Estimating the Number of Individuals in the U.S. Without Health Insurance. Implications of the Adjusted CPS Estimates

04/08/2005

The estimates from the March 2004 CPS can tell two stories: one of level and one of trend. Starting with the unadjusted CPS data, the level of uninsured was 45.0 million with a relatively flat trend since 1994, with the exception of a change due to the introduction of the verification questions. With the adjustment for verification, the trend becomes almost entirely flat. Broadening to other categories such as employer sponsored insurance, publicly sponsored insurance, the uninsured, the trends among these subgroups show very little change over the decade. The one noticeable exception is a reduction in the rate of uninsurance in children over the last few years, almost certainly attributable to the passage and implementation of the SCHIP program.

With respect to the measurement of the level of uninsured in the country, however, the adjustments dramatically alter the findings. Overall, the estimate of the proportion of the population without health insurance in CY 2003 drops from 15.6 to 12.5 percent when the CPS sample is fully adjusted as described above. The most significant contributor to this change in level is the adjustment for the Medicaid undercount, which corrects for a discrepancy of just over 17 million individuals between the unadjusted CPS estimates and Medicaid program enrollment data. Just over 9 million (just over 50%) of these “new” Medicaid eligible individuals come from the ranks of the uninsured as previously estimated.

Over the decade, the adjustments maintain the very small net increase in the uninsured from CY 1994 to CY 2003 (less than one half of one percent). For both the unadjusted and adjusted data, there is some slight movement upwards and downwards over the time period, but on the whole the trend is fairly flat. When the full period from 1989 through 2003 is examined, the trend shown in the adjusted data and the unadjusted data are quite similar. However, the level of uninsurance suggested by the adjusted data is substantially lower.

The graphs below show the effects of our adjustments on the time period 1989 through 2003. Graph 1 looks at ESI as a percent of the total population. For this population we do not show the Medicaid adjusted percents, as they do not affect the population with employer sponsored insurance. The unadjusted values, set 1, show the major discontinuity from 1993 to 1994, reflecting the substantial improvement in insurance measurement in general, but ESI in particular. The unadjusted ESI percentage for 1994 is about 4 percentage points higher than for 1993, which appears to be entirely attributable to improved survey methods. Adjusting for updated weights (set 2) makes small changes, but the additional adjustments (set 3) which embed the estimated impact of the post-1994 survey make the ESI curve fairly smooth.

Graph 1: ESI as Percent of Population

The ESI change is important in its own right, to the extent policy initiatives are predicated on observed trends in ESI coverage. In Graph 1, we can see an initial slight decline in net ESI coverage rates from CY 1989 to CY 1994 (looking at our adjusted series), but the level has been mostly stable since 1994 except for a slight increase to CY 2000 and then a decline in the last three years. The changes in the survey which contributed to this adjustment are important even if only the uninsured are being analyzed, since they had substantial impacts on coverage in general, and alter the baseline for comparison purposes. Moreover, there is some evidence that ESI may be undercounted on the CPS relative to other national surveys, therefore establishing a consistent baseline will prove important for any follow-up research on an ESI undercount.

Graph 2 looks at Medicaid as a percent of population. As noted earlier, the improvements introduced in the March 1995 CPS questionnaire reduce the number of respondents with Medicaid coverage when compared to earlier survey years. While the adjustment for new weights (set 2) minimally change the unadjusted data (set 1), it is the adjustment for this survey change (set 3), reducing Medicaid coverage prior to CY 1994, that is most noticeable. This occurs when other types of (government) coverage are picked up by the survey – types that had been previously allocated to Medicaid. There is no change to the uninsured due to this change in the survey, only a change in the allocation of coverage.

Adjusting for the Medicaid undercount (set 4) raises the number of persons covered under Medicaid and shows the growing gap from the (rising) CPS estimates and (more quickly rising) program estimates.

Graph 2: Medicaid as Percent of Total Population

The final graph, Graph 3, shows that uninsured trend remains mostly flat over the time period, peaking in CY 1998 with a slight decrease afterward but increasing since CY 2000. The pre- 1994 levels reflect backcasting the effects of the improved insurance questions. The unadjusted series (set 1) shows a gradual increase, up to 1999 when a major drop appears. Adjusting for new weights only (set 2) makes minimal changes to the pre-1999 story. Adjusting for the major questionnaire improvements in 1999 and later makes the discontinuity much smaller (set 3), but still has the same general trends. The biggest impact is seen in moving to the fully adjusted (set 4) line, where the Medicaid undercount adjustment is reflected.

