Office of Tax Analysis 

Working Paper 117

February 2019

Health Insurance Coverage from Administrative Tax 

Data

Ithai Z. Lurie* and James Pearce

The OTA Working Papers Series presents original research by the staff of the Office of Tax 

Analysis. These papers are intended to generate discussion and critical comment while 

informing and improving the quality of the analysis conducted by the Office. The papers are 

works in progress and subject to revision. Views and opinions expressed are those of the 

authors and do not necessarily represent official Treasury positions or policy. Comments are 

welcome, as are suggestions for improvements, and should be directed to the authors. OTA 

Working Papers may be quoted without additional permission. 

U.S. Department of the Treasury 

Office of Tax Analysis 

February 2019
 

 

HEALTH INSURANCE COVERAGE FROM ADMINISTRATIVE TAX DATA

February 2019

Ithai Z. Lurie1

 and James Pearce2

In this paper we present the first evidence from administrative tax data regarding the size of the 

uninsured population and the types of insurance coverage people have, exploring differences by 

age, gender, income and geography. Relying only on coverage reported to IRS by insurers yields 

significantly higher uninsured levels and rates (and lower levels and rates of any coverage 

during the year) compared to surveys (13.1% in tax data in 2016 vs. 8.8% and 10.1% in two 

commonly used survey data sets for individuals under the age of 65). However, adding 

coverage reported by taxpayers on individual income tax returns yields lower uninsured levels 

and rates compared with surveys (7.5%). The uninsured measures derived from tax data could 

be thought of as upper and lower bounds of the number of uninsured. The coverage reported by 

insurers includes only minimum essential coverage (as defined in the Affordable Care Act) while 

the self-reported taxpayer coverage information most likely includes additional forms of 

insurance.

Keywords: Health Insurance Coverage, Affordable Care Act (ACA), Uninsured, Administrative 

Tax Data

We would like to thank Janet McCubbin, David Brown, Kathryn Johnson, Ankur Patel, Tom Selden, Paul 

Jacob, Jessica Vistnes, Brett O’Hara, and Tami Gurley-Calvez. We also thank participants of the National 

Tax Association annual meetings in 2017 and participants from the Congressional Budget Office and Joint 

Committee on Taxation in a meeting where an earlier version of the paper was discussed. 

1 Ithai Lurie: Office of Tax Analysis, U.S. Department of the Treasury, Ithai.Lurie@treasury.gov.

2 James Pearce: Office of Tax Analysis, U.S. Department of the Treasury, James.Pearce@treasury.gov.

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Introduction 

The number or fraction of people with health coverage in the United States, the 

characteristics of the uninsured, and the sources of coverage for the insured have been debated 

for a long time (HHS, 2005). Most information about health coverage in the U.S. comes from

survey data.1 Although survey data contain rich demographic information, usually in a crosssectional form, it suffers from self-reporting problems and limited sample sizes, which likely

affect accuracy for both insurance and income measures. The misreporting of public program

coverage in surveys is well known (see Meyer, Mok, and Sullivan 2015). Although surveys have

attempted to limit misreporting of health insurance coverage, it might be the case that individuals

responding to the surveys still misunderstand whether they are covered or not. 

The Affordable Care Act (ACA) of 2010 legislated new reporting requirements for health 

insurance providers, creating administrative tax data detailing health insurance coverage for the

entire United States population. These new reporting requirements provide an opportunity to 

cross-check survey information about coverage. There are a few reasons why coverage levels (or

uninsurance) from survey data might differ from administrative data. First, survey and 

administrative information about coverage might differ in what constitutes coverage. In the tax

data we observe two types of coverage data: (i) insurer-reported minimum essential coverage 

(MEC, defined below) and (ii) self-reported full-year MEC. In surveys, respondents may report

coverage whether or not it is MEC. Unfortunately, the self-reported full-year MEC information 

from tax data might suffer the same problem because it is not third-party reported and people

might misunderstand the instructions or have the incentive to misreport MEC coverage. Second, 

1 The Census produces the Current Population Survey (CPS), the American Community Survey (ACS), and the

Survey of Income and Program Participation (SIPP). The Agency for Healthcare Research and Quality (AHRQ)

produces the Medical Expenditure Panel Survey (MEPS). The Center for Disease Control’s (CDC) National Center

for Health Statistics (NCHS) produces the National Health Interview Survey (NHIS).

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the underlying populations of administrative and survey data might differ. Most surveys report

coverage for civilian non-institutionalized U.S. residents. Tax data generally does not exclude 

the institutionalized population, and we generally cannot exclude such persons from our data. 

Furthermore, U.S. tax information is not limited to U.S. residents, and it is hard to exclude nonU.S. residents from the data.

2

 Third, under-reporting by insurance providers, including

employers, can occur in administrative data which may result in coverage undercounts.3 Finally, 

administrative data might misidentify an individual’s coverage. Insurance providers generally

use the name and Social Security Number (SSN) as an individual’s identifier, but may report date 

of birth (DOB) if the SSN is not known. Missing or misreported SSNs will make it difficult for 

us to identify persons who have insurance coverage and avoid double-counting people with 

multiple insurance sources. 

In this paper we present the first evidence from administrative tax data regarding the size

of the uninsured population and the types of insurance coverage people have, exploring

differences by age, gender, income, and geography. Tax data provides administrative coverage

data and administrative income data with a reduced reliance on self-reporting by individuals. 

This new information will help researchers increase knowledge about health coverage over time

by detailed income and fine geography.

Our analysis suggests that relying only on insurer-reported coverage information in the

tax data yields higher uninsured levels and rates (lower coverage levels and rates) compared to

surveys. Tax data shows that, in 2016, the full year uninsured rate for people under age 65 is

13.1% while the Medical Expenditure Panel Survey (MEPS) shows it at 8.8% and the Census’s

2 We include only tax information associated with a U.S. address, but some non-residents might have a U.S. address

where, for example, they conduct their U.S. business.

3 It is very hard to ascertain if and how much under-reporting there is. However, this issue should decline over time.

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Current Population Survey (CPS) shows it at 10.1%. However, adding self-reported coverage

information from the tax data yields lower uninsured levels and rates compared with surveys

(7.5% for the total population under age 65). 

Data 

Third Party Reporting on Forms 1095-A/B/C 

Health insurance providers are required to send a Form 1095 describing the type of

coverage a taxpayer receives to both the taxpayer and to the Internal Revenue Service (IRS), for 

purposes of administering the Premium Tax Credit (PTC) and the individual mandate to buy

health insurance (also known as the individual shared responsibility payment (ISRP)) under the 

ACA.

4

 Only “minimum essential coverage” (MEC) is reported. MEC includes governmentsponsored programs (Medicare, Medicaid, State Children’s Health Insurance Program, Veterans 

Affairs (VA) coverage, etc.), most employer-sponsored insurance, including self-insured 

coverage (ESI), individual market coverage (both on and off of the ACA Exchanges) and certain 

other coverage designated by the Department of Health and Human Services (HHS). It does not

include coverage that supplements Medicare plans, dental and vision benefits that are not part of

a comprehensive health plan, workers’ compensation coverage or coverage limited to a specific

disease or illness. 

For federal and state Exchange coverage, Exchanges issue Form 1095-A, which lists all 

individuals covered by a policy including the start and end dates of the coverage. Applicable

4 In addition to the 1095 information, other tax data gives some indication of health coverage but not the exact

nature of who is covered and for how long. Large employers need to report total ESI premiums on Form W-2. All

employers are required to report Health Savings Account (HSA) contributions through the employer on the Form

W-2. HSA contributions and distributions are reported in more detail on Forms 5498-SA and 1099-SA. Finally, selfemployed health insurance deductions and self-employed HSA contributions and distributions are also reported by

the taxpayer on their Form 1040.

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large employers (those with 50 or more full-time employees (including full-time equivalent

employees)) use Form 1095-C to provide information about the availability and affordability of 

an employer-sponsored insurance (ESI) offer. If these employers are self-insured, meaning they

provide the coverage themselves, they use part III of the form to list all individuals covered by a 

policy on a monthly basis. All other health insurance providers use Form 1095-B to list all 

individuals’ coverage by a policy on a monthly basis.5 The Form 1095-B includes codes to 

distinguish the following types of coverage: (1) Small Business Health Options Program 

(SHOP), (2) purchased ESI or small-employer self-insured coverage, (3) a governmentsponsored program, (4) individual market insurance (off-Exchange), (5) multiemployer plan, 

and (6) other designated MEC.

