The principle that the statistical system should provide flexibility-- possibilities for generating multiple groupings of data to satisfy multiple objectives--if it is to satisfy users is universally accepted. Yet in practice, this goal has not been achieved. This paper discusses the feasibility of providing flexibility in the statistical system to accommodate multiple uses of the industrial data now primarily examined within the Standard Industrial Classification (SIC) system. In one sense, the question of feasibility is almost trivial. With today's computer technology, vast amounts of data can be manipulated and stored at very low cost. Reconfigurations of the basic data are very inexpensive compared to the cost of collecting the data. Flexibility in the statistical system implies more than the technical ability to regroup data. It requires that the basic data are sufficiently detailed to support user needs and are processed and maintained in a fashion that makes the use of a variety of aggregation rules possible. For this to happen, statistical agencies must recognize the need for high quality microdata and build this into their planning processes. Agencies need to view their missions from a multiple use perspective and move away from use of a primary reporting and collection vehicle. Although the categories used to report data must be flexible, practical considerations dictate that data collection proceed within a fixed classification system. It is simply too expensive for both respondents and statistical agencies to process survey responses in the absence of standardized forms, data entry programs, etc. I argue for a basic classification centered on commodities--products, services, raw materials and labor inputs--as the focus of data collection. The idea is to make the principle variables of interest--the commodities--the vehicle for the collection and processing of the data. For completeness, the basic classification should include labor usage through some form of occupational classification. In most economic surveys at the Census Bureau, the reporting unit and the classified unit have been the establishment. But there is no need for this to be so. The basic principle to be followed in data collection is that the data should be collected in the most efficient way--efficiency being defined jointly in terms of statistical agency collection costs and respondent burdens.
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The Importance of Establishment Data in Economic Research
August 1993
Working Paper Number:
CES-93-10
The importance and usefulness of establishment microdata for economic research and policy analysis is outlined and contrasted with traditional products of statistical agencies -- aggregate cross-section tabulations. It is argued that statistical agencies must begin to seriously rethink the way they view establishment data products.
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Longitudinal Economic Data At The Census Bureau: A New Database Yields Fresh Insight On Some Old Issues
January 1990
Working Paper Number:
CES-90-01
This paper has two goals. First, it illustrates the importance of panel data with examples taken from research in progress using the U.S. Census Bureau's Longitudinal Research Database ( LRD ). Although the LRD is not the result of a "true" longitudinal survey, it provides both balanced and unbalanced panel data sets for establishments, firms, and lines of business. The second goal is to integrate the results of recent research with the LRD and to draw conclusions about the importance of longitudinal microdata for econometric research and time series analysis. The advantages of panel data arise from both the micro and time series aspects of the observations. This also leads us to consider why panel data are necessary to understand and interpret the time series behavior of aggregate statistics produced in cross-section establishment surveys and censuses. We find that typical homogeneity assumptions are likely to be inappropriate in a wide variety of applications. In particular, the industry in which an establishment is located, the ownership of the establishment, and the existence of the establishment (births and deaths) are endogenous variables that cannot simply be taken as time invariant fixed effects in econometric modeling.
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Analytic Use Of Economic Microdata; A Model For Researcher Access With Confidentiality Protection
August 1992
Working Paper Number:
CES-92-08
A primary responsibility of the Center for Economic Studies (CES) of the U.S. Bureau of the Census is to facilitate researcher access to confidential economic microdata files. Benefits from this program accrue not only to policy makers--there is a growing awareness of the importance of microdata for analyzing both the descriptive and welfare implications of regulatory and environmental changes--but also and importantly to the statistical agencies themselves. In fact, there is substantial recent literature arguing for the proposition that the largest single improvement that the U.S. statistical system could make is to improve its analytic capabilities. In this paper I briefly discuss these benefits to greater access for analytical work and ways to achieve them. Due to the nature of business data, public use databases and masking technologies are not available as vehicles for releasing useful microdata files. I conclude that a combination of outside and inside research programs, carefully coordinated and integrated is the best model for ensuring that statistical agencies reap the gains from analytic data users. For the United States, at least, this is fortuitous with respect to justifying access since any direct research with confidential data by outsiders must have a "statistical purpose". Until the advent of CES, it was virtually impossible for researchers to work with the economic microdata collected by the various economic censuses. While the CES program is quite large, as it now stands, researchers, or their representatives, must come to the Census Bureau in Washington, D.C. to access the data. The success of the program has led to increasing demands for data access in facilities outside of the Washington, D.C. area. Two options are considered: 1) Establish Census Bureau facilities in various universities or similar nonprofit research facilities and 2) Develop CES regional operations in existing Census Bureau regional offices.
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Unlocking the Information in Integrated Social Data
May 2002
Working Paper Number:
tp-2002-21
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Price Dispersion In U.S. Manufacturing: Implications For The Aggregation Of Products And Firms
March 1992
Working Paper Number:
CES-92-03
This paper addresses the question of whether products in the U.S. Manufacturing sector sell at a single (common) price, or whether prices vary across producers. Price dispersion is interesting for at least two reasons. First, if output prices vary across producers, standard methods of using industry price deflators lead to errors in measuring real output at the industry, firm, and establishment level which may bias estimates of the production function and productivity growth. Second, price dispersion suggests product heterogeneity which, if consumers do not have identical preferences, could lead to market segmentation and price in excess of marginal cost, thus making the current (competitive) characterization of the Manufacturing sector inappropriate and invalidating many empirical studies. In the course of examining these issues, the paper develops a robust measure of price dispersion as well as new quantitative methods for testing whether observed price differences are the result of differences in product quality. