Changing the CPS Health Insurance Questions And The 

Implications On The Uninsured Rate: 

Redesign and Production Estimates

Matthew Brault

Carla Medalia,

1

Ph.D.

Brett O’Hara, Ph.D.

Jonathan Rodean

Amy Steinweg

U.S. Census Bureau

4600 Silver Hill Road, Washington DC 20233

Proceedings of the 2013 Federal Committee on Statistical Methodology (FCSM) Research Conference

Presented on November 6, 2013

Paper updated February 3, 2014

DISCLAIMERS

These data are being released on request, despite concerns about their quality. The Census Bureau’s policy is not to 

withhold data that are available, unless releasing such data would violate confidentiality requirements. The Census 

Bureau recommends using these data only for research or evaluation purposes, and not to make statements about 

characteristics of the population or economy because they do not meet the criteria outlined in the Census Bureau’s

Statistical Quality standard: Releasing Information Product.

The views expressed in this research, including those related to statistical, methodological, technical, or operational 

issues, are solely those of the author and do not necessarily reflect the official positions or policies of the Census 

Bureau. The author accepts responsibility for all errors. This presentation reports the research and analysis 

undertaken by Census Bureau staff. It has undergone more limited review than official publications.

INTRODUCTION

The Annual Social and Economic Supplement to the Current Population Survey (CPS ASEC) generates widely used 

estimates on health insurance coverage and the uninsured.

2,3, 4, 5

 However, research suggeststhat the calendar year 

estimate of the uninsured is higher than it should be and that estimates actually reflect a mixture of current and past 

year coverage.

6,7,4

 To address this concern, the Census Bureau substantially redesigned the CPS ASEC health 

1 Carla Medalia is the correspondingauthor. Her email is Carla.Medalia@census.gov. 

2 Glied, Sherry, Dahlia K. Remler, and Joshua Graff Zivin. 2002. “Inside the Sausage Factory: Improving

Estimates of the Effects of Health Insurance Expansion Proposals.” Milbank Quarterly: 80(4): 603-35.

3 Holahan, John. 2011. “The 2007-09 Recession and Health Insurance Coverage.” Health Affairs: 30(1): 145-52.

4 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 – Web Exclusive: w991-w1001.

5

Ziegenfuss, Jeanette Y., and Michael E. Davern. 2011. “Twenty Years of Coverage: An Enhanced Current 

Population Survey – 1989–2008.” Health Services Research: 46(1): 199-209.

6 DeNavas-Walt, Carmen, Bernadette D. Proctor, and Jessica C. Smith. 2012. Pg. 21 in Income, Poverty, and 

Health Insurance Coverage in the United States: 2011. U.S. Bureau of the Census, Current Population Reports, 

P60-243. Washington, D.C.: U.S. Government Printing Office. 

 
insurance module over the past ten years.

8

 The redesigned instrument was fielded in a large national content test in 

March 2013. In addition to the features of the redesigned instrument, the content test also takes better advantage of 

automated computer-assisted interviewing and adds important new content to the instrument. The 2013 content test 

fielded a complete CPS ASEC interview to previous CPS respondents who were interviewed by Census Bureau 

telephone center staff. 

This report highlights results of the content test with those from the 2013 CPS ASEC. 9

 Specifically, the evaluation 

includes only production CPS data collectedin telephone centers in March 2013, rather than the full ASEC CPS 

dataset. In addition, this report compares calendar-year estimates with point-in-time estimates from the content test. 

The 2013 content test is not compared to other surveys here because the purpose is to evaluate the change in the 

questions from the CPS ASEC. Both the datasets are unedited. Comparing to other surveys would introduce too 

many additional sources of variation then is necessary for the evaluation of the content test itself. From this point, 

the restrictedCPS ASEC will be referred to as the production instrument.

HIGHLIGHTS

• The percentage of people without health insurance was 10.6 percent in the content test and 12.5percent in 

the production instrument.

• The percentage of people with Medicaidwas statistically lowerin the content test than the production 

instrument. 