We group the sources of coverage and types of forms to simplify our analysis as follows:

A. ESI – includes individuals covered by a Part III, Form 1095-C policy, covered by a Form

1095-B policy identified as types (1), (2) or (5), or covered by TRICARE (which we

identify as Form 1095-Bs of type (3) with specific military issuer names);

B. Non-Group

a. Off-Exchange – includes individuals covered by a Form 1095-B policy of type (4)

or (6);

b. Exchange – includes individuals covered by a Form 1095-A policy;

C. Public

a. Medicare – includes individuals covered by a Form 1095-B policy of type (3)

with an issuer identified as Medicare;

5 See https://www.irs.gov/affordable-care-act/employers/information-reporting-by-providers-of-minimum-essentialcoverage for additional information on reporting requirements and Instructions for Form 1095-B 

(https://www.irs.gov/pub/irs-pdf/i109495b.pdf) for more information about these reporting requirements.

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b. VA – includes individuals covered by a Form 1095-B policy of type (3) with an

issuer identified as VA;

c. Medicaid –includes all remaining individuals covered by a Form 1095-B policy of

type (3) (excluding those already found to have TRICARE, Medicare, or VA

coverage);

D. Uninsured – includes individuals with no coverage indicated on any Form 1095.

An individual can be covered by multiple policies in a given month or across months. Hence, we

assign individuals multiple coverages for some months and partial-year coverage for some 

insurance types.

All three Forms 1095 require health insurance providers to list the name of each covered

individual and either the SSN or other taxpayer identification number (TIN). If the covered

individual does not have or the provider cannot obtain an SSN or other TIN, the provider may 

instead report the individual’s date of birth.

Self-reported full-year coverage information is also available in tax data on Form 1040. 

Specifically, there is a question on the Form 1040 that asks if the taxpayer, their spouse, and their

dependents all had qualifying health insurance coverage, that is, MEC, for every month of the

year. If so, the taxpayer is directed to check a box indicating this on the Form 1040. Individuals

that check this box should also receive a Form 1095 documenting this coverage. Thus, the

checkbox can be used to cross-check the coverage information from Forms 1095-A/B/C. Some 

individuals report full-year coverage on the Form 1040, though we find no supporting Form

1095 documents for them. 

Because some individuals mark the checkbox but are not matched to supporting Form

1095 documents, we create a second “uninsured” measure that counts this self-reported

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coverage, resulting in a lower number of uninsured persons. We do not ascribe a specific 

coverage type to these people, however. We think of our two definitions as providing upper and 

lower bounds for the number and share of individuals that are uninsured (or covered) according

to administrative tax data. Using only Form 1095 information will undercount coverage if

providers did not send information to IRS or/and if we had trouble matching forms because of

missing SSNs for some individuals on Forms 1095. Using the checkbox information will 

overstate coverage because of possible self-reporting errors. 

Coverage information on Forms 1095 is reported on a monthly basis. Because not all 

surveys provide monthly information, we construct three measures of annual health insurance 

coverage. First, we construct an “ever-in-year” coverage measure by type of coverage (ESI,

non-group, etc.). Second, we construct a “whole year” coverage measure by type of coverage.

Finally, we construct a “covered life years” coverage measure by type of coverage. This third

measure weights each coverage type by the share of months a person had that coverage during

the year. It should be noted that all three of these measures allow individuals to have multiple

types of coverage during a year.

Data Construction and Restrictions 

We identify coverage for the population of individuals that are on a tax return or appear

on one of the major information returns.6 In order to make our population similar to survey data

we exclude all individuals with non-U.S. addresses and individuals who died during the year. 

6 In addition to Forms 1095-A/B/C, we use the following information returns: Form W-2 (wages), Form 1099-SSA 

(Social Security payments), Form 1099-INT (interest income), Form 1099-DIV (dividend income), Form 1098-E

(student loan interest paid), Form 1098-T (tuition statement), Form 1099-G (certain government payments including 

unemployment compensation), Form 1099-MISC (miscellaneous income), Form 1099-OID (original issue discount),

Form 1099-R (retirement distributions), Form W-2G (gambling winnings), Form 5498 (IRA contributions), Form

1098 (home mortgage interest paid), Form 1065-K1 (partnership income), and Form 1120-S-K1 (S corporation

income).

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Due to the fact that some covered individuals on Forms 1095 lack SSN identification, a

comprehensive matching of individuals’ coverage information can be complex. We identify

health coverage for individuals in three steps. First, we match all the individuals to IRS’s

administrative population of Forms 1095 using SSNs. The second and third steps attempt to deal

with the issue that some covered individuals in the Form 1095 data are missing their SSN. In the 

second step we link each Form 1095 for a covered person lacking a SSN to a tax unit by

matching the SSN of the policy holder to the SSN of a primary or secondary filer of a Form

1040. We then search within the tax unit for individuals (spouse or dependents) with the same

DOB as the covered person with the missing SSN. This step can be done only for individuals

who appear on a filed return. Note that this second step does not look outside the tax unit for

coverage with a missing SSN. The third step uses DOBs and first and last names to match the 

remaining covered individuals with missing SSN information on the Forms 1095 to all the

individuals in our population from the tax system.7 One worry with a match like this third step is 

false matches due to common names with the same DOB.8

Our final individual level data also includes information about gender, the state and zip 

code of residence, and income of the individuals. The income concept we use is Modified 

Adjusted Gross Income (MAGI) as defined by the ACA for purposes of calculating the premium

7 A population file consisting of SSN, first name, last name, and date of birth is used for this match. This population 

file was constructed using the Social Security Death Masterfile (DM1) and tax filing information (Forms 1040, W-2, 

1099-SSA, etc.). 

8 In 2016 there were 13.7 million covered observations missing SSN data out of 390.8 million total covered 

observations (3.5% of covered observations). Note that some individuals have multiple types of coverage during the 

year. Our second step matched 4.9 million of the missing SSN observations using primary filer policies (35.8%) and

an additional 1.7 million observations using secondary filer policies (12.4%). Our third step matched an additional 

2.5 million missing SSN observations using only names and DOBs (18.2%). Thus, we matched 9.2 million out of

13.7 million observations with missing SSN data (67.2%). This leaves 4.5 million unmatched observations with a

missing SSN (32.8%). Although we do not match 4.5 million observations, some of these unmatched individuals

might have received a corrected Form 1095 with the SSN or these individuals might have had coverage from 

another source or checked the Form 1040 checkbox for full year coverage. These types of occurrences would not

affect our overall coverage measures.

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tax credit. To account for the family size we divide income by the Health and Human Services

poverty thresholds.9

Analysis 

Health Insurance Coverage in Tax Data Verses Other Surveys 

Health insurance coverage data from the CPS is often cited as the official measure of

coverage, but it is not the only survey that reports coverage information. The Medical

Expenditure Panel Study (MEPS) Household Component and the American Community Survey

(ACS) are two other well-known sources for estimates of health insurance coverage. Table 1 

compares coverage estimates for individuals younger than 65 from the tax data, CPS, MEPS, and 

ACS for 2016 (Appendix Tables A1-A through A1-C show the comparison for all ages for 2016 

as well as the 2015 information). Estimates are presented for four separate coverage measures by

source of coverage: (1) ever in year; (2) whole year; (3) covered life years; and (4) point of

interview.10 Table 1A presents the number of people with each type of coverage while Table 1B

shows the share of individuals with each source of coverage by each coverage measure. The 

overall coverage and uninsured measures are presented two ways for the tax data. The first

measure includes only insurer-reported coverage from Forms 1095. The second measure

includes self-reported coverage from the Form 1040 checkbox, in addition to the Form 1095 

information. 

9 MAGI for tax filers is defined as AGI plus non-taxable social security plus tax exempt interest plus excluded

earned income from foreign sources. We also used information returns for non-filers to impute their MAGI. See

footnote 6 for a list of the information returns we used. The poverty definition is the same as that used for

calculation of PTC. The poverty threshold for year t is defined based on the HHS published levels as of year t-1. 

The number of exemptions on a tax return represents the number of people in the household and for non-filers we

assumed a family size of 1.

10 The point of interview measure is only used in ACS. This measure should most closely resemble our coveredlife-years measure.

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It is important to note in Table 1A that the tax-based population is roughly 7 million

people larger than the survey-based populations. There are a few likely reasons for this. First, the 

tax population includes everyone who has contact with the tax system. Although we limit our

data to individuals with a U.S. address, the data will still include people in the military and

individuals who live abroad but have a U.S. address for tax filing purposes.11 Second, the tax

data may also include anyone who is in the country at any point during the year compared to 

survey data which are usually point in time estimates. Hence, the tax data will include migrants

and births throughout the entire year. Third, the tax data include institutionalized persons who 

are somehow connected to the tax system, including incarcerated persons and hospitalized 

persons. 

