This paper discusses the development and use of the Longitudinal Research Data available at the Center for Economic Studies of the Bureau of the Census in terms of what has been accomplished thus far, what projects are currently in progress, and what plans are in place for the near future. The major achievement to date is the construction of the database itself, which contains data for manufacturing establishments collected by the Census in 1963, 1967, 1972, 1977 and 1982, and the Annual Survey of Manufactures for non-Census years from 1973 to 1985. These data now reside in the Center's computer in a consistent format across all years. In addition, a large software development task that greatly simplifies the task of selecting subsets of the database for specific research projects is well underway. Finally, a number of powerful microcomputers have been purchased for use by researchers for their statistical analysis. Current efforts underway at the Center include research on such policy-relevant issues as mergers and their impact on profits and production, high technology trade, import competition, plant level productivity, entry and exit, and productivity differences between large and small firms. Due to the confidentiality requirements of the Census data, most of their research is performed by Center staff and Special Sworn Employees. Under certain circumstances, the Center accepts user-written programs from outside researchers. These routines are executed by Center staff, and the resultant output is reviewed thoroughly for disclosure problems. The Center is also an active member of a task force working on methods on release "masked" or "cloned" microdata in public-use files that will protect the confidentiality of the data while at the same time provide a research tool for outside users. The Center research program contributes directly to future research possibilities. The current batch of research projects is adding insight into the nature of the LRD database. This information is continually being incorporated into the Center's software system, thus facilitating yet more research activity. Moreover, since a good portion of the research involves linking the Longitudinal Research Data to other data files, such as the NSF/Census R&D data, the scope of the databases is continually being expanded. Furthermore, the Center is exploring the possibility of linking the demographic data collected by the Census Bureau to the LRD database.
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Newly Recovered Microdata on U.S. Manufacturing Plants from the 1950s and 1960s: Some Early Glimpses
September 2011
Working Paper Number:
CES-11-29
Longitudinally-linked microdata on U.S. manufacturing plants are currently available to researchers for 1963, 1967, and 1972-2009. In this paper, we provide a first look at recently recovered manufacturing microdata files from the 1950s and 1960s. We describe their origins and background, discuss their contents, and begin to explore their sample coverage. We also begin to examine whether the available establishment identifier(s) allow record linking. Our preliminary analyses suggest that longitudinally-linked Annual Survey of Manufactures microdata from the mid-1950s through the present ' containing 16 years of additional data ' appears possible though challenging. While a great deal of work remains, we see tremendous value in extending the manufacturing microdata series back into time. With these data, new lines of research become possible and many others can be revisited.
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Public Use Microdata: Disclosure And Usefulness
September 1988
Working Paper Number:
CES-88-03
Official statistical agencies such as the Census Bureau and the Bureau of Labor Statistics collect enormous quantities of microdata in statistical surveys. These data are valuable for economic research and market and policy analysis. However, the data cannot be released to the public because of confidentiality commitments to individual respondents. These commitments, coupled with the strong research demand for microdata, have led the agencies to consider various proposals for releasing public use microdata. Most proposals for public use microdata call for the development of surrogate data that disguise the original data. Thus, they involve the addition of measurement errors to the data. In this paper, we examine disclosure issues and explore alternative masking methods for generating panels of useful economic microdata that can be released to researchers. While our analysis applies to all confidential microdata, applications using the Census Bureau's Longitudinal Research Data Base (LRD) are used for illustrative purposes throughout the discussion.
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The Center for Economic Studies 1982-2007: A Brief History
October 2009
Working Paper Number:
CES-09-35
More than half a century ago, visionaries representing both the Census Bureau and the external research community laid the foundation for the Center for Economic Studies (CES) and the Research Data Center (RDC) system. They saw a clear need for a system meeting the inextricably related requirements of providing more and better information from existing Census Bureau data collections while preserving respondent confidentiality and privacy. CES opened in 1982 to house new longitudinal business databases, develop them further, and make them available to qualified researchers. CES and the RDC system evolved to meet the designers' requirements. Research at CES and the RDCs meets the commitments of the Census Bureau (and, recently, of other agencies) to preserving confidentiality while contributing paradigm-shifting fundamental research in a range of disciplines and up-to-the-minute critical tools for decision-makers.
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THE MANUFACTURING PLANT OWNERSHIP CHANGE DATABASE: ITS CONSTRUCTION AND USEFULNESS
September 1998
Working Paper Number:
CES-98-16
The Center for Economic Studies, U. S. Bureau of the Census, has constructed the "Manufacturing Plant Ownership Change Database" (OCD)using plant-level data taken from the Census Bureau's Longitudinal Research Database (LRD). The OCD contains data on all manufacturing establishments that have experienced ownership change at least once during the period 1963-1992 . This is a unique data set which, together with the LRD, can be used to conduct a variety of economic studies that were not possible before. This paper describes how the OCD was constructed and discusses the usefulness of these data for economic research.
