28 on simulated years eligible, ages 0–18. All specifications include fixed effects for birth cohort by monthand for state of residence at age 15 (the youngest age at which we observe all individuals in our sample). The specificationtitled “Age 15 Income Splines” incorporates the interaction of birth year with a linear spline of total positive household incomeat age 15 on the parents’ tax return with knots at deciles of the sample distribution, re-estimated for every sample.. Thespecification titled “Ages 15–18 Income Splines” incorporates the interaction of birth year with separate linear splines of totalpositive household income at ages 15–18 on the parents’ tax return with knots at deciles of the sample distribution, re-estimatedfor every sample.
Appendix 18 Forecast of Fiscal Return on Investment
Through a simple comparison of coefficients, we find that the government recoups 67 cents
of each dollar that it spends on childhood Medicaid by age 28. To determine the fiscal return
on investment at older ages, we forecast how total taxes evolve due to childhood Medicaid
later in adulthood. As in Section 3.6, we divide total taxes into three components—EITC,
payroll taxes, and income taxes plus EITC (gross income taxes). These components evolve
and respond differently to childhood Medicaid from ages 19–28, as shown in Figure OA.14.
Therefore, we allow them to evolve and respond differently at age 29 and older. Using
a random 1% sample of individuals with any connection to the tax system since 1996, we
estimate how these components evolve over the life cycle by calculating average EITC, payroll
taxes, and gross income taxes for individuals at each age from 29–60 in 2013, including zeros
for individuals who do not file in 2013, discounted to birth at 0%, 1%, 2%, and 3% rates.
We report the means of each component by age in Table OA.40.
Next, we calculate the contemporaneous percent change in each component due to Med-
icaid at age 28, the oldest age at which we observe all individuals in our main sample. As
implied by the IV coefficients and means in Table OA.41, at a 0% discount rate, each addi-
tional year of Medicaid eligibility results in a 4.1% (=0.022/0.533) decrease in EITC, a 0.4%
(=-(-0.007/1.752)) decrease in payroll taxes, and a 2.8% (=0.078/2.791) increase in gross
income taxes at age 28. We assume that the percent change in each component due to Med-
icaid is the same at older ages as it is at age 28. We then calculate the implied cumulative
74
increase in total taxes due to Medicaid at each age, including the cumulative increase from
19–28. Finally, we compare the increase in taxes to the increase in spending to forecast the
fiscal return on investment.21
The results in Table OA.42, show that Medicaid delivers a positive return at all reported
discount rates at age 32, delivering an 3.18% return at a 3% discount rate. The returns at
age 32 are not surprising, given that the discounted fiscal return on investment is already
quite large at age 28. The returns are much larger at older ages, although we place little
emphasis on them because the forecast likely becomes less accurate at older ages.
21For example, consider the undiscounted fiscal ROI forecast at age 29. At age 29, as shown in TableOA.40, mean EITC is $585, so the implied 4.1% decrease is $24; mean payroll taxes are $1,831, so theimplied 0.4% decrease is $7, and mean gross income taxes is $2,738, so the implied 2.1% increase is $77.Across these components, the implied increase in total taxes at age 29 is $94 (=24-7+77). Therefore, thecumulative increase in total taxes through age 29 is $662 (=94 + 568, from the total taxes IV coefficientfrom ages 19–28), and the undiscounted ROI at age 29 is 4% (=(662-636)/636), as reported in Table OA.42.
