TRIM3 Simulations of Full-Year Uninsured Children and their Eligibility for Medicaid and SCHIP[1]

Technical Report

Kenneth Finegold and Linda Giannarelli

June, 2007

Prepared for:
Office for Health Policy
Office of the Assistant Secretary for Planning and Evaluation
U.S. Department of Health and Human Services

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Auxiliary Tables


Introduction and Findings

We estimated the number of full-year uninsured children and the share of them eligible for Medicaid or SCHIP using the TRIM3 microsimulation model. This model applies detailed state-specific rules to determine which individuals represented in the Current Population Survey (CPS) are eligible for Medicaid and/or SCHIP. Other key aspects of the model are the correction for underreporting of Medicaid, SCHIP, and other public benefits in the CPS and the imputation of immigrant legal status. Corrections for underreporting involve simulating additional enrollees so that reported coverage on the CPS matches totals given in the program administrative data. Imputation for immigrant legal status is required because this information is not provided in the CPS but is required to estimate eligibility.

Our findings are that in 2003-2004,

The TRIM3 estimate of 4.9 million full-year uninsured children is much lower than the 8.8 million for whom no coverage is reported in the CPS. The main reason for this difference is that TRIM3 corrects for the underreporting of public coverage in the survey. After the adjustment process, the annual Medicaid and SCHIP caseloads in the model’s data are close to the figures reported in annual administrative data.

The correction for underreporting also lowers the share of uninsured children estimated to be eligible for public coverage, since many children who appear eligible but uninsured are simulated to actually be enrolled. TRIM3’s imputation of immigrant legal status further reduces the share of uninsured children estimated to be eligible for public coverage; many children who seem to meet all other requirements are nonetheless simulated to be ineligible for public coverage due to restrictions on benefits for noncitizens.

Like any other estimates based on survey data, TRIM3 estimates are subject to sampling error, and are less reliable for subgroups whose sample sizes are small. We have more confidence, therefore, in our estimates of uninsurance rates and eligibility for public coverage at the national level, than in our estimates for specific subgroups.

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Overview of the TRIM3 Model

The Transfer Income Model, version 3 (TRIM3) is a comprehensive microsimulation model developed and maintained at the Urban Institute under primary funding from Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation (HHS/ASPE). TRIM3 simulates the major governmental tax, transfer, and health programs that affect the U.S. population, and can produce results at the individual, family, state, and national levels.

TRIM3 uses as its starting-point data the Annual Social and Economic Supplement (ASEC) to the Current Population Survey (formerly referred to as the March CPS). This analysis used data from two different ASEC files, those for calendar years 2003 and 2004, in order to increase the reliability of the state-level estimates. TRIM3’s annual “baseline” simulations (simulations of actual program rules) correct for the underreporting of benefits in the ASEC, and create other variables — such as program eligibility indicators — unavailable in the input data.

Because TRIM3 is a comprehensive model, the simulation of one government program informs the simulation of another government program. In the case of the Medicaid simulation, for instance, the identification of individuals eligible for Medicaid due to receipt of Supplemental Security Income (SSI) benefits is improved by using SSI variables that have been corrected for underreporting by TRIM3’s SSI simulation.

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TRIM3 Simulation of Medicaid and SCHIP

The TRIM3 Medicaid module simulates eligibility and enrollment in Medicaid and SCHIP in each month of the calendar year. Inputs to the module come from TRIM3 simulations of SSI, TANF, and child care expenses, as well as from the original data reported on the CPS.

Eligibility is assessed by applying national and state policies to each individual in each month. The policies database, updated annually, indicates who qualifies for the many different categories of Medicaid and SCHIP eligibility in each state. Criteria include such factors as income levels, age, assets, disability, SSI receipt, and pregnancy.

An enrollment decision is simulated for those simulated to be eligible for Medicaid or SCHIP. Recipients of TANF or SSI are assumed to enroll in Medicaid or SCHIP, if they are eligible. People who report Medicaid or SCHIP coverage on the CPS are also counted as enrolling, if they are simulated to be eligible. This does not include people whose “report” of coverage has actually been imputed by the Census Bureau.

Because Medicaid receipt, like other means-tested benefits, is underreported, the sum of eligible TANF/SSI participants and Medicaid/SCHIP reporters is less than the total number of participants indicated in administrative data. The TRIM3 Medicaid/SCHIP participation algorithm corrects for underreporting by imputing enrollment to eligible nonreporters until doing so would exceed ceilings for specified average monthly targets. Months of simulated participation are then adjusted to hit annual targets as well. Average monthly targets for the 2003 and 2004 alignments included

State-specific alignment was not performed for the 39 states other than those listed above or for the District of Columbia.

