Before taking on an assignment you will look over the content and only use the references and resources provided in the attachments and body of Assignment Overview. No plagiarism and original work to be done. NO OUTSIDE SOURCES ALLOWED!!
MEDICAID ELIGIBILITY AND FINANCING
Assignment Overview
Over 72 million Americans are currently covered by Medicaid (along with coverage by the SCHIP programs), which makes Medicaid the single-largest source of health insurance coverage in the United States. Depending on income, children, pregnant women, parents, senior citizens, and individuals with certain disabilities are able to access the health care system for needed services. In this Case Assignment, benefits, eligibility, financing, and reimbursement levels will be examined – including how the Patient Protection and Affordable Care Act impacted the program. How do the economics of Medicare reimbursement levels vs. private insurance reimbursement levels affect health care systems and providers?
Case Assignment
Using the information in the required readings, as well as some additional research in peer-reviewed sources, complete your Case assignment by answering the following:
- Examine the benefits and eligibility of the Medicaid program. Who can be covered, and what are the specific income restrictions when qualifying via financial status? How did the Patient Protection and Affordable Care Act change the income determination methodology?
- Describe how the Medicaid program is financed. How much do the individual states (including your home state) contribute?
- Determine how the average Medicaid reimbursement level specifically compares to the average reimbursement for private insurance. How can these reimbursement levels affect the bottom line at your facility?
Kaiser Family Foundation. (2019). Ten things to know about Medicaid: Setting the facts straight. Available at https://www.kff.org/medicaid/issue-brief/10-things-to-know-about-medicaid-setting-the-facts-straight/
Robert Wood Johnson Foundation. (2019). Medicaid: The basics. Available at https://www.rwjf.org/en/library/research/2019/02/medicaid-the-basics.html
Assignment Expectations
- Conduct additional research to gather sufficient information to support your analysis.
- Provide a response of 3-5 pages, not including title page and references
- There are multiple required items to be addressed herein; please use subheadings to show where you are responding to each required item and to ensure that none are omitted.
- Support your paper with peer-reviewed articles, with at least 3 references. Use the following link for additional information on how to recognize peer-reviewed journals:
Angelo State University Library. (n.d.).Library Guides: How to recognize peer-reviewed (refereed) journals. Retrieved from https://www.angelo.edu/services/library/handouts/peerrev.php - You may use the following source to assist in formatting your assignment:
Purdue Online Writing Lab. (n.d.). General APA guidelines. Retrieved from https://owl.english.purdue.edu/owl/resource/560/01/ - For additional information on reliability of sources, review the following source:
Georgetown University Library. (n.d.). Evaluating internet resources. Retrieved from https://www.library.georgetown.edu/tutorials/research-guides/evaluating-internet-content
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Journal of Health Economics 53 (2017) 1–16
Contents lists available at ScienceDirect
Journal of Health Economics
jo ur nal homep age: www.elsev ier .com/ lo cate /econbase
edicaid, family spending, and the financial implications of rowd-out�
arcus Dillender .E. Upjohn Institute for Employment Research, 300 S. Westnedge Ave., Kalamazoo, MI 49007-4686, United States
r t i c l e i n f o
rticle history: eceived 7 September 2016 eceived in revised form 2 December 2016 ccepted 6 February 2017 vailable online 16 February 2017
EL classification: 12
a b s t r a c t
A primary purpose of health insurance is to protect families from medical expenditure risk. Despite this goal and despite the fact that research has found that Medicaid can crowd out private coverage, little is known about the effect of Medicaid on families’ spending patterns. This paper implements a simulated instrumental variables strategy with data from the Consumer Expenditure Survey to estimate the effect of an additional family member becoming eligible for Medicaid on family-level health insurance coverage and spending. The results indicate that an additional family member becoming eligible for Medicaid increases the number of people in the family with Medicaid coverage by about 0.135–0.142 and decreases the likelihood that a family has any medical spending in a quarter by 2.7 percentage points. As previous
13
eywords: edicaid eligibility
rowd-out amily spending
research often finds with different data sets, I find evidence that Medicaid expansions crowd out some private coverage. Unlike most other data sets, the Consumer Expenditure Survey allows for considering the financial implications of crowd-out. The results indicate that families that transition from private coverage to Medicaid are able to spend significantly less on health insurance expenses, meaning Medicaid expansions can be welfare improving for families even when crowd-out occurs.