75
Table OA.40: Mean Discounted Components of Total Taxes ($000): Age 29–60
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
EITC
($000)
Payroll
Taxes
($000)
Income Taxes
+ EITC
($000)
EITC
($000)
Payroll
Taxes
($000)
Income Taxes
+ EITC
($000)
EITC
($000)
Payroll
Taxes
($000)
Income Taxes
+ EITC
($000)
EITC
($000)
Payroll
Taxes
($000)
Income Taxes
+ EITC
($000)
Age 29 0.585 1.831 2.738 0.438 1.372 2.052 0.329 1.031 1.542 0.248 0.777 1.162
Age 30 0.609 1.881 3.125 0.452 1.396 2.319 0.336 1.039 1.725 0.251 0.775 1.288
Age 31 0.612 1.933 3.359 0.449 1.420 2.468 0.331 1.046 1.818 0.245 0.773 1.344
Age 32 0.610 2.018 3.708 0.443 1.468 2.697 0.323 1.071 1.968 0.237 0.784 1.440
Age 33 0.568 2.112 3.977 0.409 1.521 2.864 0.295 1.099 2.069 0.214 0.796 1.499
Age 34 0.589 2.121 4.134 0.420 1.512 2.947 0.301 1.082 2.108 0.216 0.776 1.513
Age 35 0.589 2.128 4.320 0.416 1.502 3.050 0.295 1.064 2.160 0.209 0.756 1.535
Age 36 0.554 2.240 4.926 0.388 1.566 3.443 0.272 1.098 2.415 0.191 0.773 1.700
Age 37 0.568 2.281 5.214 0.393 1.578 3.608 0.273 1.096 2.506 0.190 0.764 1.747
Age 38 0.533 2.299 5.401 0.366 1.575 3.700 0.251 1.083 2.545 0.174 0.748 1.756
Age 39 0.553 2.347 5.738 0.375 1.592 3.892 0.256 1.084 2.651 0.175 0.741 1.812
Age 40 0.534 2.441 5.877 0.359 1.640 3.947 0.242 1.106 2.661 0.164 0.748 1.801
Age 41 0.487 2.469 6.532 0.324 1.642 4.344 0.216 1.096 2.900 0.145 0.735 1.944
Age 42 0.483 2.420 5.957 0.318 1.593 3.922 0.210 1.053 2.593 0.140 0.699 1.721
Age 43 0.416 2.539 6.744 0.271 1.655 4.396 0.178 1.083 2.878 0.117 0.712 1.892
Age 44 0.406 2.496 6.950 0.262 1.611 4.486 0.170 1.044 2.908 0.111 0.680 1.893
Age 45 0.404 2.475 6.792 0.258 1.582 4.340 0.166 1.015 2.786 0.107 0.655 1.796
Age 46 0.380 2.532 7.204 0.241 1.602 4.558 0.153 1.018 2.897 0.098 0.650 1.850
Age 47 0.366 2.496 7.231 0.229 1.564 4.530 0.144 0.984 2.851 0.091 0.622 1.802
Age 48 0.350 2.446 6.878 0.217 1.517 4.266 0.135 0.945 2.659 0.085 0.592 1.665
Age 49 0.306 2.408 6.794 0.188 1.479 4.172 0.116 0.912 2.574 0.072 0.566 1.596
Age 50 0.277 2.403 6.965 0.168 1.461 4.235 0.103 0.893 2.588 0.063 0.548 1.589
Age 51 0.285 2.428 7.350 0.172 1.461 4.425 0.104 0.884 2.677 0.063 0.538 1.628
Age 52 0.246 2.377 7.648 0.147 1.417 4.559 0.088 0.849 2.731 0.053 0.511 1.644
Age 53 0.214 2.457 7.602 0.126 1.450 4.486 0.075 0.860 2.661 0.045 0.513 1.587
Age 54 0.203 2.375 7.452 0.119 1.388 4.354 0.070 0.815 2.558 0.041 0.481 1.510
Age 55 0.171 2.291 7.736 0.099 1.325 4.475 0.057 0.771 2.603 0.034 0.451 1.522
Age 56 0.166 2.364 7.641 0.095 1.354 4.377 0.055 0.780 2.521 0.032 0.452 1.460
Age 57 0.147 2.240 7.336 0.084 1.271 4.160 0.048 0.725 2.373 0.027 0.416 1.361
Age 58 0.124 2.169 7.655 0.069 1.218 4.298 0.039 0.688 2.427 0.022 0.391 1.378
Age 59 0.120 2.122 7.135 0.067 1.180 3.967 0.037 0.660 2.218 0.021 0.371 1.247
Age 60 0.093 2.100 7.736 0.051 1.156 4.258 0.028 0.640 2.358 0.016 0.356 1.313
Discount rate = 0% Discount rate = 1% Discount rate = 2% Discount rate = 3%
Note. EITC was obtained from Form 1040, adjusted to 2011 dollars. Payroll taxes are defined as employee portion of payrolltaxes reported on Form W-2 across employers, only for the individuals of interest, and the taxes reported on Schedule SE for theself employed, both adjusted to 2011 dollars. Income taxes are defined as household federal tax payments less EITC, adjustedto 2011 dollars. We estimate mean EITC, payroll taxes, and income taxes plus EITC using a random 1% sample of individualswith any connection to the tax system since 1996. From this sample, we present average outcomes by age, including zeros forindividuals who do not file in 2013. We discount all data to birth using the given discount rate.
