CREAT: Census Research Exploration and Analysis Tool

Papers Containing Keywords(s): 'database'

The following papers contain search terms that you selected. From the papers listed below, you can navigate to the PDF, the profile page for that working paper, or see all the working papers written by an author. You can also explore tags, keywords, and authors that occur frequently within these papers.
Click here to search again

Frequently Occurring Concepts within this Search

Service Annual Survey - 13

Internal Revenue Service - 12

Center for Economic Studies - 12

Social Security Administration - 11

National Science Foundation - 11

Longitudinal Business Database - 10

Research Data Center - 10

North American Industry Classification System - 10

American Community Survey - 9

Protected Identification Key - 7

Person Validation System - 7

Person Identification Validation System - 7

Standard Industrial Classification - 7

County Business Patterns - 7

Longitudinal Employer Household Dynamics - 7

Business Register - 7

Business Dynamics Statistics - 7

Cornell University - 7

Social Security Number - 7

Bureau of Labor Statistics - 6

Economic Census - 6

Center for Administrative Records Research and Applications - 6

Census Bureau Disclosure Review Board - 5

Standard Statistical Establishment List - 5

Longitudinal Research Database - 5

Quarterly Workforce Indicators - 5

Chicago Census Research Data Center - 5

Survey of Income and Program Participation - 5

SSA Numident - 5

National Opinion Research Center - 5

Current Population Survey - 4

2020 Census - 4

Federal Statistical Research Data Center - 4

American Economic Association - 4

American Statistical Association - 4

Social Security - 4

National Center for Health Statistics - 4

Special Sworn Status - 4

Census Numident - 4

Indian Health Service - 3

Small Business Administration - 3

Metropolitan Statistical Area - 3

Company Organization Survey - 3

Employer Identification Number - 3

Disclosure Review Board - 3

Bureau of Economic Analysis - 3

Alfred P Sloan Foundation - 3

University of Michigan - 3

Unemployment Insurance - 3

National Institutes of Health - 3

Decennial Census - 3

Personally Identifiable Information - 3

Individual Taxpayer Identification Numbers - 3

Minnesota Population Center - 3

Census Bureau Person Identification Validation System - 3

Duke University - 3

Viewing papers 1 through 10 of 24


  • Working Paper

    Revisiting Methods to Assign Responses when Race and Hispanic Origin Reporting are Discrepant Across Administrative Records and Third Party Sources

    May 2024

    Authors: James Noon

    Working Paper Number:

    CES-24-26

    The Best Race and Ethnicity Administrative Records Composite file ('Best Race file') is an composite file which combines Census, federal, and Third Party Data (TPD) sources and applies business rules to assign race and ethnicity values to person records. The first version of the Best Race administrative records composite was first constructed in 2015 and subsequently updated each year to include more recent vintages, when available, of the data sources originally included in the composite file. Where updates were available for data sources, the most recent information for persons was retained, and the business rules were reapplied to assign a single race and single Hispanic origin value to each person record. The majority of person records on the Best Race file have consistent race and ethnicity information across data sources. Where there are discrepancies in responses across data sources, we apply a series of business rules to assign a single race and ethnicity to each record. To improve the quality of the Best Race administrative records composite, we have begun revising the business rules which were developed several years ago. This paper discusses the original business rules as well as the implemented changes and their impact on the composite file.
    View Full Paper PDF
  • Working Paper

    Redesigning the Longitudinal Business Database

    May 2021

    Working Paper Number:

    CES-21-08

    In this paper we describe the U.S. Census Bureau's redesign and production implementation of the Longitudinal Business Database (LBD) first introduced by Jarmin and Miranda (2002). The LBD is used to create the Business Dynamics Statistics (BDS), tabulations describing the entry, exit, expansion, and contraction of businesses. The new LBD and BDS also incorporate information formerly provided by the Statistics of U.S. Businesses program, which produced similar year-to-year measures of employment and establishment flows. We describe in detail how the LBD is created from curation of the input administrative data, longitudinal matching, retiming of economic census-year births and deaths, creation of vintage consistent industry codes and noise factors, and the creation and cleaning of each year of LBD data. This documentation is intended to facilitate the proper use and understanding of the data by both researchers with approved projects accessing the LBD microdata and those using the BDS tabulations.
    View Full Paper PDF
  • Working Paper

    Re-engineering Key National Economic Indicators

    July 2019

    Working Paper Number:

    CES-19-22

    Traditional methods of collecting data from businesses and households face increasing challenges. These include declining response rates to surveys, increasing costs to traditional modes of data collection, and the difficulty of keeping pace with rapid changes in the economy. The digitization of virtually all market transactions offers the potential for re-engineering key national economic indicators. The challenge for the statistical system is how to operate in this data-rich environment. This paper focuses on the opportunities for collecting item-level data at the source and constructing key indicators using measurement methods consistent with such a data infrastructure. Ubiquitous digitization of transactions allows price and quantity be collected or aggregated simultaneously at the source. This new architecture for economic statistics creates challenges arising from the rapid change in items sold. The paper explores some recently proposed techniques for estimating price and quantity indices in large scale item-level data. Although those methods display tremendous promise, substantially more research is necessary before they will be ready to serve as the basis for the official economic statistics. Finally, the paper addresses implications for building national statistics from transactions for data collection and for the capabilities and organization of the statistical agencies in the 21st century.
    View Full Paper PDF
  • Working Paper