• The percentage of people with private coverage was statistically higher in the content test than the 

production instrument. 

• The percentage of people uninsuredin the previous calendar year in the content test was significantly lower 

than the percentage of people uninsured at the time of the interview.

• The average time to complete the health insurance questions in the content test was 1:32 minutes longer 

than in the production instrument. However, when excluding questions that added new material on health 

insurance exchanges and employer-sponsored insurance offers and take-up, the content test was 1:20

minutes longer than the production instrument.

BACKGROUND

For a more complete discussion of the motivation for the redesigned health insurance instrument and the 2013 

content test, please see OMB Supporting Statement A10 and the paper on the 2013 content test presented at the Joint 

Statistical Meetings in 2013.11

Inflated estimate of the uninsured

Although the CPS ASEC is a widely used indicator of the uninsured in the United States, many researchers have

questioned its validity.

12

 In particular, researchers have suggested that estimates of the uninsured in the previous 

7 Kenney, Genevieve, and Victoria Lynch. 2010. “Monitoring Children’s Health Insurance Coverage Under 

CHIPRA Using Federal Surveys.” Pgs. 65-82 in Databases for Estimating Health Insurance Coverage for 

Children: A Workshop Summary, edited by Thomas J.Plewes. Washington, D.C: National Academies Press.

8

Examples of this research will be discussed in the background.

9

 "Data are subject to error arising from a variety of sources. For information on confidentiality protection, sampling 

error, non-sampling error, and definitions see: http://www.census.gov/prod/techdoc/cps/cpsmar13.pdf and 

http://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=201211-0607-002."

10 U.S. Census Bureau. 2013. OMB Supporting Statement A. Available at: 

http://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=201211-0607-002.

11 Medalia, Carla. 2013. “Health Insurance in the Current Population Survey: Now and Later?” Unpublished paper 

presented at the Joint Statistical Meetings in Montreal on August 4, 2013. Available from author upon request.

12 The issues with the traditionalCPS ASEC health insurance estimates have been well established, as discussed in 

the Census Bureau’s annual publication on health insurance. The Census Bureau devotes two-thirds of a page in the 

2

 
calendar year is too high, and may actually reflect a mixture of current and past year coverage.

13, 14, 15Research has 

also shown that people have difficulty recalling health insurance coverage in the distant past. For example, short 

spells of Medicaid that occurred early on in the previous calendar year may not be salient enough for people to recall

during the interviewed up to a year or so later.

15

 This measurement error is partially due to both the reference period 

and timing of data collection.

16

 

Redesigned health insurance instrument

The redesigned health insurance instrument differs from the traditional CPS ASEC in three primary ways: questions 

about type of coverage, questions about past coverage, and the household-level design. The completeredesigned 

instrument was previously testedin 2010, in a survey that replicated certain elements of the CPS ASEC

interview.

17, 18While this 2010 survey provided the proof of concept for the redesigned instrument,19 it did not 

include the full battery of CPS Basic and supplemental income questions that would be asked during an actual CPS 

ASEC interview. Therefore, in order to evaluate the redesigned health insurance instrument operationally in the 

CPS environment, the Census Bureau fielded a nation-wide content testin 2013, which follows the method of 

redesigned health insurance instrument closely.

20

One of the main differences between the traditionaland redesigned health insurance instruments is the reference 

period for data collection. The traditional instrument asks about coverage at any time in the past calendar year. The 

redesigned instrument also captures this information, but does so in a different way: itstarts by asking about current 

coverage and then uses follow-up questions to find out (1) when that coverage began and (2) which months the 

individual had the coverage. If the individual does not have current coverage, the instrument asks about coverage 

during the previous calendar year through the present. The change in the reference period should make it easier for 

respondents to report their coverage. It also means that the redesigned instrument can capture information about all 

months between January of the previous year and the interview month. In this regard, the redesign captures similar

information as the redesignedSurvey of Income and Program Participation, another Census Bureau survey, which 

measures monthly coverage of health insurance during the previous calendar year. 