76
Table OA.41: Discounted Spending, Total Taxes, and Total Tax Components ($000)
(1) (2) (3) (4) (5)
Medicaid Spending ($000)
Total Taxes ($000)
EITC ($000)
Payroll Taxes ($000)
Income Taxes + EITC ($000)
Age 0-18 Age 19-28 Age 28 Age 28 Age 28
Discount rate = 0%0.636*** 0.568** 0.022** -0.007 0.078**(0.059) (0.221) (0.009) (0.011) (0.037)
Mean 1.804 20.623 0.533 1.752 2.791 Discount rate = 1%
0.558*** 0.430** 0.017** -0.005 0.059**(0.051) (0.167) (0.007) (0.008) (0.028)
Mean 1.584 15.609 0.404 1.326 2.112Discount rate = 2%
0.491*** 0.326** 0.013** -0.004 0.045**(0.045) (0.127) (0.005) (0.006) (0.021)
Mean 1.396 11.846 0.306 1.006 1.603Discount rate = 3%
0.433*** 0.248** 0.010** -0.003 0.034**(0.040) (0.096) (0.004) (0.005) (0.016)
Mean 1.234 9.014 0.233 0.766 1.220
Years Eligible, Age 0-18
Years Eligible, Age 0-18
Years Eligible, Age 0-18
Years Eligible, Age 0-18
Cumulative Contemporaneous
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Cumulative Medicaidtakeup and spending for ages 0–18 are estimated in the full sample using administrative data from the Medicaid StatisticalInformation System (MSIS), adjusted to 2011 dollars. Cumulative total taxes indicate taxes paid in the full sample from ages19–28, defined as household federal tax payments plus individual payroll tax payments less EITC, adjusted to 2011 dollars. Alltotal tax components (EITC, payroll taxes, and income taxes plus EITC) are measured at age 28. EITC was obtained fromForm 1040, adjusted to 2011 dollars. Payroll taxes are defined as employee portion of payroll taxes reported on Form W-2 acrossemployers, only for the individuals of interest, and the taxes reported on Schedule SE for the self employed, both adjusted to2011 dollars. Income taxes are defined as household federal tax payments less EITC, adjusted to 2011 dollars. Coefficients areobtained from an IV regression of the given outcome on years eligible, ages 0–18. The specification includes fixed effects forbirth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individuals in our sample).We discount all data to birth using the given discount rate.
77
Table OA.42: Forecast of Fiscal Return on Investment in Medicaid (%)
(1)Discount rate = 0%
(2)Discount rate = 1%
(3)Discount rate = 2%
(4)Discount rate = 3%
Age 19-29 4.06 -8.00 -18.68 -28.13Age 19-30 20.67 6.06 -6.79 -18.07Age 19-31 38.30 20.82 5.58 -7.72Age 19-32 57.39 36.66 18.72 3.18Age 19-33 77.35 53.05 32.18 14.23Age 19-34 98.13 69.95 45.93 25.41Age 19-35 119.72 87.34 59.93 36.69Age 19-36 143.69 106.45 75.16 48.84Age 19-37 168.99 126.41 90.93 61.29Age 19-38 194.88 146.65 106.75 73.66Age 19-39 222.35 167.91 123.21 86.41Age 19-40 250.26 189.28 139.59 98.98Age 19-41 280.73 212.40 157.14 112.31Age 19-42 308.67 233.38 172.91 124.17Age 19-43 339.57 256.35 190.01 136.91Age 19-44 371.33 279.74 207.24 149.62Age 19-45 402.40 302.39 223.77 161.69Age 19-46 435.10 325.99 240.82 174.03Age 19-47 467.84 349.38 257.56 186.02Age 19-48 498.96 371.39 273.16 197.08Age 19-49 529.43 392.74 288.13 207.60Age 19-50 560.48 414.27 303.09 218.01Age 19-51 593.27 436.79 318.58 228.68Age 19-52 627.14 459.81 334.26 239.38Age 19-53 660.54 482.30 349.43 249.63Age 19-54 693.27 504.11 363.99 259.37Age 19-55 727.09 526.43 378.75 269.15Age 19-56 760.41 548.20 393.00 278.51Age 19-57 792.35 568.86 406.40 287.21Age 19-58 825.57 590.14 420.06 296.00Age 19-59 856.52 609.76 432.53 303.95Age 19-60 889.95 630.75 445.75 312.29
Note. As an example of the ROI calculation, consider the undiscounted fiscal ROI forecast at age 29. We assume that the totaltax components at ages beyond age 28 have the same percentage change due to Medicaid as at age 28. For example, considerthe undiscounted fiscal ROI forecast at age 29. At age 29, as shown in Table OA.40, mean EITC is $585, so the implied 4.1%decrease is $24; mean payroll taxes are $1,831, so the implied 0.4% decrease is $7, and mean gross income taxes is $2,738, sothe implied 2.1% increase is $77. Across these components, the implied increase in total taxes at age 29 is $94 (=24-7+77).Therefore, the cumulative increase in total taxes through age 29 is $662 (=94 + 568, from the total taxes IV coefficient fromages 19–28), and the undiscounted ROI at age 29 is 4% (=(662-636)/636), as reported in Table OA.42. We discount all datato birth using the given discount rate.