Annual targets in the 2003 and 2004 alignments included national totals for Medicaid children, SCHIP children, Medicaid adults, SCHIP adults, disabled, and elderly. The annual targets suggest that about 30 million children were covered by Medicaid and/or SCHIP in each year. Only about 20 million children, in contrast, are reported or imputed enrollees in the raw CPS data.

The TRIM3 alignment procedures described above increase the estimated number of children with public coverage to target levels. Doing so results in an estimate of the number of uninsured children (4.874 million) that is much lower than an estimate taken directly from the CPS (8.787 million). The CPS variables for Medicaid and SCHIP, taken together with variables for other sources of coverage such as employer-sponsored insurance and private nongroup coverage, produce estimates for four groups of children: those with public coverage only; those with other coverage only; those with both kinds of coverage (perhaps in different months of the year); and those with neither public nor other coverage, the uninsured.

TRIM3’s simulation of eligibility and enrollment effectively divides each of these four groups into three parts: children simulated as eligible for, and enrolled in, Medicaid or SCHIP; children simulated as eligible for public coverage in at least one month, but never enrolled; and children simulated as ineligible. TRIM3 changes 4.966 million eligible nonreporters with no other coverage into simulated Medicaid or SCHIP participants, removing these children from the total number of uninsured. A smaller number of children with no other coverage, who are enrolled in Medicaid or SCHIP according to the CPS, are simulated as uninsured, either because TRIM3 does not find them to be eligible for public coverage (923,000), or because TRIM3’s alignment procedures lead to a different result than Census imputation methods (131,000).

Children for whom other coverage is reported are also switched in both directions, but with no impact on uninsurance estimates since both CPS and TRIM3 find them to be insured for all or part of the year. Counting children who do report other coverage and children who do not, TRIM3 changes 12.389 million nonreporters to enrollees and 2.384 million reported enrollees to nonparticipants, for a net increase of 10.005 million Medicaid/SCHIP enrollees over the total reported in the CPS.

TRIM3 estimates of the number of uninsured children and the proportion of these children who are currently eligible for public coverage under Medicaid or SCHIP may be lower or higher than estimates developed with other procedures or assumptions. The possible sources of these differences include the following:

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Imputation of Immigrant Legal Status

The ASEC data includes a variable that indicates if a person is a citizen, but does not provide any information on a noncitizen’s legal status — refugee/asylee, legal nonimmigrant, legal permanent resident (LPR), or undocumented alien. Since legal status helps to determine eligibility for public benefits — including Medicaid and SCHIP — that information is imputed onto the TRIM3 version of each year’s ASEC data.

An alien is assigned to be a refugee/asylee if s/he is from a country for which refugees account for more than 50 percent of total admissions of legal permanent aliens, refugees, and asylees for the period during which the person entered. We compare the results of this process to a demographic estimate of the number of refugees residing in the United States and make minor adjustments as needed to come acceptably close to the administrative data.

Legal nonimmigrants are noncitizens who are admitted legally in the United States for a specified period and for a specified purpose (students, high-tech guest workers, au pairs, and so on). In official terms, they have not “immigrated”; however, many groups do qualify as “residents” and are in the population estimates used to develop CPS weights. Legal nonimmigrants are identified using their employment status, occupation, place or type of employment, school enrollment, income, age, information about spouse, and information about other household members. Targets are not used in producing these estimates.

Noncitizens who are not identified as refugees/asylees or as temporary aliens may be either LPRs or undocumented aliens. The assignment of LPR or undocumented status is made in a manner that comes acceptably close to demographic targets for the sizes of the two groups that should be found in the CPS data — the overall number, the numbers of children vs. adults, and the numbers in the states with the largest immigrant populations. Individuals with certain CPS-reported characteristics — those who are in occupations that make it very unlikely that they are undocumented (police officers, for example), those who receive government benefits for which undocumented aliens are ineligible, and veterans — are automatically coded as LPRs. For other noncitizens, their probability of being an LPR vs. an undocumented alien depends on state of residence, sex, and occupation.


[1] This work was performed under contract with the Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation (HHS/ASPE).  The TRIM3 model is maintained and developed by the Urban Institute, under primary funding from the Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation (HHS/ASPE). Paul Johnson provided programming assistance and Jessica Kronstadt helped run simulations and analyze their results.

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Last revised: 06/21/07