Before describing the differences in coverage between our administrative data and 

surveys it should be noted that the information coming to IRS about coverage differs from the

definitions used in the surveys. As noted above, VA coverage is included in our measure of

public coverage while the MEPS does not count VA payments as coverage. Furthermore, we

include TRICARE in ESI coverage while some surveys include it as public coverage and others

as private coverage. When possible we aligned the survey information with our definition of

ESI.12

Table 1A shows that insurer-reported tax-based coverage is lower than coverage reported

by surveys. Using an ever-in-year measure, 2016 tax data shows 241.4 million covered 

individuals under the age of 65 (86.9%) compared with 246.6 million (91.2%) and 243.6 million

11 The CPS estimate of the civilian noninstitutionalized population for 2017 (which includes coverage data for 2016)

was 320.4 million. The institutionalized population is approximately 3.9 million people (see U.S. Census Bureau,

2017). The military population is roughly 1.4 to 1.5 million. Thus, the CPS population adjusted for institutionalized

and military population is roughly 326 million compared to our tax population of 326.7 million (see Appendix Table 

A-1C). 12 For example, in the MEPS construction we included TRICARE in our measure of ESI.

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(89.9%) covered individuals in the MEPS and CPS respectively. Most of the difference in

coverage is due to lower ESI counts in the tax data. The ESI counts from tax data are lower in 

all three of our coverage concepts (whole year, ever-in-year, and covered life years). For

example, using our ever-in-year concept for 2016, tax data shows 156.3 million individuals

under age 65 with ESI coverage compared with 171.8 million from MEPS and 164.9 from CPS, 

which is a 4.6 (CPS) and 7.3 (MEPS) percentage points difference. Given that we include

military coverage in ESI and surveys do not include the military population, the difference 

among the civilian population is likely understated. One explanation for the difference in 

coverage is that the insurer-reported administrative data counts only MEC coverage, while

surveys do not limit to this type of coverage.

Although ESI coverage in tax data is low relative to survey data, Table 1A shows that

public coverage for individuals under age 65 is significantly higher in the tax data compared with 

survey data, which is consistent with well-known under reporting of public coverage in survey

data (see Klerman, et. al. (2009) for example). Tax data shows that in 2016 there were 75.6 

million covered life years of public coverage for people under age 65. We focus specifically on 

Medicaid and Medicare coverage so that we can compare how well the tax information 

corresponds to administrative enrollment data from the Centers for Medicare and Medicaid 

Services (CMS). Appendix Table A-2F shows that in 2016 there were 66.8 million covered life

years of Medicaid coverage for individuals under age 65 in the tax data, similar to the CMS

reported average monthly enrollment of 65.2 million people. Note that our tax-based measure of

Medicaid includes some state-run programs that are not necessarily counted in the CMS measure 

(such as Basic Health Program coverage). Furthermore, Appendix Table A-2E shows that in 

2015 there were 8.5 million covered life years of Medicare coverage for individuals under age 65 

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while CMS reports 8.9 million. We exclude individuals that died during the year, which should 

explain some of the lower Medicare counts in our data.

A second important conclusion from Table 1A is that the self-reported coverage in the tax

data is much higher than survey data suggests. Specifically, adding self-reported information 

increases ever-in-year coverage by 15.7 million people (to 257.1 million people), which lowers

the whole year uninsured rate from 13.1% to 7.5%. One possible reason for this large difference

could be the 4.5 million coverage observations with missing SSNs that we were unable to match 

with our three step searching algorithm. However, if all of these 4.5 million observations were

new coverage, our insurer-reported uninsured rate would decrease from 13.1% to 11.5%, still 

leaving a large unexplained difference from the self-reported uninsured rate of 7.5%.13

There are a few plausible reasons for this additional self-reported coverage. First, some 

persons in the institutionalized population (like incarcerated individuals) might receive care from

the institution but would not receive a Form 1095.14 Second, people living abroad who file with a

U.S. address can have coverage in their country of residence but will not receive a Form 1095. 

Third, there might be some people who have coverage but either the coverage provider did not

send IRS the required Form 1095 or our matching algorithm missed them. Fourth, some

individuals might mistakenly report coverage that is not MEC on Form 1040. Finally, the tax

code incentivizes people to over report insurance via the checkbox because of the ISRP. 

However, giving non-truthful information on the tax form has the potential financial

consequences via audit which should attenuate misreporting. As mentioned above, we do not

13 Out of the 4.5 million coverage observations with missing SSNs on Form 1095 that we cannot match to other tax

data, 1.7 million had ESI coverage (38.6%), 1.9 million had Medicaid (43.0), and most of the rest had non-group

coverage. Slightly more than 2.5 million of these observations were under the age of 19 (56.7%) and an additional 1 

million were between the ages of 19 and 26 (23.4%). Finally, almost 1.8 million had coverage for the full year

(41.3%).

14 In fact, incarcerated individuals can claim an exemption from the ISRP on Form 8965. See Instructions for Form

8965 for more detail (https://www.irs.gov/pub/irs-pdf/i8965.pdf).

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assign individuals to specific sources of coverage when they self-report as covered on Form 1040 

but are not matched to any Form 1095 information returns. 

Patterns of Coverage by Income 

Using population data provides the opportunity to explore coverage by very granular

income and geography.15 Figure 1 to Figure 5 graph coverage by type of insurance and income

as a share of federal poverty level (FPL) using the ever-in-year concept for individuals younger 

than 65 years old.16 We collapse the data to one percent income/FPL bins of zero to 800 percent.

We also collapse all observations with negative MAGI together and show their average coverage 

rates at the -5 percent FPL for visual clarity. Similarly we collapse all individuals with MAGI 

above 800 percent of FPL together and show their averages at the 805 percent FPL. 

Figure 1 plots the share of individuals with each type of coverage by income as a percent

of FPL in 2016. Unsurprisingly, we observe that public coverage broadly falls as income rises 

while ESI coverage increases. Conversely, Exchange and off-Exchange individual coverage 

rates are fairly low across all income levels. On net, overall coverage increases with income. 

The difference between our two measures of overall coverage seems to be fairly constant across

income although it is a little larger between 50 to 300 percent of FPL. Finally, one can see 

evidence of coverage discontinuities for the Exchange coverage rates around the 100, 200, 300 

and 400 percent FPL levels as well as a discontinuity at 400 percent FPL for ESI.

17 These

discontinuities are the result of the PTC subsidy schedule and cost sharing reduction schedule

15 In the appendix we provide tables and graphs that show detailed coverage types by age, income and gender at a 

more aggregated levels.

16 We exclude the elderly because the vast majority of them are covered by Medicare.

17 Heim el al. (2018) and Isen et al. (2018) explore the nature of these discontinuities in detail.

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which both have kinks and sometimes notches at these income points, providing individuals the

incentive to bunch or have higher coverage take-up below or above a kink or a notch. 

The top two panels of Figure 2 plot similar graphs separately for states that expanded 

Medicaid eligibility to 138 percent FPL as allowed under the ACA and states that did not. The 

bottom two panels replot the data across expansion and non-expansion states by grouping each 

type of coverage to make it easier to compare. The top panel shows that both expansion and 

non-expansion states have similar differences in our two overall coverage measures, but 

coverage at lower income levels is higher in expansion states. This is the effect of Medicaid

expansion on coverage, and it is more visible in the bottom panels of Figure 2. There is a 

slightly higher ESI and Exchange coverage in the non-expansion states compared with their

expansion state counterparts. For higher income individuals (over 400 percent FPL) there is very

little differences in coverage rates between expansion and non-expansion states. 

An interesting trend observable in Figures 1 and 2 is that the effect of self-reported 

coverage is larger for lower income individuals. Figure 3 plots this difference between selfreported overall coverage and insurer-reported coverage by age and income. Across all ages

individuals with income between 50 and 250 percent of FPL are more likely to self-report

(without supporting Form 1095 documentation) that they have coverage compared with other

individuals. Low income 27-44 year old individuals have the highest discrepancy between selfreported coverage and insurer-reported coverage. One worry might be that a disproportionate

share of the 4.5 million Form 1095 coverage observations with missing SSNs that we were

unable to match might be low income. As noted above, if all of these 4.5 million observations

were new coverage, our insurer-reported uninsured rate would decrease from 13.1 percent to 

11.5 percent still leaving a large unexplained difference from the self-reported uninsured rate of 

7.5 percent.