78
Appendix 19 First Stage Results
Table OA.43: First Stage Results
Years Eligible for Medicaid, Age 0-18
Female Male All
0.929*** 0.945*** 0.937***
(0.075) (0.079) (0.077)
Observations 4,913,139 5,132,023 10,045,162
Simulated Years Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Coefficients are obtainedfrom a regression of years eligible for Medicaid, ages 0–18, on simulated years eligible, ages 0–18. The specification includesfixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at which we observe all individualsin our sample).
Appendix 20 Filing and Marriage Results
Although the impact of Medicaid on marriage is interesting and potentially consistent with
our fertility and college enrollment results, we do not include marriage alongside our six
main outcomes because our observation of marriage is conditional on filing status, while
our observation of other outcomes is not. For example, we observe income tax when an
individual files a Form 1040, but we know that non-filers pay zero income tax, and we can
observe payroll tax on the employer-filed Form W-2 regardless of whether the individual files.
In contrast, we only observe that an individual is married if an individual files a Form 1040
as “married, filing jointly” or “married, filing separately.” We consider individuals who file
a Form 1040 with another status to be unmarried, and we omit non-filers.
Before turning to our marriage results, we first investigate the relationship between Med-
icaid eligibility and filing by estimating (1) with an indicator for contemporaneous filing at
each age as the outcome. As shown in the means in Figure OA.33 and Table OA.44, rates
of filing are not stable across ages, so we could observe changes in marriage that are entirely
driven by changes in filing behavior. At age 19, 76% of females and 74% of males file taxes.
The mean filing rate increases to 90% of females and 84% of males by age 28.
As shown in the coefficients in Figure OA.33 and Table OA.44, we find small and imprecise
effects of Medicaid eligibility on the probability of filing. For women, the coefficient at age
19 suggests that an additional year of Medicaid eligibility decreases the probability of filing
by 0.49 percentage points on a base of 76.3%. The coefficient is negative and small by age
28 when 90.5% of females file.
79
We present contemporaneous marriage coefficients and means in Figure OA.34. At age
19, an additional year of Medicaid eligibility reduces the likelihood of being married by 0.12
percentage points on a base of 4.2%. The negative effect of Medicaid on marriage increases
in magnitude until age 25, when it levels out at a reduction of around 0.80 percentage points
on a base of 24.0%.
20.1 Filing Results Figure
Figure OA.33: Filed a Tax Return (%)
.5
0.5
11.5
Coefficients (%)
19 22 25 28
Female.5
0.5
11.5
19 22 25 28Age
Male
.5
0.5
11.5
19 22 25 28
All
020
4060
80100
Means (%)
19 22 25 28
020
4060
80100
19 22 25 28Age
020
4060
80100
19 22 25 28
Cumulative Filed a Tax Return
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. The outcome represents an indicator function for whether or not an individual filed a tax return (Form 1040). Coefficientsfor each age are obtained from separate reduced form regressions of filing a tax return on simulated years eligible, ages 0–18.The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at whichwe observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95% confidence intervals.Table OA.44 contains corresponding results.
80
20.2
Filin
gR
esu
ltsT
able
Table OA.44: Filed a Tax Return (%)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Female
0.485 0.022 -0.042 0.011 -0.000 -0.043 -0.037 -0.021 -0.088 -0.108
(0.336) (0.262) (0.177) (0.114) (0.111) (0.112) (0.138) (0.146) (0.115) (0.099)
Mean 76.271 79.988 81.904 84.747 87.772 89.387 90.214 90.676 90.574 90.479
Male
0.491 0.040 -0.007 0.032 -0.054 0.015 0.024 0.173 0.103 0.152
(0.322) (0.268) (0.179) (0.139) (0.137) (0.156) (0.148) (0.178) (0.161) (0.148)
Mean 73.838 76.395 77.799 79.837 82.369 83.848 84.435 84.657 84.193 83.794
All
0.487 0.031 -0.025 0.021 -0.029 -0.014 -0.007 0.076 0.008 0.023
(0.325) (0.258) (0.166) (0.119) (0.116) (0.127) (0.134) (0.152) (0.131) (0.118)
Mean 75.028 78.152 79.807 82.239 85.012 86.557 87.262 87.601 87.314 87.064
Female Observations 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139 4,913,139
Male Observations 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023 5,132,023
All Observations 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162 10,045,162
Filed a Tax Return (%)
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Years Eligible,
Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. The outcome represents an indicator function for whether or notan individual filed a tax return (Form 1040) at a given age. Coefficients for each age are obtained from separate reduced form regressions of an indicator having fileda return on simulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngestage at which we observe all individuals in our sample). Figure OA.33 presents this table graphically.