Graph 3: Uninsured as Percent of Population

While the technical adjustments to the CPS estimates of the uninsured do not fundamentally change the picture of a relatively stable trend (i.e., they do not make the problem of the uninsured disappear or significantly alter the demographic make-up of the uninsured population) the deeper understanding they give us of the underlying insurance dynamics of the insured and uninsured populations is useful for policy makers.

For example, the adjustments suggest that the number of full year uninsured children is significantly lower than typically reported: just about 6% (4.4 million) of persons under 18 were uninsured for all of 2003, vs. 12% (9.0 million) before the adjustments.

The adjustments also raise the percentage of the uninsured who are above 300% of poverty, suggesting fewer persons eligible but not enrolled in government programs such as Medicaid. This could have implications for the types of policy remedies that one would propose.

Table 1a, below, shows adjusted values corresponding to those previously shown in Table 1.

Table 1a. The Uninsured in 2003 According to the Fully Adjusted CPS

Characteristic Total US Population (Millions) Percentage of the Total US Population Number of Uninsured (Millions) Percentage of the Group Uninsured Percentage of the Total Uninsured
Total Population
  288.3 100% 35.9 12% 100%
Poverty          
Below 100% 36.4 13% 7.0 19% 19%
100- 200% 53.5 19% 10.0 19% 28%
200- 300% 49.5 17% 7.4 15% 21%
300- 400% 40.0 14% 4.4 11% 12%
400- 500% 31.5 11% 2.3 7% 7%
500% and Over 77.4 27% 4.7 6% 13%
 
Age
Below 18 73.6 26% 26% 5% 11%
18- 24 27.8 10% 6.9 25% 19%
25- 34 39.2 14% 9.1 23% 25%
35- 44 43.6 15% 6.9 16% 19%
45- 54 41.1 14% 5.3 13% 15%
55- 64 28.4 10% 3.4 12% 10%
65 and Over 34.7 12% 0.2 1% 0%
 
Parental Status
Parents 65.5 23% 8.7 13% 26%
Childless Adults 114.7 40% 23.1 20% 68%
Children 73.4 25% 3.9 5% 12%
 
Race/ Ethnicity
White 194.9 68% 17.9 9% 50%
African-American 35.7 12% 4.6 13% 13%
Hispanic 40.4 14% 10.7 26% 30%
Other/ Mixed 17.3 6% 2.7 16% 7%
 
Immigration Status
Citizen 267.2 93% 27.3 10% 76%
Non-Citizen 21.1 7% 8.6 41% 24%
 
Work-Status
Full Time 156.5 54% 17.2 11% 48%
Part Time or Part Year 55.3 19% 10.5 19% 29%
Not Working 76.5 27% 8.3 11% 23%
 
Firm Size
Under 10 32.1 11% 8.6 27% 24%
10 to 24 15.3 5% 3.6 23% 10%
25- 99 19.5 7% 3.3 17% 9%
100- 499 19.8 7% 2.4 12% 7%
500- 999 8.0 3% 0.9 11% 3%
1,000 and Over 57.3 20% 5.5 10% 15%
Children or Not Working 136.3 47% 11.6 8% 32%

Source: ARC Adjusted 2004 CPS

It should be noted that the count of full year uninsured under the adjusted CPS, approximately 36 million, is more in line with the number of individuals who lack health insurance for a full year under the MEPS and the NHIS surveys. This is shown in Graph 4, below.

Graph 4: Comparison of the Uninsured

These surveys use more detailed questionnaires than the CPS and obtain more detailed data on health status and usage of health care. As mentioned above, the higher CPS numbers has traditionally led analysts to believe the CPS represented more of a point in time estimate of those without insurance than a count of individuals without insurance for a full year. However, the adjusted time series calls this view into question as the adjusted estimates approach other survey’s estimates.

To study this question further would require making similar adjustments to the NHIS and the MEPS, so the difference in estimates could be determined on a fully comparable basis. Given that the NHIS and the MEPS are more detailed health surveys, with different sampling frames and methodologies from the CPS, we believe that any adjustment for a possible Medicaid undercount in these surveys would be smaller than the adjustment we have made to the CPS. Published estimates of persons with Medicaid coverage from these surveys support this view. We plan to pursue this research issue as time and other priorities allow.

Other Research Directions: We anticipate additional research in the area of the Medicaid undercount and look forward to incorporating the latest, most accurate findings into our model. Moreover, future work may be warranted in regards to undercounts of other insurance types on the CPS, particularly ESI given that two-thirds of Americans receives health coverage from their employer. But beyond the question of undercounts of insurance, as we learn more about the important policy differences between the short term and the long term uninsured, we are interested in more detailed analysis of episodes and their economic and health impacts as well as their implications for using health services.

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