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Figure 4 plots coverage for different age groups on a single graph for a single type of

coverage allowing direct comparisons. Note that the off-Exchange individual coverage and 

Exchange coverage plots feature differently-scaled vertical axes (0 to 25 percent) than the Public 

and ESI graphs (0 to 100 percent) to allow for more detail of the differences in coverage by age. 

The Exchange plot highlights the discontinuities from the premium tax credit subsidy schedule

that we saw in Figure 1 with pronounced distortions at the 100 and 400 percent FPLs across all 

age groups. There is a high Exchange coverage rate just below 400 percent FPL, consistent with 

individual behavior to adjust incomes to retain subsidy eligibility (Isen et al. (2018)). Exchange 

coverage rates increase with age generally and the discontinuities are the most noticeable for the 

oldest age group. 

Figure 5 depicts coverage by gender, focusing on working age adults 19-64 because we 

should not see large coverage differences by gender for children and elderly. The top two panels

of Figure 5 plot all types of coverage separately for males and females while the bottom two 

panels replot the data by grouping each type of insurance to make it easier to compare. As with

the overall population the difference in insurer-reported coverage versus self-reported coverage 

are similar across gender. Overall coverage for females seems to be higher than coverage for

males at the low end of the income distribution. Public coverage seems to be driving most of this

this gap, although women also tend to have slightly higher ESI and Exchange coverage rates

compared to men. 

Geographical Patterns of Coverage 

Figures 6 and 7 plot maps of the U.S. by county based on the share of people who are 

uninsured. Figures 8 plots the additional coverage from including the Form 1040 checkbox

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while Figures 9 through 12 plot county coverage rates by insurance type. Each map sorts

counties into coverage (or uninsurance) quintiles weighted by population and shades each county

according to its coverage (or uninsurance) quintile level. Counties with darker shading have

higher rates of coverage (or uninsurance), except that black represents “No data”, meaning that

the county had fewer than 10 observations for at least one type of coverage (or uninsurance). 

Figures 6 and 7 show the pattern of uninsured rates for our two uninsured definitions. 

Although uninsured rates using the self-reported checkbox and Forms 1095 are significantly

lower than Form 1095-only uninsured rates, the geographical patterns are similar, with uninsured 

rates being higher in states that did not expand Medicaid, as well as in southern states and in 

rural areas. These two sets of figures compare well with a similar graph from Census’s small 

area estimates of the uninsured (see Bowers, Gann, and Upton (2018)). The major advantage of

the tax data compared to Census is that it is a population instead of a sample which makes the

estimates more precise. It can enable us to use even smaller geographic levels. Also, as years go

by the data can be structured as a panel and can be used for dynamic analysis at small geographic 

areas.

Figure 8 shows the geographic variation in the additional coverage from including the

self-reported information with insurer-reported coverage data (i.e., the difference between our

two tax-based coverage measures). Although the ACA created fairly homogenized non-group 

market rules which should have made states look similar in coverage patterns, the existence of

different Medicaid expansion policy between states and other states characteristics result in

interesting state variation. Figure 8 shows that state lines, and sometimes with-in state county

lines, matter for the propensity to have self-reported coverage without supporting Form 1095 

information. The northeast and mid-west generally have lower rates of self-reported coverage 

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without supporting Form 1095 documentation, while the south (especially Mississippi), the

south-west and Rocky Mountain states have higher rates.

Figure 9 shows that the Exchange coverage is more prevalent, not surprisingly, in states

that did not expand Medicaid coverage, as well as in New England, Florida and the upper-west.

In contrast to Exchange coverage, off-Exchange individual coverage (Figure 10) tends to be

concentrated in the mid-west and it seems to be correlated with rural areas there. Figure 11 

shows public coverage rates by counties. The states with higher public coverage seem to be the

ones that expanded Medicaid coverage as a result of the ACA. 

Figure 12 shows ESI rates by geography. There seems to be large variation in coverage 

across states and counties. The south-west seems to have low ESI rates while North Dakota has

very high rates.

Finally, all of the geographical figures show stark differences in coverage rates across

state boundaries suggesting the importance that state policy decisions can have on coverage

rates. For example, Figure 8 shows how different uninsured rates are between the border

counties of Texas and Louisiana although one might not expect those counties to differ very

much demographically.

Summary 

In this paper we present a first look at the health insurance information from new

administrative tax data. In many respects the data corroborates survey data coverage rates

overall. When comparing the insurer-reported coverage totals to survey data we see that

administrative coverage totals fall short compared to surveys (and uninsurance is higher).

However, when we supplement the administrative information with self-reported assertions of 

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full-year coverage by taxpayers the coverage totals exceed the totals from surveys (and the 

uninsured totals are lower). Administrative data compares well with MEPS data for non-group 

markets. ESI coverage in the administrative tax data is significantly lower than ESI reported in

both MEPS and CPS data which might be a result of coverage not being limited to MEC in 

survey data or some reporting issues in the administrative tax data that prevents matching

coverage to individuals (or both). Additionally, public coverage in the tax data is significantly

higher than in survey data, but agrees well with administrative enrollment data from CMS.

One feature of the current administrative data is the existence of two measures of what

constitutes coverage. Ideally, those two measures should agree and they would be fairly similar

to survey information. As stated earlier, the reasons for the differences could be due to whether

certain types of insurance coverage are deemed MEC for ACA purposes, confusion by taxpayers

about how to answer tax questions, lack of reporting on Forms 1095 by some coverage 

providers, or the failure to match some insurer reports to individuals in the population. Probably

the best way to think of the two uninsured measures from tax data is as upper and lower bounds. 

Alternatively, another way to interpret our two uninsured measures is as one measuring lack of

MEC (insurer-reported Form 1095 data only) and the other measuring the lack of any coverage 

(Form 1095 and self-reported Form 1040 data combined). 

The data presented shows the richness of the data and the potential research value of

having longitudinal population data on health coverage combined with administrative income

and demographic information. Using this detailed information we showed coverage differences

by income, geography, age and gender at very fine levels that current surveys are not providing. 

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References 

Barnett, Jessica C. and Edward R. Berchick (2017). Health Insurance Coverage in the United 

States: 2016, Current Population Reports P60-260, U.S. Census Bureau, Washington, DC. 

Bowers, L., C. Gann, and R. Upton (2018). Small Area Health Insurance Estimates: 2016, 

Current Population Reports, P30-03, U.S. Census Bureau, Washington, DC. 

Department of Health and Human Services (2005). Understanding Estimates of the Uninsured: 

Putting the Differences in Context, ASPE Issue Brief, September 2005.

Heim, Bradley T., Gillian Hunter, Adam Isen, Ithai Z. Lurie, and Shanthi P. Ramnath (2018). 

“Income Responses to the Affordable Care Act: Evidence from a Premium Tax Credit Notch”,

unpublished manuscript. 

Klerman, Jacob A., Michael Davern, Kathleen Thiede Call, Victoria Lynch, and Jeanne D.

Ringel (2009). “Understanding The Current Population Survey’s Insurance Estimates And The

Medicaid ‘Undercount’”, Health Affairs, Vol. 28, No. 6, p.w991-w1001.

Meyer, Bruce D., Wallace K.C. Mok, and James X. Sullivan (2015). “Household Surveys in 

Crisis”, Journal of Economic Perspectives, Vol. 29, No. 4, Fall 2015, p.199-226. 

Smith, Jessica C. and Carla Medalia (2014). Health Insurance Coverage in the United States: 

2013, Current Population Reports, P60-250, U.S. Census Bureau, Washington, DC. 

Sommers, Benjamin D. and Sara Rosenbaum (2011). “Issues In Health Reform: How Changes

In Eligibility May Move Millions Back And Forth Between Medicaid And Insurance

Exchanges,” Health Affairs Vol. 30, No. 2, p.228–236. 

U.S. Census Bureau (2017). Monthly Population Estimates for the United States: April 1, 2010 

to December 1, 2017, U.S. Census Bureau, Population Division. Release Date: December 2016.