81
20.3 Marriage Results Figure
Figure OA.34: Marital Status (Indicated “Married” Status on Tax Return; %)
1.5
1.5
0.5
Coefficients(%
)
19 22 25 28
Female
1.5
1.5
0.5
19 22 25 28Age
Male
1.5
1.5
0.5
19 22 25 28
All
010
2030
4050
Means(%
)
19 22 25 28
010
2030
4050
19 22 25 28Age
010
2030
4050
19 22 25 28
Cumulative Marital Status (Indicated Married Status on Tax Return)
p<0.01 0.01<p<0.05 0.05<p<0.1 p>0.1
Note. Marital status indicates filing a tax return (Form 1040) using the filing status “married, filing jointly” or “married, filingseparately.” Coefficients for each age are obtained from separate reduced form regressions of marital status on simulated yearseligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (theyoungest age at which we observe all individuals in our sample). Standard errors are clustered by state. Dashed lines show 95%confidence intervals. Table OA.45 contains corresponding results.
82
20.4
Marria
ge
Resu
ltsT
able
Table OA.45: Marital Status (Indicated “Married” Status on Tax Return; %)
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Age 19 Age 20 Age 21 Age 22 Age 23 Age 24 Age 25 Age 26 Age 27 Age 28
Marital Status (Indicated "Married'' Status on Tax Return; %)
Female
-0.207 -0.384* -0.468* -0.455 -0.623* -0.775** -0.918*** -0.952*** -0.778*** -0.710***
(0.133) (0.215) (0.254) (0.303) (0.315) (0.308) (0.298) (0.282) (0.257) (0.252)
Mean 6.215 9.992 14.072 18.508 23.167 27.966 32.579 36.908 40.882 44.438
Male
-0.019 -0.136 -0.198 -0.263 -0.342 -0.520* -0.674** -0.798*** -0.799*** -0.865***
(0.066) (0.121) (0.178) (0.234) (0.281) (0.288) (0.288) (0.269) (0.258) (0.263)
Mean 2.165 4.423 7.409 11.160 15.364 19.882 24.535 29.089 33.541 37.732
All
-0.115 -0.257 -0.329 -0.357 -0.480 -0.649** -0.800*** -0.881*** -0.795*** -0.794***
(0.095) (0.164) (0.212) (0.263) (0.290) (0.290) (0.283) (0.267) (0.250) (0.249)
Mean 4.179 7.210 10.754 14.864 19.304 23.965 28.603 33.048 37.266 41.140
Female Observations 3,747,295 3,929,942 4,024,060 4,163,759 4,312,369 4,391,714 4,432,335 4,455,032 4,450,005 4,445,362
Male Observations 3,789,366 3,920,591 3,992,642 4,097,273 4,227,178 4,303,099 4,333,243 4,344,629 4,320,794 4,300,334
All Observations 7,536,661 7,850,533 8,016,702 8,261,032 8,539,547 8,694,813 8,765,578 8,799,661 8,770,799 8,745,696
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Simulated Years
Eligible, Age 0-18
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors in parentheses are clustered by state. Marital status indicates filing a tax return (Form 1040) using thefiling status “married, filing jointly” or “married, filing separately.” Coefficients for each age are obtained from separate reduced form regressions of marital status onsimulated years eligible, ages 0–18. The specification includes fixed effects for birth cohort by month and for state of residence at age 15 (the youngest age at whichwe observe all individuals in our sample). Figure OA.34 presents this table graphically.
83
Appendix 21 Regression Discontinuity Results
In the tradition of Card and Shore-Sheppard (2004), Wherry and Meyer (2016), and Wherry
et al. (2015), we estimate regression discontinuity specifications that harness variation in
Medicaid eligibility from the Omnibus Budget Reconciliation Act of 1990 (OBRA 90). This
federal policy reduced the Medicaid eligibility threshold to 100% of the federal poverty level
for children who were born after September 30, 1983. Variation from OBRA 90 is arguably
exogenous as it is unlikely that parents manipulated birth timing in 1983 in anticipation
of federal legislation passed in 1990. The OBRA 90 expansion differentially affected our
sample of children born from 1981 to 1984. As expected, we see a jump in average simulated
Medicaid eligibility and Medicaid eligibility by month of birth at the vertical line between
September and October 1983, as displayed in the first rows of Figures OA.35 and OA.36.
Figures OA.37–OA.42 in Online Appendix 21.1 present similar plots for each of our six
main outcomes. Because we measure most of our outcomes with respect to the tax year,
we see strong seasonal patterns by month of birth, especially in total taxes, presented in
Figure OA.42. This seasonality visually obscures a potential jump at the discontinuity that
would be captured in our main specification, which flexibly adjusts for seasonality using
birth month fixed effects. Mortality is our only main outcome that does not exhibit strong
seasonality, likely because we observe it continuously throughout the year using SSA death
records. However, as shown in the first row of Figure OA.39, we still cannot visually detect
a mortality change at the discontinuity absent any seasonal adjustment.