Other differences between the traditional and redesigned instruments include the identification of plan type and 

which household members are covered by each plan. First, the traditionalinstrument asks about each plan type. By 

contrast, the redesigned instrument asks a series of questions, beginning with the general source of coverage and 

Income, Poverty, and Health Insurance Coverage in the United States: 2011 (DeNavas-Walt et. al.:21) to flaws in 

the estimate. The quality of health insurance data has long been a concern of Health and Human Services. 

13 DeNavas-Walt, Carmen, Bernadette D. Proctor, and Jessica C. Smith. 2012. Pg. 21 in Income, Poverty, and 

Health Insurance Coverage in the United States: 2011. U.S. Bureau of the Census, Current Population Reports, 

P60-243. Washington, D.C.: U.S. Government Printing Office.

14 Kenney, Genevieve, and Victoria Lynch. 2010. “Monitoring Children’s Health Insurance Coverage Under 

CHIPRA Using Federal Surveys.” Pgs. 65-82 in Databases for Estimating Health Insurance Coverage for 

Children: A Workshop Summary, edited by Thomas J.Plewes. Washington, D.C: National Academies Press.

15 Klerman, Jacob A., Michael Davern, Kathleen Thiede Call, Victoria Lynch, and Jeanne D. Ringel. 2009. 

“Understandingthe Current Population Survey’s Insurance Estimates and the Medicaid ‘Undercount.’” Health 

Affairs – Web Exclusive: w991-w1001.

16 Klerman, Jacob A., Michael Davern, Kathleen Thiede Call, Victoria Lynch, and Jeanne D. Ringel. 2009. 

“Understandingthe Current Population Survey’s Insurance Estimates and the Medicaid ‘Undercount.’” Health 

Affairs – Web Exclusive: w991-w1001.

17 Pascale, Joanne. 2012. “Findings from a Split-Ballot Experiment on a New Approach to

Measuring Health Insurance in the Current Population Survey.” Unpublished Census Bureau report. Presented at 

American Society of Health Economists Conference, Minneapolis, MN, June 2012.

18Pascale, Joanne, Jonathan Rodean, Jennifer Leeman, Carol Cosenza, Alisu schoua-Glusberg. Forthcoming. 

“Preparing to Measure Health Coverage in Federal Surveys Post-Reform: Lessons from Massachusetts.” 

19 Boudreaux, Michael, Brett Fried, Joanna Turner, and Kathleen Thiede Call. 2013. “SHADAC Analysis of the 

Survey of Health Insurance and Program Participation.” State Health Access and Data Assistance Center. 

Retrieved September 26, 2013. (http://www.shadac.org/files/shadac/publications/SHIPP_final_report.pdf).

20 U.S. Census Bureau. 2013. OMB Supporting Statement A. Available at: 

http://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=201211-0607-002. 

3

 
then asking more specific questions to identify the plan type. Second, the traditional instrument asks if anyone in 

the household was covered by a particular plan type, and if yes, who was covered. On the other hand, the 

redesigned instrument asks about an individual’s own coverage, and then asks if the same plan type covered any 

other household members. Additional questions ask each household member about any additional plans that they 

may have.

New content in the CPS ASEC

In addition to redesigning the CPS ASEC health insurance section, the Census Bureauadded new questions to 

address two areas. First, new questions allow for the measurement of health insurance exchanges, and second, new 

questions allow the Census Bureau to determine rates of employer-sponsored insurance offers and take-up.

Exchanges. One of the key features of the Patient Protection and Affordable Care Act (ACA) is the implementation 

of state-specific “Health Insurance Exchanges” in 2014. An exchange is a state-level marketplace of private health 

insurance options for individuals and small businesses. While the redesigned health insurance instrument measures 

the types of coverage included in the traditional instrument, it also is able to measure health insurance exchange 

coverage and premium subsidization through new questions.This new content was cognitively tested in 2012 in 

Massachusetts.

21

 

Employer-sponsored insurance offers and take-up. The ACA may lead to changes in the rates of employersponsored health insurance offers and take-up, or whether or not someone who is offered insurance through their 

employer enrolls in that plan.