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Table 1A: Comparing Tax Based Coverage to Survey Reporting, 2016 

Number (in 000s) of Individuals Younger than 65 by Type of Health Insurance Coverage 

Uninsured Uninsured 

Reference Period Data Source ESI Non-Group Public Overall (1) Overall (2) (1) (2) Population 

Ever In Year Tax 156,274 22,082 85,452 241,351 257,096 72,900 36,049 277,864 

MEPS 171,758 21,415 71,140 246,561 -- 56,064 -- 270,481 

CPS 164,913 37,945 73,220 243,644 -- -- -- 271,098 

Whole Year Tax 131,710 13,561 63,366 204,964 241,815 36,513 20,767 277,864 

MEPS 148,895 13,301 50,975 214,417 -- 23,920 -- 270,481 

CPS -- -- -- -- -- 27,454 -- 271,098 

Covered Life Years Tax 144,933 17,945 75,559 226,856 250,344 51,007 27,520 277,864 

MEPS 161,775 17,785 62,094 234,133 -- 36,348 -- 270,481 

Point of Interview ACS 164,027 29,500 66,609 243,338 -- 26,932 -- 270,270 

Table 1B: Comparing Tax Based Coverage to Survey Reporting, 2016 

Share of Individuals Younger than 65 by Type of Health Insurance Coverage 

Uninsured Uninsured 

Reference Period Data Source ESI Non-Group Public Overall (1) Overall (2) (1) (2)

Ever In Year Tax 56.2% 7.9% 30.8% 86.9% 92.5% 26.2% 13.0% 

MEPS 63.5% 7.9% 26.3% 91.2% -- 20.7% --

CPS 60.8% 14.0% 27.0% 89.9% -- -- --

Whole Year Tax 47.4% 4.9% 22.8% 73.8% 87.0% 13.1% 7.5% 

MEPS 55.0% 4.9% 18.8% 79.3% -- 8.8% --

CPS -- -- -- -- -- 10.1% --

Covered Life Years Tax 52.2% 6.5% 27.2% 81.6% 90.1% 18.4% 9.9% 

MEPS 59.8% 6.6% 23.0% -- -- 13.4% --

Point of Interview ACS 60.7% 10.9% 24.6% 90.0% -- 10.0% --

Note: Individuals can appear in multiple coverage statuses. Hence, summing across a row will not add up to the tax-based population. Overall (1) and Uninsured (1) use only insurer-reported Form 

1095 information. Overall (2) and Uninsured (2) supplements Form 1095 information with self-reported information from Form 1040. Our definition of non-group coverage in the MEPS includes

individuals that are covered by either an Exchange policy, a non-group policy outside the Exchange, a self-employed policy, other private insurance, or individuals with an unknown source of private

insurance. ESI coverage includes individuals that reported an employer or union as their source of insurance, private insurance held by a policyholder outside the household, or TRICARE.

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States 

100% 

• 

"'O 

Q) 

I... 60% Q) 

> 

0 

u 

Q) 

I... 

cu 40% 

..c 

(j) 

20% 

0% 

0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL 

• Overall ( 1) • ESI · Exchange 

• Overall (2) • Public · Off Exchange 

Figure 1: Coverage for Individuals Younger than 65 by Type of Insurance and Income as a Share of FPL, 2016

Note: Population data of ever-in-year coverage for individuals under age 65 in 2016 with a U.S. address. Overall (1) uses only insurer-reported Form

1095 information and Overall (2) supplements Form 1095 information with self-reported information from Form 1040.

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100% 

80% 

"C * 60% 15 

u 

~ 40% .r:. 

Cf) 

"C 

20% 

0% 

100% 

80% 

['! 

~ 60% 0 

u 

~ 40% .r:. 

Cf) 

20% 

Expansion States 

0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL 

• Overall (1) ESI • Exchange 

• Overall (2) Public · Off Exchange 

Expansion Versus Non-Expansion States 

0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL 

• Overall (1 )- Exp. • Public - Exp. Exchange - Exp. 

• Overall (1) - Non-Exp. • Public - Non-Exp. Exchange - Non-Exp. 

"C 

100% 

80% 

"C * 60% 15 

u 

~ 40% .r:. 

Cf) 

100% 

20% 

['! 

~ 60% 0 

u 

~ 40% .r:. 

Cf) 

20% 

0% 

Non-Expansion States 

0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL 

• Overall (1) ESI · Exchange 

• Overall (2) Public · Off Exchange 

Expansion Versus Non-Expansion States 

100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL 

• Overall (2) - Exp. • ESI - Exp. · Off-Exchange - Exp. 

• Overall (2) - Non-Exp. • ESI - Non-Exp. • Off-Exchange - Non-Exp. 

Figures 2: Coverage for Individuals Younger than 65 by Type of Insurance, Expansion vs. Non-Expansion States, 2016 

Note: Population data of ever-in-year coverage for individuals under age 65 in 2016 with a U.S. address. Overall (1) uses only insurer-reported Form

1095 information and Overall (2) supplements Form 1095 information with self-reported information from Form 1040.

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20% 

"O 

Q) 

I... 

Q) 15% 

> 

0 

0 

Q) 

I... 

co 10% ..c 

(j) 

5% 

0% 

0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL 

• Ages 0-18 • Ages 19-26 

• Ages 27-44 • Ages 45-64 

Figure 3: Additional Coverage from Self-Reported Checkbox from Form 1040 by Age and Income as a Share of FPL, 2016

Note: Population data of ever-in-year coverage for individuals under age 65 in 2016 with a U.S. address. 

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Public Exchange 

100% 25% 

80% 20% 

"C "C 

~ ~ 15% Q) Q) 

> > 0 0 u u 

~ 40% ~ 

.r:. "' .r:. "' Cf) Cf) 

5% 

0% 0% 

0% 100% 200% 300% 400% 500% 600% 700% 800% 0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL Income as a Share of FPL 

• Ages0-18 • Ages 19-26 • Ages 0-18 • Ages 19-26 

• Ages 27-44 • Ages 45-64 • Ages 27-44 • Ages 45-64 

ESI Off-Exchange 

100% 25% 

80% 20% 

"C "C 

~ 60% ~ 15% Q) Q) 

> > 0 0 

u u ~ 40% ~ 10% .r:. "' .r:. "' Cf) Cf) 

20% 5% • • ' ---

::::i;;-•. ~ 

0% 0% 

0% 100% 200% 300% 400% 500% 600% 700% 800% 0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL Income as a Share of FPL 

• Ages 0-18 • Ages 19-26 • Ages 0-18 • Ages 19-26 

• Ages 27-44 • Ages 45-64 • Ages 27-44 • Ages 45-64 

Figure 4: Distribution of Coverage by Age and Income as a Share of FPL, 2016 

Note: Population data of ever-in-year coverage for individuals under age 65 in 2016 with a U.S. address. 

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W ork ing Age Male Working Age Female 

100% 100% 

80% 

"C "C 

~ 60% ~ 60% Q) Q) 

> > 0 0 u u 

~ 40% ~ 40% .r:. "' .r:. "' Cf) Cf) 

20% 20% 

0% 0% 

0% 100% 200% 300% 400% 500% 600% 700% 800% 0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL Income as a Share of FPL 

• Overall (1) ESI • Exchange • Overall (1) ESI · Exchange 

• Overall (2) Public · Off Exchange • Overall (2) Public · Off Exchange 

Working Age Male Versus Female Working Age Male Versus Female 

100% 100% 

80% 80% 

"C "C 

~ 60% ~ 60% Q) Q) 

> > 0 0 

u u ~ 40% ~ 40% .r:. "' .r:. "' Cf) Cf) 

20% 20% 

0% 0% 

0% 100% 200% 300% 400% 500% 600% 700% 800% 0% 100% 200% 300% 400% 500% 600% 700% 800% 

Income as a Share of FPL Income as a Share of FPL 

• Overall (1) - Male Public - Male Exchange - Male • Overall (2) - Male ESI - Male Off-Exchange - Male 

• Overall (1) - Female Public - Female Exchange - Female • Overall (2) - Female ESI - Female Off-Exchange - Female 

Figure 5: Coverage for Individuals Younger than 65 by Gender and Income as a Share of FPL, 2016

Note: Population data of ever-in-year coverage for individuals under age 65 in 2016 with a U.S. address. Overall (1) uses only insurer-reported Form

1095 information and Overall (2) supplements Form 1095 information with self-reported information from Form 1040.

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% Uninsured 

• 10.1 - 38.8 

D 7.9 - 10.1 

D 6.1 - 7.9 

D 4 .3- 6.1 

D 1.8 - 4.3 

• No data 

Figure 6: Share of Individuals Younger than 65 Uninsured by County Including Self-Reported Checkbox from Form 1040, 2016 

Note: Population data of ever-in-year coverage for all individuals under age 65 in 2016 with a U.S. address. To comply with disclosure rules we

include counties with 10 or more observations for each type of insurance. Excluded counties are labeled “No data”.