To address seasonality, we compute the mean outcome for each birth month of 1981,
and we subtract it from the mean outcome for the same birth month in later years.22 This
seasonal adjustment makes jumps around the discontinuity more visible, especially for total
taxes, as shown in the second row of Figure OA.42. However, we still see strong patterns by
calendar year of birth that are difficult to address in our regression discontinuity specification
because there are only three months after the discontinuity within the 1983 calendar year.
In our main specification, we do not need to estimate a trend across birth months, so we
simply incorporate year fixed effects.
To estimate the effect of OBRA 90 on a seasonally-adjusted cumulative outcome Yi, in
our regression discontinuity specification, we fit linear functions on both sides of September
30, 1983:
Yi = α01{ri ≥ 0}+ α1ri + α2ri1{ri ≥ 0}+ α3 + ηi, (OA.1)
22Our approach to seasonal adjustment differs from the approach used by Wherry et al. (2015) andWherry and Meyer (2016), who adjust their data using birth month fixed effects estimated before and afterthe discontinuity. In our sample, birth months are not balanced on either side of the discontinuity; the datacontain 33 cohorts before September 30, 1983 and only 15 afterward. Therefore, birth month fixed effectsestimated on the entire sample could capture some of the effect of OBRA 90.
84
where we normalize the running variable ri, which represents birth month cohort, to be zero
in October 1983. Cohorts with ri ≥ 0 are treated by OBRA 90. We exclude birth month
cohorts from 1981, which we use for seasonal adjustment, and we include birth month cohorts
from January 1982 – December 1984, such that ri ∈ [−21, 14]. Since we address seasonality
outside of the specification, we present bootstrapped standard errors using 200 replications.
The first stage results in the first two columns of Table OA.46 show that OBRA 90 generated
around 0.60 to 0.70 years of eligibility across both sexes and across actual and simulated
Medicaid eligibility, although we obtain precise estimates for simulated eligibility only.
Table OA.46 also presents regression discontinuity coefficients for our six main outcomes.
The jumps at the discontinuity are imprecise across all outcomes, but they are broadly
consistent with the signs and magnitudes of our main estimates (which need not be the
case because both sets of estimates rely on different variation). At the discontinuity, we
see a jump of $135 in cumulative total taxes by age 28 in the full sample, implying that an
additional year of simulated eligibility increases taxes by $198 (=135/0.682), which is broadly
consistent with our main estimate of $471. For mortality by age 28, an additional year of
simulated eligibility from OBRA 90 decreases the rate by 0.025% (=-0.017/0.682), which is
consistent with our main estimate of 0.033%. Similarly, the results for college enrollment are
positive but smaller in magnitude, and the results for wage income are positive and larger in
magnitude than our main estimates. We find a negligible effect on EITC. Finally, departing
from our main estimate, we find suggestive evidence of a positive effect of OBRA 90 on
fertility.
85
21.1 Regression Discontinuity Figures
Figure OA.35: Simulated Years Eligible for Medicaid, Age 0–18
23
45
6S
im. Y
ears
Elig
ible
, Age
0-1
8
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
23
45
6
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
23
45
6
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
0.5
11.
52
2.5
3S
im. Y
ears
Elig
ible
, Age
0-1
8
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
0.5
11.
52
2.5
3
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
0.5
11.
52
2.5
3
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for childrenborn after September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in thefigure. The first row graphs simulated eligibility for each birth month cohort from January 1981 – December 1984, withoutadjustments for seasonal variation. To adjust for seasonal variation, the second row subtracts from each birth month cohortthe mean simulated eligibility for the respective birth month in 1981.
86
Figure OA.36: Years Eligible for Medicaid, Age 0–18
23
45
6Y
ears
Elig
ible
, Age
0-1
8
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
23
45
6
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
23
45
6
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
0.5
11.
52
2.5
Yea
rs E
ligib
le, A
ge 0
-18
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
0.5
11.
52
2.5
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
0.5
11.
52
2.5
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for children bornafter September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in the figure.The first row graphs eligibility for each birth month cohort from January 1981 – December 1984, without adjustments forseasonal variation. To adjust for seasonal variation, the second row subtracts from each birth month cohort the mean eligibilityfor the respective birth month in 1981.
87
Figure OA.37: Cumulative College Enrollment (%) by Age 28
6070
8090
100
Cum
. Col
lege
Enr
ollm
ent (
%)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
6070
8090
100
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
6070
8090
100
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
-20
24
68
Cum
. Col
lege
Enr
ollm
ent (
%)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
-20
24
68
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
-20
24
68
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for children bornafter September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in the figure.Cumulative college enrollment indicates ever having enrolled in college by age 28, starting at age 19 and observed throughForm 1098-T filed by educational institutions. The first row graphs mean college enrollment for each birth month cohort fromJanuary 1981 – December 1984, without adjustments for seasonal variation. To adjust for seasonal variation, the second rowsubtracts from each birth month cohort the mean outcome for the respective birth month in 1981.
