Describing the Form 5500-Business Register Match
January 2003
Working Paper Number:
tp-2003-05
Abstract
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.
:
enterprise,
report,
insurance,
measure,
irs,
coverage,
pension,
retiree,
filing,
identifier
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.
:
Standard Statistical Establishment List,
Internal Revenue Service,
Standard Industrial Classification,
Bureau of Labor Statistics,
Service Annual Survey,
County Business Patterns,
Current Population Survey,
Medical Expenditure Panel Survey,
Employer Identification Numbers,
Survey of Income and Program Participation,
Social Security,
Educational Services,
Census Bureau Business Register,
Business Register
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 'Describing the Form 5500-Business Register Match' are listed below in order of similarity.
-
Working PaperUsing Census Business Data to Augment the MEPS-IC🔥
December 2005
Working Paper Number:
CES-05-26
This paper has two aims: first to describe methods, issues, and outcomes involved in matching data from the Insurance Component of the Medical Expenditure Panel Survey (MEPSIC) to other business microdata collected by the U.S. Census Bureau, and second to present some simple results that illustrate the usefulness of such combined data. We present the results of linking the MEPS-IC with data from the 1997 Economic Censuses (EC), but also discuss other possible sources of business data. An issue in any linkage is whether the linked sample remains representative and large enough to be useful. The EC data are attractive because, given the survey's broad coverage and large sample, most of the MEPS-IC sample can be matched to it. We use the combined EC/MEPS-IC data to construct productivity measures that are useful auxiliary data in examining employers' health insurance offering decisions.View Full Paper PDF
-
Working PaperEmployer-Provided Benefit Plans, Workforce Composition and Firm Outcomes🔥
January 2005
Working Paper Number:
tp-2005-01
What do firms gain by offering benefits? Economists have proposed two payoffs: (i) benefits may be a more cost-effective form of compensation than wages for employees facing high marginal tax rates, and (ii) benefits may attract a more stable, skilled workforce. Both should improve firm outcomes, but we have little evidence on this matter. This paper exploits a rich new dataset to examine how firm productivity and survival are related to benefit offering, and finds that benefit-offering firms have higher productivity and higher survival rates. Differences in firm and workforce characteristics explain some but not all of the differences in outcomes.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 PaperContributions to Health Insurance Premiums: When Does the Employer Pay 100 Percent?
December 2005
Working Paper Number:
CES-05-27
We identify the characteristics of establishments that paid 100 percent of health insurance premiums and the policies they offered from 1997-2001, despite increased premium costs. Analyzing data from the MEPS-IC, we see little change in the percent of establishments that paid the full cost of premiums for employees. Most of these establishments were young, small, singleunits, with a relatively high paid workforce. Plans that were fully paid generally required referrals to see specialists, did not cover pre-existing conditions or outpatient prescriptions, and had the highest out-of-pocket expense limits. These plans also were more likely than plans not fully paid by employers to have had a fee-for-service or exclusive provider arrangement, had the highest premiums, and were less likely to be self-insured.View Full Paper PDF
-
Working PaperUsing Worker Flows in the Analysis of the Firm
August 2003
Working Paper Number:
tp-2003-09
This paper uses a novel approach to measure firm entry and exit, mergers and acquisition. It uses information about the flows of clusters of workers across business units to identify longitudinal linkage relationships in longitudinal business data. These longitudinal relationships may be the result of either administrative or economic changes and we explore both types of newly identified longitudinal relationships. In particular, we develop a set of criteria based on worker flows to identify changes in firm relationships ? such as mergers and acquisitions, administrative identifier changes and outsourcing. We demonstrate how this new data infrastructure and this cluster flow methodology can be used to better differentiate true firm entry/exit and simple changes in administrative identifiers. We explore the role of outsourcing in a variety of ways but in particular the outsourcing of workers to the temporary help industry. While the primary focus is on developing the data infrastructure and the methodology to identify and interpret these clustered flows of workers, we conclude the paper with an analysis of the impact of these changes on the earnings of workers.View Full Paper PDF
-
Working PaperIntegrated Longitudinal Employee-Employer Data for the United States
May 2004
Working Paper Number:
tp-2004-02
View Full Paper PDF
-
Working PaperA Change of PACE: Comparing the 1994 and 1999 Pollution Abatement Costs and Expenditures Surveys
July 2004
Working Paper Number:
CES-04-09
Since 1973, the Pollution Abatement Costs and Expenditures (PACE) survey has been the principle source of information on U.S. industries' capital expenditure and operating costs associated with pollution abatement efforts. The PACE survey was discontinued after 1994 and then revived in 1999 for one year ' in a substantially different form than the preceding surveys however, making longitudinal analysis quite difficult. Conceptual differences include matters as fundamental as the scope and meaning of pollution abatement as well as the definition of operating costs. A number of other critical changes also exist, including ones of industrial coverage and sample selection. This paper is the first comprehensive effort to document the many changes in the PACE survey across these years and to provide a detailed guide for researchers and policymakers who wish to compare the 1994 and 1999 data. Overall, we find a 27% decline in environmental spending by the manufacturing sector between these two years, though there appears to be significant heterogeneity across industries. We discuss potential reasons for this dramatic decline, focusing mainly on issues of survey methodology and design. This paper should help inform current efforts to redevelop the PACE survey and re-establish it as a regular, annual survey.View Full Paper PDF
-
Working PaperNewly Recovered Microdata on U.S. Manufacturing Plants from the 1950s and 1960s: Some Early Glimpses
September 2011
Working Paper Number:
CES-11-29
Longitudinally-linked microdata on U.S. manufacturing plants are currently available to researchers for 1963, 1967, and 1972-2009. In this paper, we provide a first look at recently recovered manufacturing microdata files from the 1950s and 1960s. We describe their origins and background, discuss their contents, and begin to explore their sample coverage. We also begin to examine whether the available establishment identifier(s) allow record linking. Our preliminary analyses suggest that longitudinally-linked Annual Survey of Manufactures microdata from the mid-1950s through the present ' containing 16 years of additional data ' appears possible though challenging. While a great deal of work remains, we see tremendous value in extending the manufacturing microdata series back into time. With these data, new lines of research become possible and many others can be revisited.View Full Paper PDF
-
Working PaperIntroducing 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
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.View Full Paper PDF