© 2017 Elsevier B.V. All rights reserved.
the expenditures of U.S. households over the past quarter of the year. I focus on families with incomes less than 200 percent of the
Medicaid provides free or cheap health insurance to individu- ls with low incomes and has the potential to transform families’ pending patterns. According to the 2014 Consumer Expenditure urvey (CEX), 23 percent of households with at least one per- on with Medicaid coverage have any quarterly medical spending, hile 44 percent of households without Medicaid do. Meanwhile,
nly 38 percent of households with at least one person with Medi- aid coverage have any quarterly health insurance spending, while 3 percent without Medicaid do. These numbers are consistent ith Medicaid being a financial boon to households. But as Medi-
aid is a means-tested program, these numbers could also reflect hat poorer families that are able to spend less on medical care and ealth insurance are more likely to be eligible for Medicaid.
Despite a key goal of health insurance being to protect fami- ies from medical expenditure risk, little is known about the effect f Medicaid on financial outcomes. As Buchmueller et al. (2015a) xplain in their recent review of economics research on Medicaid,
Given that a fundamental purpose of health insurance is to protect ndividuals and families from the financial burden of large medi- al expenditures, there is surprisingly little research on the effect
� I thank Joelle Abramowitz, Erik Nesson, and seminar participants at the 2016 SHEcon Conference for discussions and comments.
E-mail address: [email protected]
ttp://dx.doi.org/10.1016/j.jhealeco.2017.02.002 167-6296/© 2017 Elsevier B.V. All rights reserved.
of Medicaid on financial outcomes.” The research on the financial effects of Medicaid that exists often focuses on extreme spending events and finds that Medicaid reduces bankruptcies and the num- ber of bills going to collections (Finkelstein et al., 2012; Gross and Notowidigdo, 2011; Hu et al., 2016). In contrast to the literature on the financial effects of Medicaid, the literature that studies Med- icaid coverage crowding out private coverage is large,1 but a key issue that has received little attention is what the financial impli- cations of this crowd-out are for families.
The goals of this paper are to understand how Medicaid eli- gibility affects families’ spending and to consider the welfare implications of spending effects. To estimate the effect of Medicaid eligibility on families’ spending, I implement a simulated instru- mental variables (IV) strategy using data from the CEX, which is a data set collected by the Bureau of Labor Statistics (BLS) that tracks
federal poverty level (FPL) and use variation in Medicaid eligibil-
1 A sample of the literature, much of which I discuss later, includes Bronchetti (2014), Buchmueller et al. (2005), Busch and Duchovny (2005), Cutler and Gruber (1996), Gruber and Simon (2008), Ham and Shore-Sheppard (2005a), Ham et al. (2014), Hamersma and Kim (2013), Koch (2013, 2015), LoSasso and Buchmueller (2004), and Shore-Sheppard (2008).
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eligibility, they use a simulated IV strategy and find that Medicaid
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ty due to legislative changes during the 2000s.2 During this time eriod, several states changed their eligibility rules for children, ut the majority of changes come from states expanding Medicaid overage for parents, meaning that the bulk of the identifying vari- tion comes from parents becoming eligible for Medicaid. The CEX rovides two main advantages over many other data sets. First, it llows for studying how Medicaid eligibility affects medical spend- ng for a nationally representative sample of the U.S. population. econd, the CEX allows for studying how crowd-out affects families’ pending on health insurance.
I first consider the effect of Medicaid eligibility on health insur- nce coverage using the CEX data. I estimate that an additional erson in a family being eligible for Medicaid increases the num- er of people in the family with Medicaid coverage by 0.135–0.142 nd decreases the number of private health insurance plans paid or by families by an average of 0.053–0.055. These estimates are imilar to estimates that I find using the March Current Population urveys (CPS) and the Survey of Income and Program Participation SIPP) and fall within the range of other estimates of the effect of
edicaid eligibility on health insurance coverage. I then consider how Medicaid eligibility affects spending. I find
hat an additional person being eligible for Medicaid reduces the ikelihood that a family has any spending on medical care in a uarter by 2.7 percentage points. The bulk of this decrease appears o come from families who had relatively small quarterly medical xpenditures prior to Medicaid as decreases in the likelihood of aving positive spending in a quarter that is less than $100 drive he results.
