Papers Containing Tag(s): 'Employer Identification Numbers'
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Viewing papers 181 through 183 of 183
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Working PaperThe Contribution Of Establishment Births And Deaths To Employment Growth
April 1998
Working Paper Number:
CES-98-05
The purpose of this paper is to examine how establishment births and deaths contribute to job creation, job destruction, and net employment growth at different frequencies of measurement. The longitudinal data are constructed from quarterly unemployment insurance microdata, and are essentially a census of establishments in all industries. Defining establishment births and deaths turns out to be an exercise in how to use cross-sectional administrative data for longitudinal research purposes. The analysis of job flows indicates that the frame is relatively small but certainly non-trivial, whereas births and deaths account for roughly half of all jobs created and destroyed on a triennial time frame. Net Employment GrowthView Full Paper PDF
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Working PaperUsing Matched Client And Census Data To Evaluate The Performance Of The Manufacturing Extension Partnership
April 1995
Working Paper Number:
CES-95-07
This paper proposes a framework for evaluating the Manufacturing Extension Partnership (MEP). The MEP is administered by the National Institute of Standards and Technology (NIST) as part of its effort to improve the global competitiveness of U.S. manufacturing industries. As the name implies, the MEP is modelled after agricultural extension. Rather than farmers the MEP's target population is small and medium sized manufacturers, generally those with less than 500 employees. The MEP currently supports 44 manufacturing extension centers around the country. These centers provide technical and business assistance for manufacturers much as county extension agents do for farmers. The goal of evaluation is to see if MEP engagements lead to positive outcomes from the view of important MEP stakeholders (e.g., MEP clients, MEP centers, NIST, state and local governments and Congress). These outcomes are discussed in McGuckin and Redman (1995) and include: Process Outcomes (e.g., adoption of a new technology by a client); Intermediate Outcomes (e.g., reduction in the clients defect rate); Business Outcomes (e.g., survival and profits) and Policy Outcomes (increases in employment,wages and/or exports). The evaluation framework described in this paper has two components. The first component is an evaluation dataset which contains measures of many of the program outcomes listed above for both MEP clients and a representative control group of non- clients. This dataset will be constructed by linking MEP client records with plant level Census data housed at the Center for Economic Studies of the Census Bureau. The Census data provides measures of several outcome and control variables which are comparable across both plants and time. The Census data include observations for all manufacturing plants in the U.S. from which representative control groups can be constructed. The MEP client records provide data on the type and intensity of extension engagements. Linking these rich sources of information yields a comprehensive and powerful dataset for MEP evaluation. The second component is an evaluation methodology which exploits this rich dataset to make statistical inferences about the impact of MEP services, while carefully controlling for other influences. By using this methodology, we can address many of the shortcomings which plagued previous attempts to evaluate extension services. In addition to evaluation, the dataset described in this paper may be used to profile the characteristics of MEP clients and compare them to non-clients. The Census data contain the complete universe of manufacturing establishments in the U.S.View Full Paper PDF
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Working PaperPublished Versus Sample Statistics From The ASM: Implications For The LRD
January 1991
Working Paper Number:
CES-91-01
In principle, the Longitudinal Research Database ( LRD ) which links the establishments in the Annual Survey of Manufactures (ASM) is ideal for examining the dynamics of firm and aggregate behavior. However, the published ASM aggregates are not simply the appropriately weighted sums of establishment data in the LRD . Instead, the published data equal the sum of LRD-based sample estimates and nonsample estimates. The latter reflect adjustments related to sampling error and the imputation of small-establishment data. Differences between the LRD and the ASM raise questions for users of both data sets. For ASM users, time-series variation in the difference indicates potential problems in consistently and reliably estimating the nonsample portion of the ASM. For LRD users, potential sample selection problems arise due to the systematic exclusion of data from small establishments. Microeconomic studies based on the LRD can yield misleading inferences to the extent that small establishments behave differently. Similarly, new economic aggregates constructed from the LRD can yield incorrect estimates of levels and growth rates. This paper documents cross-sectional and time-series differences between ASM and LRD estimates of levels and growth rates of total employment, and compares them with employment estimates provided by Bureau of Labor Statistics and County Business Patterns data. In addition, this paper explores potential adjustments to economic aggregates constructed from the LRD. In particular, the paper reports the results of adjusting LRD-based estimates of gross job creation and destruction to be consistent with net job changes implied by the published ASM figures.View Full Paper PDF