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% Uninsured 

• 16.6 - 50.1 

D 14.1 - 16.6 

D 11.2 - 14.1 

D 8 .8-11.2 

D 3.7 - 8.8 

• No data 

Figure 7: Share of Individuals Younger than 65 Uninsured by County Excluding Self-Reported Checkbox from Form 1040, 2016 

Note: Population data of ever-in-year coverage for all individuals under age 65 in 2016 with a U.S. address. To comply with disclosure rules we 

include counties with 10 or more observations for each type of insurance. Excluded counties are labeled “No data”. 

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Add'I 0

/o Insured 

• 7.1 - 25.2 

D 5.9 - 7.1 

D 5.1 - 5.9 

D 4 .1 - 5.1 

D 1.2 - 4.1 

• No data 

Figure 8: Additional Coverage from Self-Reported Checkbox on Form 1040 for Individuals Younger than 65 by County, 2016

Note: Population data of ever-in-year coverage for all individuals under age 65 in 2016 with a U.S. address. To comply with disclosure rules we

include counties with 10 or more observations for each type of insurance. Excluded counties are labeled “No data”. 

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% Exchange 

• s.s- 24.2 . 4.7 - 5.5 

 3.8-4.7 

D 3.0- 3.8 

 0.3 - 3.0 

• No data 

Figure 9: Share of Individuals Younger than 65 Covered by Non-Group Exchange by County, 2016

Note: Population data of ever-in-year coverage for all individuals under age 65 in 2016 with a U.S. address. To comply with disclosure rules we

include counties with 10 or more observations for each type of insurance. Excluded counties are labeled “No data”. 

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Off-Exchange 

• 4.9-27.5 • 3.8 - 4 .9 

D 2.9- 3.8 

 2.1 - 2.9 

D 0.2 - 2.1 

• No data 

Figure 10: Share of Individuals Younger than 65 Covered by Non-Group Off-Exchange by County, 2016 

Note: Population data of ever-in-year coverage for all individuals under age 65 in 2016 with a U.S. address. To comply with disclosure rules we

include counties with 10 or more observations for each type of insurance. Excluded counties are labeled “No data”. 

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% Public 

• 38.2 - 72.6 

• 32.2 - 38.2 

D 27.9 - 32.2 

D 22.9-27.9 

D 4.3 - 22.9 

• No data 

Figure 11: Share of Individuals Younger than 65 Covered by Public Insurance by County, 2016

Note: Population data of ever-in-year coverage for all individuals under age 65 in 2016 with a U.S. address. To comply with disclosure rules we

include counties with 10 or more observations for each type of insurance. Excluded counties are labeled “No data”.

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% ESI 

• 65.2-85.4 

• 58.9 - 65.2 

D 53.6 - 58.9 

D 47.8- 53.6 

D 11.6 - 47.8 

• No data 

Figure 12: Share of Individuals Younger than 65 Covered by Employer-Sponsored Insurance (ESI) by County, 2016

Note: Population data of ever-in-year coverage for all individuals under age 65 in 2016 with a U.S. address. To comply with disclosure rules we

include counties with 10 or more observations for each type of insurance. Excluded counties are labeled “No data”.

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Appendix Tables 

Table A - 1A: Comparing Tax Based Coverage to Survey Reporting, 2015 

Number (in 000s) of Individuals Younger than 65 by Type of Health Insurance Coverage 

Reference Period Data Source ESI Non-Group Public Overall(1) Overall(2) Uninsured(1) Uninsured(2) Population 

Ever In Year Tax 153,363 22,808 79,621 234,422 254,388 81,129 38,500 277,429 

MEPS 168,720 22,890 71,602 245,141 -- 59,449 -- 270,633 

CPS 164,206 39,042 73,786 242,862 -- -- -- 271,322 

Whole Year Tax 128,291 12,870 58,402 196,300 238,929 43,008 23,041 277,429 

MEPS 145,306 13,923 51,181 211,184 -- 25,492 -- 270,633 

CPS -- -- -- -- -- 28,460 -- 271,322 

Covered Life Years Tax 141,683 18,158 70,134 219,142 247,535 58,288 29,895 277,429 

MEPS 159,060 18,580 62,585 232,465 -- 38,168 -- 270,633 

Point of Interview ACS 162,589 28,836 65,198 240,648 -- 29,366 -- 270,014 

Table A-1B: Comparing Tax Based Coverage to Survey Reporting, 2015 

Number (in 000s) of Individuals by Type of Health Insurance Coverage 

Reference Period Data Source ESI Non-Group Public Overall (1) Overall (2) Uninsured(1) Uninsured(2) Population 

Ever In Year Tax 162,941 23,633 125,393 280,664 301,121 82,888 39,411 324,711 

MEPS 187,710 32,999 120,895 295,274 -- 63,439 -- 321,423 

CPS 177,540 52,057 118,395 289,903 -- -- -- 318,869 

Whole Year Tax 136,480 13,230 101,769 241,823 285,300 44,047 23,590 324,711 

MEPS 161,025 20,686 95,597 257,984 -- 26,149 -- 321,423 

CPS -- -- -- -- -- 28,966 -- 318,869 

Covered Life Years Tax 150,564 18,746 114,695 265,073 294,103 59,638 30,608 324,711 

MEPS 176,322 27,317 109,406 280,778 -- 40,645 -- 321,423 

Point of Interview ACS 180,707 43,633 109,874 286,693 -- 29,758 -- 316,451 

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Table A-1C: Comparing Tax Based Coverage to Survey Reporting, 2016 

Number (in 000s) of Individuals by Type of Health Insurance Coverage 

Reference Period Data Source ESI Non-Group Public Overall (1) Overall (2) Uninsured(1) Uninsured(2) Population 

Ever In Year Tax 167,039 23,096 132,750 289,157 305,382 74,580 36,929 326,681 

MEPS 190,065 32,430 122,098 298,533 -- 60,211 -- 323,142 

CPS 178,455 51,961 119,361 292,320 -- -- -- 320,372 

Whole Year Tax 141,145 14,068 108,151 252,101 289,752 37,524 21,299 326,681 

MEPS 163,969 20,965 96,997 262,930 -- 24,609 -- 323,142 

CPS -- -- -- -- -- 28,052 -- 320,372 

Covered Life Years Tax 155,030 18,702 121,604 274,377 298,472 52,304 28,209 326,681 

MEPS 178,420 27,440 110,664 284,405 -- 38,737 -- 323,142 

Point of Interview ACS 182,473 44,815 112,688 290,872 -- 27,304 -- 318,176 

Note: Individuals can appear in multiple coverage statuses. Hence, summing across a row will not add up to the tax-based population (in Tables A-1A, A-1B and A-1C). Overall (1) and Uninsured (1)

use only insurer-reported Form 1095 information. Overall (2) and Uninsured (2) supplements Form 1095 information with self-reported information from Form 1040. Our definition of non-group

coverage in the MEPS includes individuals that are covered by either an Exchange policy, a non-group policy outside the Exchange, a self-employed policy, other private insurance, or individuals

with an unknown source of private insurance. ESI coverage includes individuals that reported an employer or union as their source of insurance, private insurance held by a policyholder outside the

household, or TRICARE.

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Table A-2A: Ever in Year Composition of Coverage by Age, 2015 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

Age Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 19 37,642 3,419 1,102 2,387 36,287 2 36,250 56 70,980 77,023 20,877 7,291 80,789 

Ages 19-26 20,573 3,067 1,377 1,765 8,893 205 8,688 173 29,042 31,940 13,406 6,664 35,731 

Ages 27-44 43,850 6,718 3,739 3,120 16,139 1,699 14,056 1,526 61,003 67,021 27,240 14,369 76,113 

Ages 45-64 51,297 9,604 5,713 4,085 18,302 6,906 11,582 2,713 73,397 78,405 19,607 10,177 84,796 

65 + 9,579 824 316 514 45,772 45,061 4,551 4,207 46,243 46,733 1,759 911 47,282 

Overall 162,941 23,633 12,248 11,871 125,393 53,872 75,127 8,675 280,664 301,121 82,888 39,411 324,711 

Table A-2B: Ever in Year Composition of Coverage by Age, 2016 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

Age Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 19 37,756 3,250 1,265 2,043 38,603 2 38,571 50 72,883 77,252 18,055 6,467 80,249 

Ages 19-26 21,018 2,943 1,436 1,575 9,688 194 9,518 150 29,880 32,235 12,274 6,277 35,635 

Ages 27-44 45,179 6,507 3,925 2,716 17,873 1,658 15,882 1,539 63,440 68,397 25,079 13,735 76,809 

