CREAT: Census Research Exploration and Analysis Tool

Papers Containing Tag(s): 'Census Numident'

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Frequently Occurring Concepts within this Search

Protected Identification Key - 32

Social Security Number - 30

Internal Revenue Service - 29

American Community Survey - 28

Census Bureau Disclosure Review Board - 28

Social Security Administration - 28

Person Validation System - 18

Decennial Census - 17

Social Security - 16

Disclosure Review Board - 16

Longitudinal Employer Household Dynamics - 14

Person Identification Validation System - 14

Current Population Survey - 12

Master Address File - 10

Employer Identification Numbers - 9

W-2 - 9

Personally Identifiable Information - 9

Longitudinal Business Database - 8

Department of Housing and Urban Development - 8

2010 Census - 8

North American Industry Classification System - 8

Individual Taxpayer Identification Numbers - 8

SSA Numident - 8

Business Register - 7

Housing and Urban Development - 6

Bureau of Labor Statistics - 6

Earned Income Tax Credit - 6

Office of Management and Budget - 6

National Opinion Research Center - 6

Center for Economic Studies - 5

Census Bureau Person Identification Validation System - 5

Unemployment Insurance - 5

University of Chicago - 5

Census Edited File - 5

Service Annual Survey - 5

Center for Administrative Records Research and Applications - 5

Quarterly Workforce Indicators - 4

Survey of Income and Program Participation - 4

Medicaid Services - 4

Centers for Medicare - 4

Supplemental Nutrition Assistance Program - 4

1940 Census - 4

Data Management System - 4

PIKed - 4

COVID-19 - 4

Some Other Race - 4

Ordinary Least Squares - 4

MAF-ARF - 4

Census Household Composition Key - 4

Centers for Disease Control and Prevention - 4

National Science Foundation - 4

Indian Health Service - 4

Federal Statistical Research Data Center - 4

Survey of Business Owners - 4

Individual Characteristics File - 3

Business Dynamics Statistics - 3

MAFID - 3

Standard Industrial Classification - 3

National Bureau of Economic Research - 3

County Business Patterns - 3

Employment History File - 3

Employer Characteristics File - 3

Census Bureau Master Address File - 3

Current Population Survey Annual Social and Economic Supplement - 3

Adjusted Gross Income - 3

Cornell University - 3

Office of Personnel Management - 3

Harvard University - 3

Composite Person Record - 3

Postal Service - 3

Research Data Center - 3

Alfred P Sloan Foundation - 3

International Trade Research Report - 3

Indian Housing Information Center - 3

National Institute on Aging - 3

Census Bureau Longitudinal Business Database - 3

Local Employment Dynamics - 3

Federal Tax Information - 3

Department of Defense - 3

Annual Survey of Entrepreneurs - 3

Legal Form of Organization - 3

Viewing papers 31 through 37 of 37


  • Working Paper

    Age and High-Growth Entrepreneurship

    April 2018

    Working Paper Number:

    carra-2018-03

    Many observers, and many investors, believe that young people are especially likely to produce the most successful new firms. We use administrative data at the U.S. Census Bureau to study the ages of founders of growth-oriented start-ups in the past decade. Our primary finding is that successful entrepreneurs are middle-aged, not young. The mean founder age for the 1 in 1,000 fastest growing new ventures is 45.0. The findings are broadly similar when considering high-technology sectors, entrepreneurial hubs, and successful firm exits. Prior experience in the specific industry predicts much greater rates of entrepreneurial success. These findings strongly reject common hypotheses that emphasize youth as a key trait of successful entrepreneurs.
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  • Working Paper

    Just Passing Through: Characterizing U.S. Pass-Through Business Owners

    January 2017

    Working Paper Number:

    CES-17-69

    We investigate the use of administrative data on the owners of partnerships and S-corporations to develop new statistics that characterize business owners. Income from these types of entities is "passed through" to owners to be taxed on the owners' tax returns. The information returns associated with such pass-through entities (Form K1 records) make it possible to link individual owners to the businesses they own. These linkages can be leveraged to associate measures of the demographic and human capital characteristics of business owners with the characteristics of the businesses they own. This paper describes measurement issues associated with administrative records on these pass-through entities and their integration with other Census data products. In addition, we document a number of interesting trends in business ownership among pass-through entities. We show a substantial decline in both entry and exit with less churn among both owners and owned businesses. We also show that the owners of pass-through entities are older, more likely to be male, and more likely to be white compared to the working population.
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  • Working Paper