It is not immediately clear that the crowd-out of private health nsurance coverage will lead to families spending less on health nsurance. According to the 2014 CEX, more than 25 percent of amilies with private health insurance do not have any quarterly pending on health insurance, while only 30 percent spend more han $1000 per quarter on health insurance. A cottage indus- ry has developed around helping firms sign up Medicaid-eligible mployees for Medicaid to save the firms money (Kim, 2016), and ome research suggests that firms are successfully able to capital- ze on Medicaid expansions to lower their health insurance costs Buchmueller et al., 2005). If the crowd-out comes from workers ho had low spending on health insurance, crowd-out may not
esult in cost savings to families. Taking advantage of the CEX’s questions about health insurance
pending, I find that an additional person being eligible for Medicaid educes the likelihood that a family has any health insurance expen- itures by 4.3 percentage points. This decrease appears to come rom families that were spending more than $100 per quarter on ealth insurance prior to Medicaid and reduces average spending n health insurance in a quarter by $47. Under the assumption that edicaid only affects health insurance costs for those who experi-
nce crowd-out, the estimates imply that the reductions in private nsurance from Medicaid expansions save the switching families an verage of $4124–4284 per year, meaning the families that experi- nce crowd-out were paying significant amounts of the premiums or their private insurance. The results from this study suggest that
edicaid eligibility makes families better off even when crowd-out ccurs.
The paper contributes to the small literature on the spend-
ng effects of Medicaid in a number of ways. One contribution is hat the current study focuses on Medicaid expansions that affect amilies, whereas other studies have mainly focused on Medicaid
2 I use variation in both Medicaid and the State Children’s Health Insurance Pro- ram (CHIP) eligibility. As is common in this literature, I refer to both Medicaid and HIP as Medicaid for ease of discourse, even though the two are distinct programs
n many states.
conomics 53 (2017) 1–16
coverage for childless adults, who comprise a much smaller share of the Medicaid population. Another contribution of this study is that it uses a nationally representative data set that is designed to measure expenditures and that allows for considering the effect of Medicaid eligibility on a wider variety of financial outcomes than previous research has considered. Importantly, the paper estimates the financial impacts of crowd-out on health insurance spending. Whether families or employers capture monetary savings from crowd-out is an open question that has important welfare implica- tions.
The paper proceeds as follows. The next section provides a brief overview of Medicaid and discusses previous research on crowd-out from Medicaid expansions and on the spending effects of Medicaid. Section 2 discusses a simple conceptual framework for how Medicaid eligibility could affect spending and what the implications of spending effects are for welfare. Section 3 describes the variation in Medicaid eligibility, the CEX data, and the empir- ical strategy. Section 4 presents the empirical results. Section 5 discusses the results and concludes.
1. Background
1.1. Medicaid
Medicaid is a state-run program that is jointly financed by the federal government and by states that provides health insurance to people with low incomes, people with disabilities, and the elderly in long-term care with low incomes.3 In 1997, State Children’s Health Insurance Program (CHIP) legislation expanded eligibility of chil- dren for public health insurance beyond the existing limits of the Medicaid program. In the years that followed, states have expanded eligibility for both the CHIP program and Medicaid. States typically require family incomes to be lower for parents to be eligible than they do for children to be eligible.
Although federal Medicaid rules require states to cover major services including physician and hospital care, the rules do not require states to pay for other services such as prescription drugs or dental care. Despite flexibility in coverage options, most states cover most basic categories of health spending. For instance, all states cover prescription drugs and optometrist services. While almost all cover dental services for children, not all states cover dental care for adults. Covered services are provided with little or no copayment required (Ross et al., 2009).
1.2. Prior research on crowd-out from Medicaid expansions
The health insurance effects of Medicaid eligibility are relevant for assessing the magnitude and channels of any potential effects of Medicaid eligibility on spending. In contrast to the literature on the financial impacts of Medicaid, a large literature has examined Med- icaid take-up and the effect of Medicaid on private health insurance coverage. Much of this research builds on Cutler and Gruber (1996), who estimate the effect of Medicaid eligibility on Medicaid take- up and on private health insurance coverage using data from the 1988 to 1993 March CPS. To deal with the endogeneity of Medicaid
eligibility increases Medicaid coverage by 23.5 percentage points and decreases private insurance coverage by 7.4 percentage points.