Ages 45-64 52,321 9,383 5,971 3,576 19,288 6,915 12,824 2,626 75,146 79,212 17,492 9,570 85,170 

65 + 10,765 1,014 399 622 47,297 46,528 4,916 4,164 47,806 48,286 1,681 880 48,818 

Overall 167,039 23,096 12,996 10,531 132,750 55,297 81,711 8,527 289,157 305,382 74,580 36,929 326,681 

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Table A-2C: Whole Year Composition of Coverage by Age, 2015 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

Age Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 19 31,289 2,050 400 1,619 27,639 2 27,601 49 59,913 73,498 9,809 3,767 80,789 

Ages 19-26 16,113 1,435 454 960 4,935 165 4,758 124 22,325 29,067 6,690 3,792 35,731 

Ages 27-44 35,115 3,349 1,368 1,927 10,805 1,578 8,662 1,418 48,873 61,744 15,110 9,092 76,113 

Ages 45-64 45,774 6,037 2,824 3,134 15,022 6,389 8,298 2,599 65,189 74,619 11,399 6,391 84,796 

65 + 8,190 360 65 295 43,367 42,446 3,747 4,067 45,523 46,371 1,039 548 47,282 

Overall 136,480 13,230 5,112 7,935 101,769 50,579 53,066 8,257 241,823 285,300 44,047 23,590 324,711 

Table A-2D: Whole Year Composition of Coverage by Age, 2016 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

Age Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 19 31,646 2,015 575 1,427 29,833 1 29,800 45 62,194 73,782 7,365 2,996 80,249 

Ages 19-26 16,575 1,492 618 866 5,511 157 5,361 106 23,361 29,358 5,755 3,400 35,635 

Ages 27-44 36,507 3,575 1,830 1,726 12,109 1,547 10,025 1,448 51,730 63,074 13,369 8,412 76,809 

Ages 45-64 46,982 6,478 3,633 2,829 15,912 6,428 9,359 2,520 67,679 75,600 10,024 5,958 85,170 

65 + 9,435 507 88 419 44,785 43,816 4,014 4,029 47,137 47,938 1,012 532 48,818 

Overall 141,145 14,068 6,743 7,267 108,151 51,950 58,559 8,147 252,101 289,752 37,524 21,299 326,681 

36 

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February 2019
 

 

Table A-2E: Covered Life Year Coverage by Age, 2015 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

Age Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 19 34,633 2,740 758 1,991 32,723 2 32,685 53 66,684 75,626 14,105 5,164 80,789 

Ages 19-26 18,430 2,276 937 1,357 7,062 184 6,872 148 26,211 30,585 9,520 5,147 35,731 

Ages 27-44 39,848 5,113 2,615 2,519 13,624 1,639 11,514 1,473 56,059 64,565 20,054 11,547 76,113 

Ages 45-64 48,772 8,029 4,462 3,604 16,725 6,645 10,005 2,657 70,187 76,759 14,609 8,037 84,796 

65 + 8,881 588 191 399 44,562 43,731 4,156 4,138 45,931 46,568 1,351 714 47,282 

Overall 150,564 18,746 8,962 9,869 114,695 52,202 65,232 8,469 265,073 294,103 59,638 30,608 324,711 

Table A-2F: Covered Life Year Coverage by Age, 2016 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

Age Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 19 34,877 2,637 919 1,731 34,991 2 34,958 48 68,796 75,890 11,453 4,359 80,249 

Ages 19-26 18,896 2,225 1,028 1,219 7,745 175 7,586 127 27,153 30,889 8,482 4,746 35,635 

Ages 27-44 41,249 5,056 2,875 2,221 15,157 1,604 13,125 1,494 58,699 65,941 18,110 10,868 76,809 

Ages 45-64 49,912 8,027 4,879 3,208 17,665 6,670 11,164 2,574 72,208 77,624 12,963 7,547 85,170 

65 + 10,097 757 242 518 46,046 45,160 4,487 4,097 47,520 48,128 1,297 689 48,818 

Overall 155,030 18,702 9,943 8,897 121,604 53,611 71,321 8,340 274,377 298,472 52,304 28,209 326,681 

Note: Individuals can appear in multiple coverage statuses. Hence, summing across a row will not add up to the tax-based population (in Tables A-2A through A-2F). Overall (1) and Uninsured (1)

use only insurer-reported 1095 information. Overall (2) and Uninsured (2) supplements 1095 information with self-reported information from Form 1040.

37 

U.S. Department of the Treasury 

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February 2019
Table A-3A: Ever in Year Composition of Under 65 Coverage by Income Group, 2015 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

FPL Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 100% 10,897 3,945 2,343 1,683 38,609 2,806 37,003 956 49,215 54,195 26,959 16,773 64,537 

100-133% 5,900 1,730 1,319 448 11,064 1,501 9,990 322 16,588 18,891 9,300 4,660 22,013 

133-150% 3,545 938 717 242 4,491 558 4,011 157 7,890 8,870 4,129 2,018 10,156 

150-200% 11,715 2,673 1,994 742 9,204 1,086 8,095 414 20,738 22,994 9,844 4,702 25,830 

200-250% 12,261 2,227 1,529 755 5,167 684 4,330 368 17,459 19,061 6,901 3,135 20,850 

250-300% 12,326 1,818 1,117 748 3,135 472 2,459 338 15,576 16,837 5,062 2,115 17,999 

300-400% 23,217 2,687 1,346 1,409 3,481 665 2,407 570 26,983 28,898 6,745 2,407 30,155 

400-500% 18,985 1,715 578 1,172 1,748 396 1,018 415 20,934 22,261 3,992 1,130 22,808 

500-600% 14,048 1,178 316 883 976 238 492 291 15,215 16,103 2,422 571 16,363 

Above 600% 40,468 3,897 674 3,275 1,744 406 771 637 43,824 46,277 5,774 989 46,719 

Overall 153,363 22,808 11,932 11,357 79,621 8,812 70,576 4,468 234,422 254,388 81,129 38,500 277,429 

38 

U.S. Department of the Treasury 

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February 2019
Table A-3B: Ever in Year Composition of Under 65 Coverage by Income Group, 2016 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

FPL Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 100% 10,735 3,854 2,438 1,491 41,240 2,812 39,839 906 51,393 55,076 24,025 15,425 64,112 

100-133% 5,791 1,661 1,324 369 11,883 1,505 10,860 307 17,101 18,933 8,187 4,147 21,630 

133-150% 3,534 903 720 201 4,890 552 4,431 149 8,158 8,983 3,762 1,853 10,135 

150-200% 11,876 2,594 2,032 616 10,114 1,078 9,051 397 21,490 23,454 9,183 4,424 26,065 

200-250% 12,574 2,177 1,600 624 5,664 677 4,852 359 18,046 19,436 6,476 3,020 21,126 

250-300% 12,701 1,786 1,199 625 3,400 468 2,741 330 16,073 17,141 4,720 2,070 18,259 

300-400% 23,833 2,614 1,474 1,196 3,686 655 2,628 566 27,626 29,174 6,153 2,385 30,402 

400-500% 19,431 1,636 644 1,023 1,811 389 1,086 415 21,323 22,343 3,522 1,128 22,879 

500-600% 14,311 1,123 358 784 999 233 517 291 15,434 16,100 2,090 574 16,354 

Above 600% 41,488 3,733 808 2,979 1,766 399 788 643 44,707 46,456 4,781 1,022 46,901 

Overall 156,274 22,082 12,596 9,909 85,452 8,769 76,795 4,364 241,351 257,096 72,900 36,049 277,864 

39 

U.S. Department of the Treasury 

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February 2019
Table A-3C: Whole Year Composition of Under 65 Coverage by Income Group, 2015 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

FPL Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 100% 7,027 1,944 888 1,024 29,218 2,640 27,447 899 37,577 47,763 15,321 10,341 64,537 

100-133% 3,853 839 563 262 8,257 1,413 7,096 302 12,713 17,353 5,425 3,122 22,013 

133-150% 2,439 465 316 142 3,217 520 2,716 146 6,028 8,138 2,266 1,286 10,156 

150-200% 8,535 1,340 875 444 6,304 1,000 5,188 383 15,985 21,128 5,092 2,836 25,830 

200-250% 9,503 1,153 668 464 3,450 622 2,632 341 13,948 17,715 3,391 1,789 20,850 

250-300% 10,030 985 492 474 2,105 426 1,456 315 12,936 15,884 2,422 1,162 17,999 

300-400% 19,854 1,547 595 925 2,427 596 1,408 535 23,410 27,748 3,172 1,257 30,155 

