Papers Containing Tag(s): 'Longitudinal Employer Household Dynamics'
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Viewing papers 211 through 220 of 246
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Working PaperSocial, Economic, Spatial, and Commuting Patterns of Self-Employed Jobholders
April 2007
Working Paper Number:
tp-2007-03
A significant number of employees within the United States identify themselves as selfemployed, and they are distinct from the larger group identified as private jobholders. While socioeconomic and spatial information on these individuals is readily available in standard datasets, such as the 2000 Decennial Census Long Form, it is possible to gain further information on their wage earnings by using data from administrative wage records. This study takes advantage of firm-based data from Unemployment Insurance administrative wage records linked with the Census Bureau's household-based data in order to examine self-employed jobholders - both as a whole and as subgroups defined according to their earned wage status - by their demographic characteristics as well as their economic, commuting, and spatial location outcomes. Additionally, this report evaluates whether self-employed jobholders and the defined subgroups should be included explicitly in future labor-workforce analyses and transportation modeling. The analyses in this report use the sample of self-employed workers who lived in Los Angeles County, California.View Full Paper PDF
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Working PaperSocial, Economic, Spatial, and Commuting Patterns of Informal Jobholders
April 2007
Working Paper Number:
tp-2007-02
A significant number of employees within the United States can be considered "informal" or "off-the-books" workers. These workers, who by definition do not appear in administrative wage records, are distinct from the larger group of private jobholders who do appear in administrative records. However, while socioeconomic and spatial information on these individuals is readily available in standard datasets, such as the 2000 Decennial Census Long Form, it is not possible to identify the informal workers by only using such data because of the lack of accurate, formal wage records. This study takes advantage of firm-based data that originates in Unemployment Insurance administrative wage records linked with the Census Bureau's household-based data in order to examine informal jobholders by their demographic characteristics as well as their economic, commuting, and spatial location outcomes. In addition this report evaluates whether informal jobholders should be included explicitly in future labor-workforce analyses and transportation modeling. The analyses in this report use the sample of workers who lived in Los Angeles County, California.View Full Paper PDF
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Working PaperSocial, Economic, Spatial, and Commuting Patterns of Dual Jobholders
April 2007
Working Paper Number:
tp-2007-01
Individuals who hold multiple jobs have complex working lives and complex commuting patterns. Economic and spatial information on these individuals is not readily available in standard datasets, such as the 2000 Decennial Census Long Form, because the survey questions were not designed to collect details on multiple jobs. This study takes advantage of firm-based data from the Unemployment Insurance administrative wage records, linked with the Census Bureau's household-based data, to examine multiple jobholders - and specifically a sentinel group of dual jobholders. The study uses a sample from Los Angeles County, California and examines the dual jobholders by their demographic characteristics as well as their economic, commuting, and spatial location outcomes. In addition this report evaluates whether multiple jobholders should be included explicitly in future labor-workforce analyses and transportation modeling.View Full Paper PDF
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Working PaperMeasuring U.S. Innovative Activity
March 2007
Working Paper Number:
CES-07-11
Innovation has long been credited as a leading source of economic strength and vitality in the United States because it leads to new goods and services and increases productivity, leading to better living standards. Better measures of innovative activities'activities including but not limited to innovation alone'could improve what we know about the sources of productivity and economic growth. The U.S. Census Bureau either currently collects, or has collected, data on some measures of innovative activities, such as the diffusion of innovations and technologies, human and organizational capital, entrepreneurship and other worker and firm characteristics, and the entry and exit of businesses, that research shows affect productivity and other measures of economic performance. But developing an understanding of how those effects work requires more than just measures of innovative activity. It also requires solid statistical information about core measures of the economy: that is, comprehensive coverage of all industries, including improved measures of output and sales and additional information on inputs and purchased materials at the micro (enterprise) level for the same economic unit over time (so the effects can be measured). Filling gaps in core data would allow us to rule out the possibility that a measure of innovative activity merely proxies for something that is omitted from or measured poorly in the core data, provide more information about innovative activities, and strengthen our ability to evaluate the performance of the entire economy. These gaps can be filled by better integrating existing data and by more structured collections of new data.View Full Paper PDF
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Working PaperGross Job Flows for the U.S. Manufacturing Sector: Measurement from the Longitudinal Research Database
December 2006
Working Paper Number:
CES-06-30
Measures of job creation and destruction are now produced regularly by the U.S. statistical agencies. The Bureau of Labor Statistics releases via the Business Employment Dynamics (BED) on a quarterly basis measures of job creation and destruction for the U.S. nonfarm business sector and related disaggregation by industrial sector and size class. The U.S. Census Bureau has developed the Longitudinal Business Database (LBD) covering the nonfarm business sector that has been used to produce research analysis and special tabulations including tabulations of job creation and destruction. Both of these data programs build upon the measurement methods and data analysis of job creation and destruction measures from the Longitudinal Research Database (LRD) developed and published by Davis, Haltiwanger and Schuh (1996). In this paper, the LRD based estimates of job creation and destruction are updated and made available for consistent annual and quarterly series from 1972-1998. While the BED and LBD programs are more comprehensive in scope than the LRD, the extensive development of the LRD permits the construction of measures of job creation and destruction for a rich array of employer characteristics including industry, size, business age, ownership structure, location and wage structure. The updated series that are released with this working paper provide measures along each of these dimensions. The paper describes in detail the changes in the processing of the Annual Survey of Manufactures over the 1972-1998 period that are important to incorporate by users of the LRD at Census Research Data Centers as well as users of products from the LRD such as job creation and destruction.View Full Paper PDF
