Introducing the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR): Description, Data Construction Methodology, and Quality Assessment
August 2022
Working Paper Number:
CES-22-29
Abstract
This report introduces a new dataset, the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR), consisting of MEPS-IC survey data on establishments and their health insurance benefits packages linked to Decennial Census data and administrative tax records on MEPS-IC establishments' workforces. These data include new measures of the characteristics of MEPS-IC establishments' parent firms, employee turnover, the full distribution of MEPS-IC workers' personal and family incomes, the geographic locations where those workers live, and improved workforce demographic detail. Next, this report details the methods used for producing the MEPS-ICAR. Broadly, the linking process begins by matching establishments' parent firms to their workforces using identifiers appearing in tax records. The linking process concludes by matching establishments to their own workforces by identifying the subset of their parent firm's workforce that best matches the expected size, total payroll, and residential geographic distribution of the establishment's workforce. Finally, this report presents statistics characterizing the match rate and the MEPS-ICAR data itself. Key results include that match rates are consistently high (exceeding 90%) across nearly all data subgroups and that the matched data exhibit a reasonable distribution of employment, payroll, and worker commute distances relative to expectations and external benchmarks. Notably, employment measures derived from tax records, but not used in the match itself, correspond with high fidelity to the employment levels that establishments report in the MEPS-IC. Cumulatively, the construction of the MEPS-ICAR significantly expands the capabilities of the MEPS-IC and presents many opportunities for analysts.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
payroll,
survey,
respondent,
employee,
employ,
employed,
employment estimates,
employment data,
insurance,
workforce,
tax,
associate,
employment measures,
employment statistics,
irs,
medicaid,
filing,
assessed,
income data
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
Internal Revenue Service,
Center for Economic Studies,
Administrative Records,
Current Population Survey,
Decennial Census,
Medical Expenditure Panel Survey,
Employer Identification Numbers,
University of Minnesota,
American Community Survey,
Longitudinal Employer Household Dynamics,
Agency for Healthcare Research and Quality,
Business Register,
United States Census Bureau,
Federal Insurance Contribution Act,
Protected Identification Key,
Department of Health and Human Services,
Quarterly Workforce Indicators,
Census Bureau Disclosure Review Board,
Disclosure Review Board,
Center for Administrative Records Research,
Personally Identifiable Information,
Data Management System
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'Introducing the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR): Description, Data Construction Methodology, and Quality Assessment' are listed below in order of similarity.
-
Working PaperNational Experimental Wellbeing Statistics - Version 1
February 2023
Working Paper Number:
CES-23-04
This is the U.S. Census Bureau's first release of the National Experimental Wellbeing Statistics (NEWS) project. The NEWS project aims to produce the best possible estimates of income and poverty given all available survey and administrative data. We link survey, decennial census, administrative, and third-party data to address measurement error in income and poverty statistics. We estimate improved (pre-tax money) income and poverty statistics for 2018 by addressing several possible sources of bias documented in prior research. We address biases from 1) unit nonresponse through improved weights, 2) missing income information in both survey and administrative data through improved imputation, and 3) misreporting by combining or replacing survey responses with administrative information. Reducing survey error substantially affects key measures of well-being: We estimate median household income is 6.3 percent higher than in survey estimates, and poverty is 1.1 percentage points lower. These changes are driven by subpopulations for which survey error is particularly relevant. For house holders aged 65 and over, median household income is 27.3 percent higher and poverty is 3.3 percentage points lower than in survey estimates. We do not find a significant impact on median household income for householders under 65 or on child poverty. Finally, we discuss plans for future releases: addressing other potential sources of bias, releasing additional years of statistics, extending the income concepts measured, and including smaller geographies such as state and county.View Full Paper PDF
-
Working PaperA Comparison of Employee Benefits Data from the MEPS-IC and Form 5500
September 2008
Working Paper Number:
CES-08-32
This paper compares data on employers\u2019 health and pension offerings from the two sources: publicly available administrative data from Form 5500 filings and survey data from the Insurance Component of the Medical Expenditure Panel Survey (MEPS-IC). The basic findings are that the 5500 filings cover too few health plans to be very useful as a substitute or supplement to the MEPS-IC measure of whether or not employers offer health insurance. The pension information in the 5500 filings is potentially more useful as a supplement to the MEPSIC for research purposes where additional pension information would be useful in studying employers\u2019 decisions to offer health insurance.View Full Paper PDF
-
Working PaperNew Uses of Health and Pension Information
January 2002
Working Paper Number:
tp-2002-03
View Full Paper PDF
-
Working PaperEmployer-Sim Microsimulation Model: Model Development and Application to Estimation of Tax Subsidies to Health Insurance
December 2014
Working Paper Number:
CES-14-46
Employment-related health coverage is the predominant form of health insurance in the nonelderly, US population. Developing sound policies regarding the tax treatment of employer-sponsored insurance requires detailed information on the insurance benefits offered by employers as well as detailed information on the characteristics of employees and their familes. Unfortunately, no nationally representative data set contains all of the necessary elements. This paper describes the development of the Employer-Sim model which models tax-based health policies by using data on workers from the Medical Expenditure Panel Survey Household Component (MEPS HC) to form synthetic workforces for each establishment in the Medical Expenditure Panel Survey Insurance Component (MEPS IC). This paper describes the application of Employer-Sim to estimating tax subsidies to employer-sponsored health insurance and presents estimates of the cost and indcidence of the subsidy for 2008. The paper concludes by discussing other potential applications of the Employer-Sim model.View Full Paper PDF
-
Working PaperDeclines in Employer Sponsored Coverage Between 2000 and 2008: Offers, Take-Up, Premium Contributions, and Dependent Options
September 2010
Working Paper Number:
CES-10-23