22, 23 As a result, the Council for Economic Advisors asked the Census Bureau to add 

questions to the ASEC to measure these changes. The redesigned instrument includes a short series of questions 

asked of people who are currently employed but who do not have health insurance through their own employer. 

These questions were originally asked in the CPS Contingent Worker Supplement, fielded in February of 1995, 

1997, 1999, 2001, and 2005. This particular set of questions only works with a current coverage question. 

DATA AND METHODS

Data

The sample for the 2013 content test was selected from retired sample for the CPS. None of these households had 

been given the CPS ASEC before, but they had received the CPS Basic and other CPS supplements, such as the 

Displaced Workers supplement, Child Support, or Food Security. The retired sample was between one and two 

years old, meaning that their last CPS interview was one to two years prior. The sample was selected to exclude 

households that had been selected for another survey, the American Time Use Survey, as well as other 

characteristics.24

 To be interviewed, households needed to be reachable by the same phone number that they had 

when they were last interviewed one to two years before. Furthermore, households needed to live at the same 

addresses as their last interview. The final sample size for the content test was 22,508 households with 1,168 

households ineligible for the CPS ASEC interview, which reduced the sample to 21,340 households. The data 

presented have been weighted by the Census Bureau to reflect the total civilian non-institutionalized population. 

Trained CPS ASEC interviewers at three Census Bureau telephone centers, in Hagerstown Maryland, Jeffersonville 

Indiana, and Tucson Arizona, conducted 9,195 household interviews (including complete and partial interviews) for 

21 Pascale, Joanne, Jonathan Rodean, Jennifer Leeman, Carol Cosenza, Alisu schoua-Glusberg. Forthcoming. 

“Preparing to Measure Health Coverage in Federal Surveys Post-Reform: Lessons from Massachusetts.” 

22 Maxwell, Nan L. 2013. “The ACA, Health Care Costs, and Disparities in Employer-Sponsored Health 

Insurance.” Mathematica Policy Research Reports, Mathematica Policy Research. Retrieved August 1, 2013 

(http://EconPapers.repec.org/RePEc:mpr:mprres:7683).

23 Thurm, Scott. 2013. “Will Companies Stop Offering Health Insurance Because of the Affordable Care Act?” 

The Wall Street Journal, June 16. Retrieved August 1, 2013 

(http://online.wsj.com/article/SB10001424127887323582904578488781195872870.html).

24 For a complete description of the sampling method used for the 2013 content test, please see the following paper: 

Brault, Matthew. "Non-Response Bias in the 2013 CPS ASEC Content Test." Paper presented at the Federal 

Committee on Statistical Methodology 2013 Annual Meeting. Available from author upon request.

4

 
the CPS Basic part of the interview. The analytical sample for the content test, which included only those 

individuals that were still in the survey by the health status question, was 16,401individuals.

The data from the content test have been partially recoded to replicate the data produced by the traditional ASEC. 

Census Bureau staff edited the demographic characteristics, such as those collected during the CPS Basic part of the 

interview, using the same programs used in the traditional CPS. Furthermore, the Census Bureau recoded data from 

the content test so that they contain the same information as the traditional ASEC variables. 

The data that serve as the comparison group is the 2013 CPS ASEC, which was conducted in February, March and 

April which was conducted with a combination of in-person and phone center interviews. The original sample size 

for the full ASEC sample was 98,095 households. After removing ineligible addresses, the sample was reduced to 

83,225 households, which includes both interviews and Type A noninterviews. These households contained 

202,634 individuals. The analysis focuses on interviews conducted in March 2013 in ASEC call centers, which 

included 6,410households. These households contain the final analytical sample, which was 13,228 individuals. 

This sample consisted of unedited responses to the types of health insurance coverage using household and 

individualinformation. We chose not to use the imputation flagsthat reside on the person public use microdata file

(zero indicates that the insurance typewas not imputed or allocated). There were sevenmore unweighted people 

insured if we used theseflags. We are assuming, but not verifying,that those sevenpeople had an incorrect 

imputation flag.