88
Figure OA.38: Cumulative Fertility (%) by Age 28
2535
4555
6575
Cum
. Fer
tility
(%
)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
2535
4555
6575
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
2535
4555
6575
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
-15
-10
-50
510
Cum
. Fer
tility
(%
)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
-15
-10
-50
510
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
-15
-10
-50
510
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for children bornafter September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in the figure.Cumulative fertility indicates if a dependent child is ever born by age 28, starting at age 19. If an individual ever claims adependent child on a Form 1040, SSA records yield age at birth. The first row graphs mean fertility for each birth month cohortfrom January 1981 – December 1984, without adjustments for seasonal variation. To adjust for seasonal variation, the secondrow subtracts from each birth month cohort the mean outcome for the respective birth month in 1981.
89
Figure OA.39: Cumulative Mortality (%) by Age 28
0.2
5.5
.75
11.
251.
5C
um. M
orta
lity
(%)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
0.2
5.5
.75
11.
251.
5
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
0.2
5.5
.75
11.
251.
5
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
-.3
-.2
-.1
0.1
.2C
um. M
orta
lity
(%)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
-.3
-.2
-.1
0.1
.2
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
-.3
-.2
-.1
0.1
.2
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for children bornafter September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in the figure.Cumulative mortality indicates mortality by age 28, starting at age 19 and measured using SSA death records. The first rowgraphs mean mortality for each birth month cohort from January 1981 – December 1984, without adjustments for seasonalvariation. To adjust for seasonal variation, the second row subtracts from each birth month cohort the mean outcome for therespective birth month in 1981.
90
Figure OA.40: Cumulative Wage Income ($000) by Age 28
100
120
140
160
180
200
Cum
. Wag
e In
com
e ($
000)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
100
120
140
160
180
200
Ja
n-81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
100
120
140
160
180
200
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
05
1015
20C
um. W
age
Inco
me
($00
0)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
05
1015
20
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
05
1015
20
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for children bornafter September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in the figure.Cumulative wage income indicates wage income earned by age 28, starting at age 19 and adjusted to 2011 dollars. We obtainwage income from Form W-2, and we censor wage income earned at $10 million. The first row graphs wage income for eachbirth month cohort from January 1981 – December 1984, without adjustments for seasonal variation. To adjust for seasonalvariation, the second row subtracts from each birth month cohort the mean outcome for the respective birth month in 1981.
91
Figure OA.41: Cumulative EITC ($000) by Age 28
01
23
45
Cum
. EIT
C (
$000
)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
01
23
45
Ja
n-81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
01
23
45
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
0.1
5.3
.45
.6.7
5C
um. E
ITC
($0
00)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
0.1
5.3
.45
.6.7
5
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
0.1
5.3
.45
.6.7
5
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for children bornafter September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in the figure.Obtained from Form 1040, cumulative EITC indicates EITC earned by age 28, starting at age 19, adjusted to 2011 dollars.The first row graphs EITC for each birth month cohort from January 1981 – December 1984, without adjustments for seasonalvariation. To adjust for seasonal variation, the second row subtracts from each birth month cohort the mean outcome for therespective birth month in 1981.
92
Figure OA.42: Cumulative Total Taxes ($000) by Age 28
05
1015
2025
30C
um. T
otal
Tax
es (
$000
)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Female
05
1015
2025
30
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
Male
05
1015
2025
30
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
AllRaw Data
-1-.
50
.51
Cum
. Tot
al T
axes
($0
00)
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
-1-.
50
.51
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Birth Month Cohort
-1-.
50
.51
Jan-
81
Jan-
82
Jan-
83
Sep-8
3
Jan-
84
Dec-8
4
Detrended using 1981
Note. OBRA 90 reduced the eligibility threshold for Medicaid eligibility to 100% of the federal poverty level for children bornafter September 30, 1983. Cohorts that experienced this increase in eligibility are to the right of the vertical line in the figure.Cumulative total taxes indicate taxe s paid by age 28, starting at age 19, adjusted to 2011 dollars and defined as householdfederal tax payments plus individual payroll tax payments less EITC. The first row graphs total taxes for each birth monthcohort from January 1981 – December 1984, without adjustments for seasonal variation. To adjust for seasonal variation, thesecond row subtracts from each birth month cohort the mean outcome for the respective birth month in 1981.