    Squeezing More Out of Your Data: Business Record Linkage with Python

    November 2018

    Working Paper Number:

    CES-18-46

    Integrating data from different sources has become a fundamental component of modern data analytics. Record linkage methods represent an important class of tools for accomplishing such integration. In the absence of common disambiguated identifiers, researchers often must resort to ''fuzzy" matching, which allows imprecision in the characteristics used to identify common entities across dfferent datasets. While the record linkage literature has identified numerous individually useful fuzzy matching techniques, there is little consensus on a way to integrate those techniques within a single framework. To this end, we introduce the Multiple Algorithm Matching for Better Analytics (MAMBA), an easy-to-use, flexible, scalable, and transparent software platform for business record linkage applications using Census microdata. MAMBA leverages multiple string comparators to assess the similarity of records using a machine learning algorithm to disambiguate matches. This software represents a transparent tool for researchers seeking to link external business data to the Census Business Register files.
    View Full Paper PDF
  • Working Paper

    Disclosure Limitation and Confidentiality Protection in Linked Data

    January 2018

    Working Paper Number:

    CES-18-07

    Confidentiality protection for linked administrative data is a combination of access modalities and statistical disclosure limitation. We review traditional statistical disclosure limitation methods and newer methods based on synthetic data, input noise infusion and formal privacy. We discuss how these methods are integrated with access modalities by providing three detailed examples. The first example is the linkages in the Health and Retirement Study to Social Security Administration data. The second example is the linkage of the Survey of Income and Program Participation to administrative data from the Internal Revenue Service and the Social Security Administration. The third example is the Longitudinal Employer-Household Dynamics data, which links state unemployment insurance records for workers and firms to a wide variety of censuses and surveys at the U.S. Census Bureau. For examples, we discuss access modalities, disclosure limitation methods, the effectiveness of those methods, and the resulting analytical validity. The final sections discuss recent advances in access modalities for linked administrative data.
    View Full Paper PDF
  • Working Paper

    Examining Multi-Level Correlates of Suicide by Merging NVDRS and ACS Data

    January 2017

    Working Paper Number:

    CES-17-25

    This paper describes a novel database and an associated suicide event prediction model that surmount longstanding barriers in suicide risk factor research. The database comingles person-level records from the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) to establish a case-control study sample that includes all identified suicide cases, while faithfully reflecting general population sociodemographics, in sixteen USA states during the years 2005 2011. It supports a statistical model of individual suicide risk that accommodates person-level factors and the moderation of these factors by their community rates. Named the United States Multi-Level Suicide Data Set (US-MSDS), the database was developed outside the RDC laboratory using publicly available ACS microdata, and reconstructed inside the laboratory using restricted access ACS microdata. Analyses of the latter version yielded findings that largely amplified but also extended those obtained from analyses of the former. This experience shows that the analytic precision achievable using restricted access ACS data can play an important role in conducting social research, although it also indicates that publicly available ACS data have considerable value in conducting preliminary analyses and preparing to use an RDC laboratory. The database development strategy may interest scientists investigating sociodemographic risk factors for other types of low-frequency mortality.
    View Full Paper PDF
  • Working Paper

    Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics

    February 2016

    Working Paper Number:

    CES-16-10

    We describe and analyze a method that blends records from both observed and synthetic microdata into public-use tabulations on establishment statistics. The resulting tables use synthetic data only in potentially sensitive cells. We describe different algorithms, and present preliminary results when applied to the Census Bureau's Business Dynamics Statistics and Synthetic Longitudinal Business Database, highlighting accuracy and protection afforded by the method when compared to existing public-use tabulations (with suppressions).
    View Full Paper PDF
  • 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.
    View Full Paper PDF
  • Working Paper

    Business Dynamics of Innovating Firms: Linking U.S. Patents with Administrative Data on Workers and Firms

    July 2015

    Working Paper Number:

    CES-15-19

    This paper discusses the construction of a new longitudinal database tracking inventors and patent-owning firms over time. We match granted patents between 2000 and 2011 to administrative databases of firms and workers housed at the U.S. Census Bureau. We use inventor information in addition to the patent assignee firm name to and improve on previous efforts linking patents to firms. The triangulated database allows us to maximize match rates and provide validation for a large fraction of matches. In this paper, we describe the construction of the database and explore basic features of the data. We find patenting firms, particularly young patenting firms, disproportionally contribute jobs to the U.S. economy. We find patenting is a relatively rare event among small firms but that most patenting firms are nevertheless small, and that patenting is not as rare an event for the youngest firms compared to the oldest firms. While manufacturing firms are more likely to patent than firms in other sectors, we find most patenting firms are in the services and wholesale sectors. These new data are a product of collaboration within the U.S. Department of Commerce, between the U.S. Census Bureau and the U.S. Patent and Trademark Office.
    View Full Paper PDF
  • Working Paper

    Creating Linked Historical Data: An Assessment of the Census Bureau's Ability to Assign Protected Identification Keys to the 1960 Census

    September 2014

    Working Paper Number:

    carra-2014-12

    In order to study social phenomena over the course of the 20th century, the Census Bureau is investigating the feasibility of digitizing historical census records and linking them to contemporary data. However, historical censuses have limited personally identifiable information available to match on. In this paper, I discuss the problems associated with matching older censuses to contemporary data files, and I describe the matching process used to match a small sample of the 1960 census to the Social Security Administration Numeric Identification System.
    View Full Paper PDF