The types of health insurance coverage are private insurance plans and government coverage. Private insurance 

includes direct purchase and employer-sponsored insurance. Government insurance includes Medicare, Medicaid, 

other government health care, and military coverage. In all of the CPS reports, the Census Bureauconsiders 

"Medicaid" as Medicaid, CHIPand other government health care.

25

 For the purposes of this paper, Medicaid 

includes Medicaid andCHIP programs. The logic of this decision was both programs are managed by the same 

agency (Centers for Medicare & Medicaid Services), many states have the CHIP program as an extension of the 

Medicaid program, and both programs serve low-income children. We do not show military coverage or other 

government health care here due to the small sample sizes. Indian Health Services does not count as health 

insurance coverage because it is clinic-based or hospital-based health care.

Nonresponse and Section Dropout

Due to survey dropout, not all of the households interviewed for the CPS Basic were included in the sample for the 

health insurance section. The overall response rate for the CPS Basic production instrument was 90.7 percent in 

2013, which is substantially higher than for the redesigned instrument, which was 43.1 percent. As shown in Table 

1, this corresponds to an initial nonresponse rate of 9.3percent in the traditionalinstrument and a 56.9 percent 

nonresponse rate in the content test. 

In addition to the CPS Basic nonresponse rate,respondents sometimes drop out of the survey once it has begun. The 

dropout rate among those households that were considered completeor partial CPS Basic interviews but dropped out 

before the end of the health insurance section was 15.9 percent in the contenttest, compared to 14.5 percent in the 

traditional instrument. Combining the section dropout with the CPS Basic nonresponse, 63.8 percent of eligible 

households were dropped from the analytical sample in the content test, compared with 22.5 percent in the

traditional instrument. This means that the analytical sample for the content test included 36.2 percent of the 

eligible households, compared with 77.5 percent for the traditional instrument.

The content test, which was only in call centers, was weighted to reflect the national population in March of 2013. 

However, that population is larger than the analytical sample because of the dropout rate. Again, the analytical 

sample is the people that answeredthe health insurance questions. The CPS ASEC is also weighted to the national 

population in March of 2013. The dropout rate affectsthe weighted CPS ASEC. In addition, the call centers 

represent a subset of the national population estimate and were only from March. 

25 These individual types of health insurance are on the PUMS file so an analyst can make their own decisions.

5

 

(hereafter referred to as the ASEC call centers) to the unedited weighted redesign results(hereafter referred to as the 

content test).

27

 

The percentage of people without health insurance was 10.6 percent in the content test and 12.5 percent in the ASEC 

call centers. In other words, the content test had a 1.8percentage point lower uninsured rate than the ASEC call 

centers. This pattern, where the percentage of those uninsured was lower in the content test than in the production 

call centers, was consistent by age group. Those aged 18 to 64, aged 19 to 25, and aged 35 to 44 had lower levels of 

uninsured in the content test than in the production call centers. The difference for those in all other age groups 

were in the same direction but not statistically different between the two surveys. For this last group, aged 65 and 

above, we would not have expected a difference between the content test and production ASEC because the 

population is almost entirely covered by Medicare. 

The percentage of people who were uninsured in the content test was generally lower than in the ASEC call centers 

by race and Hispanic origin. The differences for White alone, non-Hispanic White, and Black alone were all lower 

in the content test than in the ASEC call centers, while the difference for Hispanic and Asians were in the same 

direction but not statistically significant. 

In addition to the percentage of people without coverage for the previous calendar year, rates by type of coverage 

are also shown. For all ages, the percentage of people with private coveragewas higher in the content test than in 

the production ASEC, while the percentage of people with government coverage was lower in the content test than 

in the production ASEC. This pattern is also present for those under age 18and aged 18 to 64, although private 

coverage for these age groups is not statistically significant.

Comparing the content test calendar year to current coverage estimate

As previously described, the CPS ASEC is often criticized for producing calendar year estimates that may actually

reflect a combination of past year and current coverage. To address this, the redesign explicitly asks about both 

current coverage as well as calendar year coverage. Therefore, in addition to comparing the 2012 calendar year 

content test estimate to theproduction ASEC, it can also be compared to the current coverage estimate from the 

content test. Note that the calendar year estimates are subtracted from current coverage estimates. 

