CREAT: Census Research Exploration and Analysis Tool

Published Versus Sample Statistics From The ASM: Implications For The LRD

January 1991

Working Paper Number:

CES-91-01

Abstract

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.

Document Tags and Keywords

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:
estimating, estimation, macroeconomic, company, statistical, aggregation, quarterly, enterprise, aggregate, survey, merger, empirical, longitudinal, employment growth, establishment, regression, incorporated, imputation, employment data, employment estimates

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:
Bureau of Labor Statistics, National Science Foundation, Metropolitan Statistical Area, Census of Manufactures, Longitudinal Research Database, Annual Survey of Manufactures, Internal Revenue Service, Social Security Administration, Center for Economic Studies, County Business Patterns, University of Maryland, National Establishment Time Series, Employer Identification Number

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