400-500% 16,873 1,046 230 803 1,289 352 601 392 18,816 21,678 1,874 547 22,808 

500-600% 12,741 758 127 623 750 210 297 275 13,941 15,792 1,148 260 16,363 

Above 600% 37,435 2,793 293 2,477 1,385 354 479 603 40,944 45,730 2,894 442 46,719 

Overall 128,291 12,870 5,047 7,640 58,402 8,133 49,319 4,190 196,300 238,929 43,008 23,041 277,429 

40 

U.S. Department of the Treasury 

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February 2019
Table A-3D: Whole Year Composition of Under 65 Coverage by Income Group, 2016 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

FPL Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 100% 6,855 2,154 1,216 930 31,743 2,660 30,138 858 40,086 48,687 12,718 9,035 64,112 

100-133% 3,758 952 729 222 9,005 1,422 7,874 289 13,443 17,483 4,530 2,698 21,630 

133-150% 2,430 520 398 121 3,539 517 3,052 139 6,372 8,282 1,976 1,151 10,135 

150-200% 8,676 1,493 1,112 378 6,956 997 5,870 369 16,883 21,641 4,575 2,612 26,065 

200-250% 9,802 1,262 863 394 3,778 619 2,974 334 14,649 18,105 3,080 1,689 21,126 

250-300% 10,419 1,059 647 408 2,276 424 1,635 310 13,539 16,189 2,186 1,119 18,259 

300-400% 20,553 1,608 789 809 2,565 590 1,553 535 24,249 28,017 2,776 1,228 30,402 

400-500% 17,422 1,036 308 722 1,334 348 648 394 19,357 21,751 1,556 536 22,879 

500-600% 13,085 745 173 568 768 207 314 277 14,264 15,780 921 254 16,354 

Above 600% 38,710 2,731 419 2,297 1,401 350 487 612 42,120 45,879 2,195 445 46,901 

Overall 131,710 13,561 6,656 6,849 63,366 8,133 54,545 4,118 204,964 241,815 36,513 20,767 277,864 

41 

U.S. Department of the Treasury 

Office of Tax Analysis 

February 2019
Table A-3E: Covered Life Year Composition of Under 65 Coverage by Income Group, 2015 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

FPL Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 100% 8,702 2,991 1,656 1,348 34,636 2,724 32,957 930 44,246 51,254 20,291 13,283 64,537 

100-133% 4,814 1,330 986 351 9,860 1,458 8,742 313 14,992 18,188 7,021 3,825 22,013 

133-150% 2,982 726 541 190 3,930 540 3,439 152 7,132 8,538 3,024 1,618 10,156 

150-200% 10,163 2,076 1,505 585 7,884 1,043 6,770 398 18,823 22,155 7,007 3,675 25,830 

200-250% 10,990 1,737 1,145 603 4,344 652 3,515 354 16,065 18,464 4,785 2,386 20,850 

250-300% 11,316 1,431 833 606 2,622 449 1,959 326 14,549 16,422 3,449 1,576 17,999 

300-400% 21,800 2,147 996 1,162 2,941 630 1,894 552 25,632 28,417 4,523 1,738 30,155 

400-500% 18,130 1,389 406 988 1,508 374 799 404 20,155 22,029 2,653 779 22,808 

500-600% 13,527 972 221 754 856 223 388 283 14,755 15,985 1,608 378 16,363 

Above 600% 39,259 3,359 482 2,884 1,551 379 613 620 42,793 46,082 3,925 637 46,719 

Overall 141,683 18,158 8,771 9,470 70,134 8,470 61,076 4,332 219,142 247,535 58,288 29,895 277,429 

42 

U.S. Department of the Treasury 

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February 2019
 

 

 

Table A-3F: Covered Life Year Composition of Under 65 Coverage by Income Group, 2016 

Numbers in 000s. 

Non- Off- Overall Overall Uninsured Uninsured 

FPL Group ESI Group Exchange Exchange Public Medicare Medicaid VA (1) (2) (1) (2) Population 

Under 100% 8,517 3,017 1,832 1,210 37,194 2,737 35,705 884 46,542 52,140 17,570 11,971 64,112 

100-133% 4,712 1,329 1,048 293 10,643 1,464 9,569 298 15,594 18,267 6,036 3,364 21,630 

133-150% 2,973 723 570 160 4,297 535 3,825 144 7,435 8,665 2,700 1,469 10,135 

150-200% 10,327 2,077 1,603 495 8,683 1,037 7,608 382 19,644 22,640 6,421 3,426 26,065 

200-250% 11,313 1,739 1,249 507 4,765 648 3,957 346 16,707 18,849 4,418 2,276 21,126 

250-300% 11,715 1,433 931 515 2,844 446 2,194 320 15,099 16,731 3,160 1,528 18,259 

300-400% 22,482 2,118 1,133 1,001 3,118 622 2,082 551 26,372 28,699 4,030 1,703 30,402 

400-500% 18,640 1,336 469 874 1,564 368 858 405 20,620 22,114 2,259 766 22,879 

500-600% 13,838 935 261 678 878 220 410 284 15,025 15,982 1,329 372 16,354 

Above 600% 40,416 3,238 604 2,646 1,572 373 626 628 43,818 46,257 3,084 645 46,901 

Overall 144,933 17,945 9,701 8,379 75,559 8,451 66,834 4,244 226,856 250,344 51,007 27,520 277,864 

Individuals can appear in multiple coverage statuses. Hence, summing across a row will not add up to the tax-based population (in Tables A-3A through A-3F). Overall (1) and Uninsured (1) use only

insurer-reported Form 1095 information. Overall (2) and Uninsured (2) supplements Form 1095 information with self-reported information from Form 1040.

43 

U.S. Department of the Treasury 

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February 2019
 

 

 

      

      

Appendix Figures

Figure A-1: Share of Individuals Younger than 65 by Type of Coverage or Uninsurance by Gender, 2016 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

Male Female 

Uninsured All Year Rates by Data Source and 

Gender, 2015 

Tax (1) Tax (2) CPS MEPS 

0.0% 

20.0% 

40.0% 

60.0% 

80.0% 

100.0% 

Male Female 

Coverage Rates by Data Source and Gender, 

2015 

Tax (1) Tax (2) CPS MEPS 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

Male Female 

Uninsured All Year Rates by Data Source and 

Gender, 2016 

Tax (1) Tax (2) CPS MEPS 

0.0% 

20.0% 

40.0% 

60.0% 

80.0% 

100.0% 

Male Female 

Coverage Rates by Data Source and Gender, 

2016 

Tax (1) Tax (2) CPS MEPS 

Note: Population data of ever-in-year coverage or whole year uninsured for all individuals under age 65 in 2015 and 2016 with a U.S. address. Tax

(1) uses only insurer-reported Form 1095 information. Tax (2) supplements Form 1095 information with self-reported information from Form 1040.

44 

U.S. Department of the Treasury 

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February 2019
 

 

 

 

 

1. !!!!!! I 1111 11 I 1 11111 I 1 1. !~!!! 11 1111111 I 11111 ! I 1 

   rn    rn 

   iii    iii 

Figure A-2: Share of Individuals Younger than 65 by Type of Coverage or Uninsurance by Age, 2016 

0% 

5% 

10% 

15% 

20% 

25% 

Under 19 Ages 19-26 Ages 27-44 Ages 45-64 

Uninsured All Year Rates by Data Source and 

Age, 2015 

Tax (1) Tax (2) CPS MEPS 

0% 

5% 

10% 

15% 

20% 

25% 

Under 19 Ages 19-26 Ages 27-44 Ages 45-64 

Uninsured All Year Rates by Data Source and 

Age, 2016 

Tax (1) Tax (2) CPS MEPS 

0% 

20% 

40% 

60% 

80% 

100% 

Under 19 Ages 19-26 Ages 27-44 Ages 45-64 

Coverage Rates by Data Source and Age, 2015 

Tax (1) Tax (2) CPS MEPS 

0% 

20% 

40% 

60% 

80% 

100% 

Under 19 Ages 19-26 Ages 27-44 Ages 45-64 

Coverage Rates by Data Source and Age, 2016 

Tax (1) Tax (2) CPS MEPS 

Note: Population data of ever-in-year coverage or whole year uninsured for all individuals under age 65 in 2015 and 2016 with a U.S. address. Tax

(1) uses only insurer-reported Form 1095 information. Tax (2) supplements Form 1095 information with self-reported information from Form 1040.

45 

U.S. Department of the Treasury 

Office of Tax Analysis 

February 2019