In the sample, the percentage of people who were uninsured in 2012 was 10.6 percent, compared to 12.0 percent at 

the time of the interview. Therefore, more people report being uninsured currently than are uninsured for the entire 

previous calendar year, which is consistent with the expectation that people are generally more likely to be currently 

uninsured than they were for the entire previous calendar year. 

In addition to examining the difference between calendar year and current coveragefor the uninsured rate, we 

examined the difference by coverage type. While the differences by type were in the expected direction, none of 

estimates wasstatistically significant. Unlike the uninsured status, a negative relationship is expected for private 

coverage, since someone is more likely to have had private insurance at any time in the previous calendar year than 

to currently have private insurance. This was found to be the true in the content test: the percentage of people with 

private health insurance coverage was 72.3 percent in 2012 and 70.7 percent at the time of the interview, a nonsignificant difference. In 2012, the percentage of people covered by government insurance was 28.2 percent, which 

was not statistically different from the 27.9 percent for the current coverageestimate. The percentage of people with 

Medicare was 15.7percent in the calendar year and 16.1 percent at the time of the interview, a non-significant 

difference. Finally, the percentage of people on Medicaid in 2012 was 11.2 percent, which was not statistically 

different from the 10.5 percent at the time of the interview. Given the churning on and off Medicaid,

28 it would 

make sense if the spread between these two estimates were greater than 0.6 percentage points. 

27 The table also includes additional production ASEC estimates for the original weighted ASEC (final estimate) and 

the ASEC March call center unedited but not adjusted weighted estimate.

28 Czajka, John L. 2012. “Medicaid Enrollment Gaps, 2005 to 2007: Final Report.” Washington, D.C.: 

Mathematica Policy Research.

7

 
Comparing the content test to production instrument: mean length of interview

The mean time for a total health insurance interview increased for the content test from the production instrument. 29

 

The total mean household time for a health insurance interview was 2:39 for the production instrument, compared to 

4:12 for the content test, for an average increase of 1:32. This figure includes the complete health insurance 

instrument, including the self-rated health questions for both instruments as well as the new content added to the 

content test health insurance instrument (employer-sponsored insurance take-up and offers and exchange-related 

health insurance questions). Excluding the new content in the content test, the average household time for an 

interview in the production instrument remains steady at 2:39 but is 3:59 for the content test, for an average increase 

of 1:20. In other words, the new content added 0:13 on average to the length of the interview. 

DISCUSSION

One of the main hypotheses for this comparison is that the redesigned calendar year estimate of the uninsured will 

be lower than it is for the production instrument. This hypothesis is based on research which shows that the 

production CPS uninsured estimate is too high, and that it reflects a mixture of current and past year coverage.

30,31, 32

 

Because the redesigned instrument explicitly addresses this concern by asking about both current and past coverage, 

the instrument allows for estimates of current coverageand calendar year coverage that have discrete reference 

periods.

Making comparable measuresto the production CPS proves difficult when the sample’s respondents are not 

reflective of the larger population. The content test’s low response rate raised concerns about what role nonresponse

bias would have on key estimates. A separate analysis of nonresponse showed that non-response exerted downward 

bias on estimates of uninsurance and upward bias on Medicare coverage.

33

 However, the weights used in this 

analysis may account for and correct this kind of bias. More research is being conducted to examine these possible 

sources of nonresponse bias and the effect that it could have on the results presented in this paper.

29 For a thorough analysis of the time it took to complete the content test and CPS ASEC interviews, please see:

Bee, Adam and Aaron Cantu. 2013. "Evaluating Respondent Burden of the CPS ASEC Content Test with Timer 

Data.” Paper to be presented at the 2013 FCSM meeting in Washington, D.C.