    Assessing Coverage and Quality of the 2007 Prototype Census Kidlink Database

    September 2015

    Working Paper Number:

    carra-2015-07

    The Census Bureau is conducting research to expand the use of administrative records data in censuses and surveys to decrease respondent burden and reduce costs while improving data quality. Much of this research (e.g., Rastogi and O''Hara (2012), Luque and Bhaskar (2014)) hinges on the ability to integrate multiple data sources by linking individuals across files. One of the Census Bureau's record linkage methodologies for data integration is the Person Identification Validation System or PVS. PVS assigns anonymous and unique IDs (Protected Identification Keys or PIKs) that serve as linkage keys across files. Prior research showed that integrating 'known associates' information into PVS's reference files could potentially enhance PVS's PIK assignment rates. The term 'known associates' refers to people that are likely to be associated with each other because of a known common link (such as family relationships or people sharing a common address), and thus, to be observed together in different files. One of the results from this prior research was the creation of the 2007 Census Kidlink file, a child-level file linking a child's Social Security Number (SSN) record to the SSN of those identified as the child's parents. In this paper, we examine to what extent the 2007 Census Kidlink methodology was able to link parents SSNs to children SSN records, and also evaluate the quality of those links. We find that in approximately 80 percent of cases, at least one parent was linked to the child's record. Younger children and noncitizens have a higher percentage of cases where neither parent could be linked to the child. Using 2007 tax data as a benchmark, our quality evaluation results indicate that in at least 90 percent of the cases, the parent-child link agreed with those found in the tax data. Based on our findings, we propose improvements to the 2007 Kidlink methodology to increase child-parent links, and discuss how the creation of the file could be operationalized moving forward.
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  • Working Paper

    Person Matching in Historical Files using the Census Bureau's Person Validation System

    September 2014

    Working Paper Number:

    carra-2014-11

    The recent release of the 1940 Census manuscripts enables the creation of longitudinal data spanning the whole of the twentieth century. Linked historical and contemporary data would allow unprecedented analyses of the causes and consequences of health, demographic, and economic change. The Census Bureau is uniquely equipped to provide high quality linkages of person records across datasets. This paper summarizes the linkage techniques employed by the Census Bureau and discusses utilization of these techniques to append protected identification keys to the 1940 Census.
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  • Working Paper

    Estimating Record Linkage False Match Rate for the Person Identification Validation System

    July 2014

    Working Paper Number:

    carra-2014-02

    The Census Bureau Person Identification Validation System (PVS) assigns unique person identifiers to federal, commercial, census, and survey data to facilitate linkages across files. PVS uses probabilistic matching to assign a unique Census Bureau identifier for each person. This paper presents a method to measure the false match rate in PVS following the approach of Belin and Rubin (1995). The Belin and Rubin methodology requires truth data to estimate a mixture model. The parameters from the mixture model are used to obtain point estimates of the false match rate for each of the PVS search modules. The truth data requirement is satisfied by the unique access the Census Bureau has to high quality name, date of birth, address and Social Security (SSN) data. Truth data are quickly created for the Belin and Rubin model and do not involve a clerical review process. These truth data are used to create estimates for the Belin and Rubin parameters, making the approach more feasible. Both observed and modeled false match rates are computed for all search modules in federal administrative records data and commercial data.
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  • Working Paper

    The Person Identification Validation System (PVS): Applying the Center for Administrative Records Research and Applications' (CARRA) Record Linkage Software

    July 2014

    Working Paper Number:

    carra-2014-01

    The Census Bureau's Person Identification Validation System (PVS) assigns unique person identifiers to federal, commercial, census, and survey data to facilitate linkages across and within files. PVS uses probabilistic matching to assign a unique Census Bureau identifier for each person. The PVS matches incoming files to reference files created with data from the Social Security Administration (SSA) Numerical Identification file, and SSA data with addresses obtained from federal files. This paper describes the PVS methodology from editing input data to creating the final file.
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  • Working Paper

    LEHD Infrastructure files in the Census RDC - Overview

    June 2014

    Working Paper Number:

    CES-14-26

    The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2011 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureaus secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifcations made to the files to facilitate researcher access.
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