3 Medicaid has traditionally provided coverage for low-income families with chil- dren rather than all low-income adults. As part of the Affordable Care Act, Medicaid was expanded in many states to include low-income childless adults. Some states had already expanded Medicaid to low-income childless adults prior to the passage of the Affordable Care Act.
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Since the seminal work by Cutler and Gruber (1996), other stud- es using simulated IV strategies with March CPS data have tended o estimate effects of Medicaid eligibility that are smaller in abso- ute value both on Medicaid take-up and on the decrease in private overage. For example, Shore-Sheppard (2008) finds that adding ontrols for age over time causes the estimated effect of Medi- aid eligibility on Medicaid coverage to fall to between 15 and 9 percentage points and the estimated effect on private cover- ge to be close to zero and statistically insignificant. LoSasso and uchmueller (2004) estimate that 9 percent of the newly eligible
rom the CHIP expansions received coverage and that half of this ncrease came from those with private coverage.
Papers that use simulated IV strategies with the SIPP find sim- larly mixed estimates. For example, Ham and Shore-Sheppard 2005a) estimate that Medicaid eligibility increases take-up by 11.8 ercentage points but does not affect private coverage. Gruber and imon (2008), on the other hand, estimate that an additional per- on being eligible for Medicaid increases the number of people in
household with Medicaid coverage by between 0.109 and 0.156 eople and reduces the number of people with private coverage by etween 0.066 and 0.122. They find that most of the decrease in rivate coverage comes from employer-sponsored coverage.
In addition to results varying by data set and specification, the ffect of Medicaid eligibility on the crowd-out of private cover- ge differs by group and time period. For instance, Hamersma and im (2013) use SIPP data from 1996 to 2007 and find that a par- nt becoming eligible for Medicaid increases the likelihood that he parent has Medicaid coverage by 14.8 percentage points and as no effect on private coverage. Using CPS data from 1996 to 002, Busch and Duchovny (2005) find similar take-up rates and nly weak, suggestive evidence that parental Medicaid expansions rowd out private coverage. In contrast to these studies, McMorrow t al. (2016) use National Health Interview Survey data from 1998 o 2010 and find evidence that about one-third of people who ake up parental Medicaid expansions previously had private cov- rage. Wagner (2015) finds that Medicaid eligibility expansions or the disabled crowd out much private coverage, while early esults for childless expansions suggest that the degree of crowd- ut may vary by state (Sommers et al., 2014). As Gruber and Simon 2008) summarize, early results appear to differ by data set and are ften sensitive to specification, while the literature on the more ecent expansions tends to find more consistent crowd-out effects. lthough there is no consensus about the degree of crowd-out, the ongressional Budget Office considers the crowd-out to lie between 5 and 50 percent (Congressional Budget Office, 2007).4 Refer to itler and Zavodny (2014), Buchmueller et al. (2015a), and Gruber nd Simon (2008) for excellent reviews of the literature.5
4 While most of the literature is agnostic about reasons that crowd-out might ccur, two papers explore endogenous health insurance offerings by firms. Shore- heppard et al. (2000) use firm-level data and find that a firm having more workers ligible for Medicaid is associated with the firm being less likely to offer dependent overage. However, they do not find that the share of Medicaid-eligible workers in
firm has an effect on the premiums the workers have to pay. Buchmueller et al. 2005) find some evidence that firms whose workers are likely to have been affected y Medicaid expansions raise employees’ contributions for family coverage. Nei- her paper finds that firms are less likely to offer health insurance after Medicaid xpansions. 5 This literature review focuses largely on studies that use simulated IV strategies. ther papers use different methods, including difference-in-differences and regres-
ion discontinuity designs. For examples, refer to Blumberg et al. (2000), Card and hore-Sheppard (2004), Dague et al. (2011), De La Mata (2012), Koch (2013), Koch 2015), and Yazici and Kaestner (2000).