Even before the current economic downturn, rates of employer-sponsored insurance (ESI) declined substantially, falling six percentage points between 2000 and 2008 for nonelderly Americans. During a previously documented decline in ESI, from 1987 to 1996, the fall was found to be the result of a reduction in enrollment or 'take-up' of offered coverage and not a decline in employer offer/eligibility rates. In this paper, we investigate the components of the more recent decline in ESI coverage by firm size, using data from the MEPS-IC, a large nationally representative survey of employers. We examine changes in offer rates, eligibility rates and take-up rates for coverage, and include a new dimension, the availability of and enrollment in dependent coverage. We investigate how these components changed for employers of different sizes and find that declining coverage rates for small firms were due to declines in both offer and take-up rates while declining rates for large firms were due to declining enrollment in offered coverage. We also find a decrease in the availability of dependent coverage at small employers and a shift towards single coverage across employers of all sizes. Understanding the components of the decline in coverage for small and large firms is important for establishing the baseline for observing the effects of the current economic downturn and the implementation of health insurance reform.View Full Paper PDF
-
Working PaperEstimating the Costs of Covering Dependents through Employer-Sponsored Plans
January 2017
Working Paper Number:
CES-17-48
Several health reform microsimulation models use synthetic firms to estimate how changes in federal and state policies will affect employers' offers of health insurance, as well as the price of health insurance for workers and firms. These models typically rely on distinct measures of the average costs of single and dependent coverage, for employees and employers, which do not capture the joint distribution of these costs. Since some firms pay a large share of the premium for single polices but a lower share for dependent coverage, or the reverse, simulation models that do not account for the joint distribution of premium costs may not be sufficient to answer certain policy questions. To address this issue, we developed a method to extract estimates of the joint distribution of employer and employee costs of health insurance coverage from the Medical Expenditure Panel Survey ' Insurance Component (MEPS-IC). This paper describes how these distributions were constructed and how they were incorporated into the Urban Institute's Health Insurance Policy Simulation Model (HIPSM). The estimates presented in this paper and those available in supplementary datasets may be useful for other simulation models that need to utilize information on the joint distribution of single and dependent employee premium contributions.View Full Paper PDF
-
Working PaperInvestigating the Use of Administrative Records in the Consumer Expenditure Survey
March 2018
Working Paper Number:
carra-2018-01
In this paper, we investigate the potential of applying administrative records income data to the Consumer Expenditure (CE) survey to inform measurement error properties of CE estimates, supplement respondent-collected data, and estimate the representativeness of the CE survey by income level. We match individual responses to Consumer Expenditure Quarterly Interview Survey data collected from July 2013 through December 2014 to IRS administrative data in order to analyze CE questions on wages, social security payroll deductions, self-employment income receipt and retirement income. We find that while wage amounts are largely in alignment between the CE and administrative records in the middle of the wage distribution, there is evidence that wages are over-reported to the CE at the bottom of the wage distribution and under-reported at the top of the wage distribution. We find mixed evidence for alignment between the CE and administrative records on questions covering payroll deductions and self-employment income receipt, but find substantial divergence between CE responses and administrative records when examining retirement income. In addition to the analysis using person-based linkages, we also match responding and non-responding CE sample units to the universe of IRS 1040 tax returns by address to examine non-response bias. We find that non-responding households are substantially richer than responding households, and that very high income households are less likely to respond to the CE.View Full Paper PDF
-
Working PaperDescribing the Form 5500-Business Register Match
January 2003
Working Paper Number:
tp-2003-05
View Full Paper PDF
-
Working PaperUsing the MEPS-IC to Study Retiree Health Insurance
April 2006
Working Paper Number:
CES-06-13
This paper discusses using the restricted-access Medical Expenditure Panel Survey- Insurance Component (MEPS-IC) to study employer-sponsored retiree health insurance (RHI). This topic is particularly interesting given current events such as the aging of baby boomers, rising health care costs, new prescription drug coverage under Medicare, and changes in accounting standards for reporting liabilities related to RHI offerings. Consequently, employers are grappling with an aging workforce, evaluating Medicare subsidies to employers for offering retiree drug plans, facing rising premium costs as a result of rising health care costs, and trying to show profitability on financial reports. This paper provides technical information on using the MEPS-IC to study RHI and points out data issues with some of the measures in the database. Descriptive statistics are provided to illustrate the types of retiree estimates possible using the MEPS-IC and to show some of the trends in this subject area. Not surprising, these estimates show that employer offers of RHI have declined, greater numbers of retirees are enrolling in these plans, and expenditures for employer-sponsored RHI have been rising.View Full Paper PDF
-
Working PaperEarnings Through the Stages: Using Tax Data to Test for Sources of Error in CPS ASEC Earnings and Inequality Measures
September 2024
Working Paper Number:
CES-24-52
In this paper, I explore the impact of generalized coverage error, item non-response bias, and measurement error on measures of earnings and earnings inequality in the CPS ASEC. I match addresses selected for the CPS ASEC to administrative data from 1040 tax returns. I then compare earnings statistics in the tax data for wage and salary earnings in samples corresponding to seven stages of the CPS ASEC survey production process. I also compare the statistics using the actual survey responses. The statistics I examine include mean earnings, the Gini coefficient, percentile earnings shares, and shares of the survey weight for a range of percentiles. I examine how the accuracy of the statistics calculated using the survey data is affected by including imputed responses for both those who did not respond to the full CPS ASEC and those who did not respond to the earnings question. I find that generalized coverage error and item nonresponse bias are dominated by measurement error, and that an important aspect of measurement error is households reporting no wage and salary earnings in the CPS ASEC when there are such earnings in the tax data. I find that the CPS ASEC sample misses earnings at the high end of the distribution from the initial selection stage and that the final survey weights exacerbate this.View Full Paper PDF