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Documenting the Business Register and Related Economic Business Data
March 2016
Working Paper Number:
CES-16-17
The Business Register (BR) is a comprehensive database of business establishments in the United States and provides resources for the U.S. Census Bureau's economic programs for sample selection, research, and survey operations. It is maintained using information from several federal agencies including the Census Bureau, Internal Revenue Service, Bureau of Labor Statistics, and the Social Security Administration. This paper provides a detailed description of the sources and functions of the BR. An overview of the BR as a linking tool and bridge to other Census Bureau data for additional business characteristics is also given.
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CONSTRUCTION OF REGIONAL INPUT-OUTPUT TABLES FROM ESTABLISHMENT-LEVEL MICRODATA: ILLINOIS, 1982
August 1993
Working Paper Number:
CES-93-12
This paper presents a new method for use in the construction of hybrid regional input-output tables, based primarily on individual returns from the Census of Manufactures. Using this method, input- output tables can be completed at a fraction of the cost and time involved in the completion of a full survey table. Special attention is paid to secondary production, a problem often ignored by input-output analysts. A new method to handle secondary production is presented. The method reallocates the amount of secondary production and its associated inputs, on an establishment basis, based on the assumption that the input structure for any given commodity is determined not by the industry in which the commodity was produced, but by the commodity itself -- the commodity-based technology assumption. A biproportional adjustment technique is used to perform the reallocations.
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The Census of Construction Industries Database
August 1998
Working Paper Number:
CES-98-10
The Census of Construction Industries (CCI) is conducted every five years as part of the quinquennial Economic Census. The Census of Construction Industries covers all establishments with payroll that are engaged primarily in contract construction or construction on their own account for sale as defined in the Standard Industrial Classification Manual. As previously administered, the CCI is a partial census including all multi-establishments and all establishments with payroll above $480,000, one out of every five establishments with payroll between $480,000 and $120,000 and one out of eight remaining establishments. The resulting database contains for each year approximately 200,000 establishments in the building construction, heavy construction and special trade construction industrial classifications. This paper compares the content, survey procedures, and sample response of the 1982, 1987 and 1992 Censuses of Construction.
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Using 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.
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Dispersion in Dispersion: Measuring Establishment-Level Differences in Productivity
April 2018
Working Paper Number:
CES-18-25RR
We describe new experimental productivity statistics, Dispersion Statistics on Productivity (DiSP), jointly developed and published by the Bureau of Labor Statistics (BLS) and the Census Bureau. Productivity measures are critical for understanding economic performance. Official BLS productivity statistics, which are available for major sectors and detailed industries, provide information on the sources of aggregate productivity growth. A large body of research shows that within-industry variation in productivity provides important insights into productivity dynamics. This research reveals large and persistent productivity differences across businesses even within narrowly defined industries. These differences vary across industries and over time and are related to productivity-enhancing reallocation. Dispersion in productivity across businesses can provide information about the nature of competition and frictions within sectors, and about the sources of rising wage inequality across businesses. Because there were no official statistics providing this level of detail, BLS and the Census Bureau partnered to create measures of within-industry productivity dispersion. These measures complement official BLS aggregate and industry-level productivity growth statistics and thereby improve our understanding of the rich productivity dynamics in the U.S. economy. The underlying microdata for these measures are available for use by qualified researchers on approved projects in the Federal Statistical Research Data Center (FSRDC) network. These new statistics confirm the presence of large productivity differences and we hope that these new data products will encourage further research into understanding these differences.
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Large Plant Data in the LRD: Selection of a Sample for Estimation
March 1999
Working Paper Number:
CES-99-06
This paper describes preliminary work with the LRD during our tenure at the Census Bureau as participants in the ASA/NSF/Census Research Program. The objective of the work described here were two-fold. First, we wanted to examine the suitableness of these data for the calculation of plant-level productivity indexes, following procedures typically implemented with time series data. Second, we wanted to select a small number of 2-digit industry groups that would be well suited to the estimation of production functions and systems of factor share equations and factor demand forecasting equations with system-wide techniques. This description of our initial work may be useful to other researchers who are interested in the LRD for the analysis of productivity growth and/or the estimation of systems of factor equations, because the specific results reported in this memo suggest that the data are of good quality, or because the nature of the tasks undertaken provides insight into issues that arise in the analysis of longitudinal establishment data.
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