conomics 53 (2017) 1–16 3
1.3. Prior research on financial impacts of Medicaid
The literature on the financial impacts of Medicaid is smaller than the literature on crowd-out and has generally focused on an inability to pay medical bills. Gross and Notowidigdo (2011) study the effect of Medicaid expansions in the 1990s on bankruptcies. They find that a 10-percent increase in Medicaid eligibility reduces personal bankruptcies by 8 percent. Finkelstein et al. (2012) study Oregon allocating slots to an oversubscribed Medicaid program for adults using a lottery. Using administrative data from the Consumer Credit Database and from the credit bureau TransUnion, they find that Medicaid coverage is associated with a significant decline in the likelihood that a medical bill is sent to collections but no sig- nificant decline in bankruptcies or liens. Hu et al. (2016) study the effect of the Affordable Care Act (ACA) Medicaid expansion to child- less adults using data from the Federal Reserve Bank of New York’s Consumer Credit Panel. They find that low-income zip codes expe- rienced a reduction in the number of unpaid bills and the amount of debt sent to third-party collection agencies in states that expanded Medicaid.
Although these extreme financial outcomes are important, they do not represent a full picture of the spending effects of Medicaid. Contemporaneous spending has received less attention, though the Finkelstein et al. (2012) Oregon study is an exception. Finkelstein et al. supplement their analysis of administrative data with survey data and find intent-to-treat estimates that suggest that winning the Medicaid lottery decreases the likelihood of having any med- ical spending in the last six months by 5.8 percentage points and of having an outstanding medical bill by 5.2 percentage points. The current study differs from Finkelstein et al. in three main ways. First, the current study focuses on Medicaid eligibility for families, while Finkelstein et al. study the effect of Medicaid on childless adults, who may respond to Medicaid differently than families. Medicaid eligibility for childless adults is still relatively new, and the vast majority of people covered by Medicaid are in families with children.6 Second, the CEX contains a much wider set of spending outcomes than is available in the survey used in Finkelstein et al. A particularly important spending outcome available in the CEX that the Oregon health insurance experiment does not address is health insurance spending. Third, the current study uses a simulated IV strategy, while Finkelstein et al. study the effects of an experiment. While experiments are often thought to be the gold standard of research, they are expensive and rarely done with health insurance, which precludes them as an option for most studies of Medicaid. As is the case with the Oregon health insurance experiment, they are also often restricted in their geography.
Another study that considers the financial implications of Med- icaid is Sommers and Oellerich (2013), who estimate the impact of Medicaid with the Census Bureau’s Supplemental Poverty Measure by stochastically drawing counterfactual medical expenditures from propensity-score-matched individuals without Medicaid. They find that Medicaid reduces out-of-pocket medical spending from $376 to $871 per beneficiary and decreases poverty rates by 1.0 percent among children, 2.2 percent among disabled adults, and 0.7 percent among elderly individuals. My study differs from Sommers and Oellerich in that I estimate the effect of Medicaid eli-
gibility using variation from natural experiments and consider a wider set of outcomes.7
6 According to 2015 March CPS data, less than a quarter of Medicaid recipients had no children in their household.
7 Gruber and Yelowitz (1999) produce an early study of the effect of Medicaid eligibility on savings and consumption using CEX data from the 1980s and early 1990s and find evidence that Medicaid eligibility increases non-health-related con- sumption and decreases savings. As Medicaid typically had asset tests prior to the
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. Conceptual framework
Medicaid eligibility has the potential to affect health insurance overage in two main ways. First, it can allow uninsured people to ecome insured. Second, it can allow people who were receiving rivate coverage to drop that coverage so that they can receive edicaid. For the previously uninsured, Medicaid lowers the price of
ealth care. As health care is a normal good, this lower price means eople should theoretically consume more of it, a prediction that as found broad empirical support.8 If all health care expendi- ures are covered by Medicaid, the effect of Medicaid on spending n health care should be negative. If non-covered care comple- ents covered care, Medicaid eligibility could potentially increase
pending on medical care. As lowering the cost of medical care can ncrease the amount of medical services received, reduce medi- al expenditures, and lower the risk of catastrophic medical bills, edicaid likely increases welfare for the previously uninsured. For those who previously had private coverage, Medicaid may
llow families to spend less on health insurance premiums, espe- ially if they were paying a high share of the premiums for the rivate health insurance. However, if the coverage they had was oor or if employers can successfully capture the cost savings from edicaid expansions, households’ spending on health insurance ay not fall dramatically. If the coverage people lose was poor,
hen Medicaid would affect medical spending in a way similar as it oes for the previously uninsured.