30 DeNavas-Walt, Carmen, Bernadette D. Proctor, and Jessica C. Smith. 2012. Pg. 21 in Income, Poverty, and 

Health Insurance Coverage in the United States: 2011. U.S. Bureau of the Census, Current Population Reports, 

P60-243. Washington, D.C.: U.S. Government Printing Office.

31 Kenney, Genevieve, John Holahan, and Len Nichols. 2006. “Toward a More Reliable Federal Survey for 

Tracking Health Insurance Coverage and Access.” Health Services Research: 41(3): 918-45.

32 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 – Web Exclusive: w991-w1001.

33 Brault, Matthew. "Non-Response Bias in the 2013 CPS ASEC Content Test." Paper presented at the Federal 

Committee on Statistical Methodology 2013 Annual Meeting. Available from author upon request.

8

 
TABLES

Table 1. Nonresponse and dropout in the 2013 CPS ASEC and 2013 Content Test

 Production CPS ASEC

March Call

Content Test Centers Total Sample

CPS Basic nonresponse 56.9% 0.0% 9.3% 

Section dropout (through end health 

insurance) 15.9% 11.4% 14.5% 

Total nonresponse and dropout 63.8% 11.4% 22.5% 

Analytical sample (as percent of 

eligible households) 36.2% 88.6% 77.5%

 

Source: CPS ASEC health insuranceproduction instrument and content test (2013). 

Notes: “CPS Basic nonresponse” refers to nonresponse in the CPS Basic interview. “Section dropout” refers to the 

all dropout from before the supplement began through the end of the health insurance section. “Total nonresponse 

and dropout” refers to all nonresponse and dropout from the beginning of the CPS Basic interview through the end 

of the health insurance section.

9
Table 2. Demographic characteristics of the 2013 CPS ASEC and 2013 Content Test

P Content Test

Final estimates Call centers, March

Call centers, March, 

adjusted Call centers, March

N (in 

1000s) %

SE 

(%)

N (in 

1000s) %

SE 

(%)

N (in 

1000s) %

SE 

(%)

N (in 

1000s) %

SE 

(%)

Age

Under 65 268,008 86.1 0.0 

 

 16,400 78.6 0.6 

 

 

 

 

 

 

 

 

 

 

 

207,615 85.3 0.4 207,615 85.3 0.4

 0 to 17 74,425 23.9 0.0 3,459 16.6 0.4 57,760 23.7 0.5 57,760 23.7 0.4

 18 to 34 71,777 23.1 0.0 4,253

 

20.4 0.5 51,480 21.1 0.5 51,480 21.1 1.2

 35 to 64 121,806 39.2 0.0 8,687 41.6 0.5 98,376 40.4 0.6 98,376 40.4 0.7

65 and over 43,108 13.9 0.0 4,472 21.4 0.6 35,860 14.7 0.4 35,860 14.7 0.4

Race and ethnicity

White non-Hispanic 195,330 62.8 0.0 16,856 80.8 0.6 159,950

 

 

 

 

65.7 1.0 159,950 65.7 0.6

Black non-Hispanic 37,619 12.1 0.0 1,307 6.3 0.4 26,566 10.9 0.7 26,566 10.9 0.5

Other non-Hispanic 24,937 8.0 0.0 994 4.8 0.4 19,608 8.1 0.6 19,608 8.1 0.3

Hispanic 53,230 17.1 0.0 1,714 8.2 0.5 37,351 15.3 0.8 37,351 15.3 0.5

Work Status for 

persons aged 18-64

Full time, full year 

 

 

 

 

98,762 51.0 0.2 98,762 51.0 0.2 75,509 50.4 0.8 75,509 50.4 0.8

Less than full time, full 47,070 24.3 0.2 47,070 24.3 0.2 39,022 26.0 0.6 39,022 26.0 0.9

Not working 47,753 24.7 0.2 47,753 24.7 0.2 35,325 23.6 0.7 35,325 23.6 0.6

Sex

Male 152,335 49.0 0.0 10,258 49.2 0.4 118,284

 