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Working PaperDistribution Preserving Statistical Disclosure Limitation
September 2006
Working Paper Number:
tp-2006-04
One approach to limiting disclosure risk in public-use microdata is to release multiply-imputed, partially synthetic data sets. These are data on actual respondents, but with confidential data replaced by multiply-imputed synthetic values. A mis-specified imputation model can invalidate inferences because the distribution of synthetic data is completely determined by the model used to generate them. We present two practical methods of generating synthetic values when the imputer has only limited information about the true data generating process. One is applicable when the true likelihood is known up to a monotone transformation. The second requires only limited knowledge of the true likelihood, but nevertheless preserves the conditional distribution of the confidential data, up to sampling error, on arbitrary subdomains. Our method maximizes data utility and minimizes incremental disclosure risk up to posterior uncertainty in the imputation model and sampling error in the estimated transformation. We validate the approach with a simulation and application to a large linked employer-employee database.View Full Paper PDF
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Working PaperUsing linked employer-employee data to investigate the speed of adjustments in downsizing firms
May 2006
Working Paper Number:
tp-2006-03
When firms are faced with a demand shock, adjustment can take many forms. Firms can adjust physical capital, human capital, or both. The speed of adjustment may differ as well: costs of adjustment, the type of shock, the legal and economic enviroment all matter. In this paper, we focus on firms that downsized between 1992 and 1997, but ultimately survive, and investigate how the human capital distribution within a firm influences the speed of adjustment, ceteris paribus. In other words, when do firms use mass layoffs instead of attrition to adjust the level of employment. We combine worker-level wage records and measures of human capital with firm-level characteristics of the production function, and use levels and changes in these variables to characterize the choice of adjustment method and speed. Firms are described/compared up to 9 years prior to death. We also consider how workers fare after leaving downsizing firms, and analyze if observed differences in post-separation outcomes of workers provide clues to the choice of adjustment speed.View Full Paper PDF
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Working PaperMeasuring the Dynamics of Young and Small Businesses: Integrating the Employer and Nonemployer Universes
February 2006
Working Paper Number:
CES-06-04
We develop a preliminary version of an Integrated Longitudinal Business Database (ILBD) that combines administrative records and survey-based data for virtually all employer and nonemployer business units in the United States. In the process, we confront conceptual and practical issues that arise in measuring the importance and dynamic behavior of younger and smaller businesses. We also document some basic facts about younger and smaller businesses. In doing so, we exploit the ability of the ILBD to follow business transitions between employer and nonemployer status, and vice-versa. This aspect of the ILBD opens a new frontier for the study of business formation and the precursors to job creation in the U.S. economy.View Full Paper PDF
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Working PaperConfidentiality Protection in the Census Bureau Quarterly Workforce Indicators
February 2006
Working Paper Number:
tp-2006-02
The QuarterlyWorkforce Indicators are new estimates developed by the Census Bureau's Longitudinal Employer-Household Dynamics Program as a part of its Local Employment Dynamics partnership with 37 state Labor Market Information offices. These data provide detailed quarterly statistics on employment, accessions, layoffs, hires, separations, full-quarter employment (and related flows), job creations, job destructions, and earnings (for flow and stock categories of workers). The data are released for NAICS industries (and 4-digit SICs) at the county, workforce investment board, and metropolitan area levels of geography. The confidential microdata - unemployment insurance wage records, ES-202 establishment employment, and Title 13 demographic and economic information - are protected using a permanent multiplicative noise distortion factor. This factor distorts all input sums, counts, differences and ratios. The released statistics are analytically valid - measures are unbiased and time series properties are preserved. The confidentiality protection is manifested in the release of some statistics that are flagged as "significantly distorted to preserve confidentiality." These statistics differ from the undistorted statistics by a significant proportion. Even for the significantly distorted statistics, the data remain analytically valid for time series properties. The released data can be aggregated; however, published aggregates are less distorted than custom postrelease aggregates. In addition to the multiplicative noise distortion, confidentiality protection is provided by the estimation process for the QWIs, which multiply imputes all missing data (including missing establishment, given UI account, in the UI wage record data) and dynamically re-weights the establishment data to provide state-level comparability with the BLS's Quarterly Census of Employment and Wages.View Full Paper PDF
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Working PaperThe LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators
January 2006
Working Paper Number:
tp-2006-01
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, has built 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. Beginning in 2003 and building on this infrastructure, the Census Bureau has published the Quarterly Workforce Indicators (QWI), a new collection of data series that offers unprecedented detail on the local dynamics of labor markets. Despite the fine detail, confidentiality is maintained due to the application of state-of-the-art confidentiality protection methods. This article describes how the input files are compiled and combined to create the infrastructure files. We describe the multiple imputation methods used to impute in missing data and the statistical matching techniques used to combine and edit data when a direct identifier match requires improvement. Both of these innovations are crucial to the success of the final product. Finally, we pay special attention to the details of the confidentiality protection system used to protect the identity and micro data values of the underlying entities used to form the published estimates. We provide a brief description of public-use and restricted-access data files with pointers to further documentation for researchers interested in using these data.View Full Paper PDF