93
21.2
Regre
ssion
Disco
ntin
uity
Table
Table OA.46: Regression Discontinuity Results for Cumulative Outcomes by Age 28
(1) (2) (3) (4) (5) (6) (7) (8)
Simulated
Years Eligible,
Age 0-18
Years
Eligible,
Age 0-18
College
Enrollment
(%)
Fertility
(%)
Mortality
(%)
Wage
Income
($000)
EITC
($000)
Total
Taxes
($000)
Female
Treated by OBRA 90 0.684*** 0.586 0.255 0.246 0.002 0.806 0.030 0.108
(0.160) (0.546) (1.124) (1.468) (0.018) (2.656) (0.257) (1.007)
Birth Month Cohort 0.041*** 0.028 0.137*** -0.136** -0.000 0.289*** 0.011 -0.009
(0.008) (0.025) (0.054) (0.068) (0.001) (0.127) (0.012) (0.048)
Treated by OBRA 90 * Birth Month Cohort -0.007 0.002 -0.019 -0.307** -0.001 -0.065 -0.006 0.001
(0.016) (0.049) (0.087) (0.112) (0.002) (0.197) (0.021) (0.076)
Constant 1.305*** 0.947** 3.024*** -3.470*** -0.013 8.814*** 0.423*** -0.177
(0.116) (0.357) (0.811) (0.992) (0.013) (1.829) (0.180) (0.706)
Male
Treated by OBRA 90 0.681*** 0.607 0.276 0.102 -0.033 1.636 0.013 0.175
(0.156) (0.498) (1.338) (0.956) (0.036) (2.263) (0.115) (0.668)
Birth Month Cohort 0.041*** 0.029 0.145** -0.139*** 0.002 0.377*** 0.007 0.003
(0.009) (0.026) (0.072) (0.051) (0.002) (0.115) (0.006) (0.035)
Treated by OBRA 90 * Birth Month Cohort -0.007 -0.001 -0.019 -0.259*** -0.006** -0.121 -0.004 -0.001
(0.015) (0.052) (0.115) (0.083) (0.003) (0.193) (0.010) (0.058)
Constant 1.307*** 0.934** 3.418*** -3.720*** 0.010 10.334*** 0.235** 0.293
(0.114) (0.359) (1.010) (0.713) (0.025) (1.599) (0.084) (0.492)
All
Treated by OBRA 90 0.682*** 0.597* 0.281 0.193 -0.017 1.196 0.024 0.135
(0.118) (0.365) (1.020) (1.022) (0.038) (1.935) (0.158) (0.609)
Birth Month Cohort 0.041*** 0.029 0.140*** -0.139** 0.001 0.336*** 0.008 -0.002
(0.006) (0.019) (0.049) (0.053) (0.002) (0.105) (0.008) (0.032)
Treated by OBRA 90 * Birth Month Cohort -0.007 0.000 -0.019 -0.282*** -0.003 -0.095 -0.005 -0.001
(0.011) (0.034) (0.086) (0.084) (0.003) (0.166) (0.014) (0.052)
Constant 1.306*** 0.940*** 3.211*** -3.616*** -0.000 9.621*** 0.324*** 0.069
(0.085) (0.258) (0.747) (0.691) (0.026) (1.346) (0.110) (0.433)
Note. *** p < 0.01, ** p < 0.05, * p < 0.10. Standard errors were bootstrapped with 200 repetitions. Coefficients are obtained from a regression of the cumulativeoutcome by age 28 on an indicator for treatment by OBRA 90, birth month cohort centered around the OBRA 90 cutoff, and the interaction between the two. To adjustfor seasonal variation, we subtract from each birth month cohort the mean outcome for the respective birth month in 1981. Cumulative college enrollment indicates everhaving enrolled in college by age 28, starting at age 19 and observed through Form 1098-T filed by educational institutions. Cumulative fertility indicates if a dependentchild is ever born by age 28, starting at age 19. If an individual ever claims a dependent child on a Form 1040, SSA records yield age at birth. Cumulative mortalityindicates mortality by age 28, starting at age 19 and measured using SSA death records. Cumulative wage income indicates wage income earned by age 28, starting at age19 and adjusted to 2011 dollars. We obtain wage income from Form W-2, and we censor wage income earned at $10 million. Cumulative EITC indicates EITC earned byage 28, starting at age 19, adjusted to 2011 dollars. We observe EITC using Form 1040. Cumulative total taxes indicate taxes paid by age 28, starting at age 19, adjustedto 2011 dollars and defined as household federal tax payments plus individual payroll tax payments less EITC.
94
References for the Online Appendix
Card, D. and L. D. Shore-Sheppard (2004). Using discontinuous eligibility rules to identify
the effects of the federal medicaid expansions on low-income children. The Review of
Economics and Statistics 86 (3), 752–766.
Wherry, L. R. and B. D. Meyer (2016). Saving teens: Using a policy discontinuity to estimate
the effects of medicaid eligibility. Journal of Human Resources 51 (3), 556 – 588.
Wherry, L. R., S. Miller, R. Kaestner, and B. D. Meyer (2015). Childhood medicaid coverage
and later life health care utilization. Review of Economics and Statistics (0).
95