48.6 0.4 118,284 48.6 0.6

Female 158,781 51.0 0.0 10,613 50.9 0.4 125,191 51.4 0.4 125,191 51.4 0.6

N (in thousands) 311,116 20,871 243,475 243,475

n (sample size) 172,662 13,228 13,228 16,401

10

Source: CPS ASEC health insuranceproduction instrumentand content test (2013). 
Table 3. Health insurance coverage in the 2013 CPS ASEC and 2013 Content Test

Production CPS ASEC Content Test Difference

Producti Production Call Production 

on (final Centers, March Call Centers, and Contest Content 

estimate) (unedited) March (unedited) Test Test O nly

Calender 

Prod. (adj)- year -

Original Original Adjusted Calendar Current Content Current 

Universe Estimate weight weight weight year Coverage Test Coverage

Total by Coverage Type

Total Uninsured 15.4 10.5 12.5 10.6 12.0 1.8 * -1.4 *

Total Private 63.9 72.9 69.7 72.0 70.4 -2.3 * 1.6 *

Total Gov. 32.6 33.8 30.9 28.6 28.3 2.3 * 0.3 *

Total ... Medicare 15.7 22.5 16.2 15.7 16.2 0.5 -0.4 *

Total ... Medicaid 16.4 9.2 12.5 11.4 10.8 1.0 0.6 *

Under 18 by Coverage Type

Aged 0 to 17 Uninsured 8.9 6.0 6.7 6.0 7.0 0.7 -1.0 *

Aged 0 to 17 Private 60.1 66.7 62.7 65.9 64.1 -3.2 1.8 *

Aged 0 to 17 Gov. 39.2 33.9 37.1 32.2 30.6 4.9 * 1.5 *

Aged 0 to 17 ... Medicare 1.0 0.9 1.1 0.8 0.8 0.3 -0.1 

Aged 0 to 17 ... Medicaid 35.9 29.4 32.9 29.1 27.5 3.7 1.6 *

18 to 64 by Coverage Type

Aged 18 to 64 Uninsured 21.0 14.8 17.2 14.6 16.6 2.7 * -2.0 *

Aged 18 to 64 Private 67.2 76.5 73.4 75.3 73.7 -1.9 1.7 *

Aged 18 to 64 Gov. 16.6 13.6 14.1 12.2 12.0 1.8 * 0.2 

Aged 18 to 64 ... Medicare 4.2 4.5 4.2 3.8 4.1 0.4 -0.3 *

Aged 18 to 64 ... Medicaid 10.6 5.4 6.3 6.3 5.9 0.0 0.4 *

Race and Hispanic Origin by Coverage Status

White Alone Uninsured 14.7 10.0 11.9 9.9 10.9 2.0 * -0.9 *

... Non-Hispanic White Uninsured 11.1 8.2 8.3 6.5 7.3 1.8 * -0.9 *

Black Alone Uninsured 19.0 15.7 15.4 12.4 17.4 3.0 * -5.0 *

Asian Alone Uninsured 15.1 11.9 12.6 10.3 11.3 2.3 -1.0 

Hispanic Uninsured 29.1 29.0 29.0 26.1 27.5 2.9 -1.4 

Age by Coverage Status

0 to 18 Uninsured 9.2 6.3 7.5 6.1 7.3 1.4 -1.2 *

19 to 25 Uninsured 25.5 21.3 24.0 18.3 22.8 5.7 * -4.5 *

26 to 34 Uninsured 27.1 20.4 23.5 20.1 21.0 3.4 -0.9 

35 to 44 Uninsured 21.2 17.2 20.5 14.1 16.0 6.3 * -1.9 *

45 to 64 Uninsured 16.1 10.6 11.8 11.4 13.1 0.4 -1.7 *

65 and above Uninsured 1.5 1.6 1.9 1.5 1.0 0.4 0.5 *

N (in thousands) 311,116 20,871 243,475 243,475 243,475 -- --

n (sample size) 172,662 13,228 13,228 16,401 16,401 -- --

Source: CPS ASEC health insuranceproduction instrumentand content test (2013). 

Notes: * indicates that the difference is statistically significant at the 90% confidence levelor higher. 

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