The welfare implications of crowd-out depend on both the qual- ty of the private coverage that is crowded out and what share the amily was paying for the private coverage. Consider the following hree pre-Medicaid-eligibility cases:
. The family was paying very little for good coverage.
. The family was paying full price for good coverage.
. The family was paying very little for poor coverage.
Medicaid eligibility crowding out private coverage for case (1) oes not necessarily help the family. If an employer was paying
arge amounts for the worker’s health insurance, then the worker
eaving private employer-sponsored coverage for Medicaid lowers mployers’ costs. These lower costs for employers may or may not ater translate into higher wages for the worker.9
990s, their analysis pertains to a different vintage of the Medicaid program than xists now. In Appendix B, I consider the effect of Medicaid eligibility on non-health- elated consumption and discuss Gruber and Yelowitz further.
8 However, it should be noted that people may ultimately consume less medical are if Medicaid allows them to obtain more preventive care that prevents the need or more health care later. Examples of research that find that Medicaid increases he use of health care services include Aizer (2007), Baicker et al. (2013), Bronchetti 2014), Buchmueller et al. (2015b), Burns et al. (2014), Currie et al. (2008), Dafny nd Gruber (2005), De La Mata (2012), DeLeire et al. (2013), Finkelstein et al. (2012), ipton and Decker (2015), and Taubman et al. (2014). This finding holds for private nsurance health insurance (Anderson et al., 2012, 2014), Medicare (Card et al., 2008, 009), and health insurance expansions coming from broad health insurance reform Kolstad and Kowalski, 2012; Miller, 2012) as well.
9 It is unclear whether workers or firms bear the cost of health insurance bene- ts. If workers value money spent on health insurance as much as they would value he money itself, if employers can perfectly identify which people are eligible for
edicaid, and if employers can perfectly and instantly adjust compensation, theory redicts that employers will pass the costs of health insurance to employees in the orm of lower wages (Gruber, 1994; Summers, 1989). Therefore, Medicaid expan- ions have the potential to increase wages if employers no longer have to provide orkers with health insurance coverage. However, these assumptions may not hold
or a variety of reasons. For example, identifying Medicaid-eligible people is likely ifficult since employers would have to know total family income. Furthermore, inkelstein et al. (2012) find that the Oregon health insurance experiment’s Medi- aid recipients only value Medicaid at 20–40 percent of Medicaid’s cost, suggesting hat many low-income workers may not fully value health insurance.
conomics 53 (2017) 1–16
Crowd-out of (2) or (3), on the other hand, will still make the family better off. If the family was paying full price for good cov- erage (case 2), then Medicaid functions as an income transfer to low-income families. As Bitler and Zavodny (2014) explain, these transfers are still welfare enhancing on average if societal prefer- ences put more weight on income at the bottom end of the income distribution than on income at the top end of the income distribu- tion. Under certain assumptions, risk aversion results in crowd-out of (3) being more welfare improving than crowd-out of (2), but in either case, Medicaid still makes these families better off. Refer to Appendix A for a discussion of these assumptions and the model that underlies these predictions.
To summarize the empirical predictions and implications, Med- icaid likely lowers medical expenditures, but there are also ways that Medicaid could increase medical expenditures. Medicaid crowding out private coverage would mean that Medicaid eligibil- ity should have a non-positive effect on health insurance spending. Finding that Medicaid eligibility reduces private health insurance coverage but not health insurance spending means that the family’s private insurance likely had very low benefits (and was therefore not costly) or that the cost-savings from Medicaid were passed through to firms.10 Finding a negative effect of Medicaid eligibil- ity on spending on health insurance suggests that the family was paying the premiums for private insurance prior to switching to Medicaid.
3. Medicaid variation, data, and estimation
3.1. Variation in Medicaid Eligibility
This paper uses variation in Medicaid eligibility that arises due to changes to the income thresholds for parents and children.11
As most of the CHIP expansions for children occurred in the late 1990s, the majority of the variation in this paper comes from expan- sions for parents. In 2000, the mean income threshold for parental Medicaid eligibility for states in the CEX was 76.7 percent of the FPL. By 2014, the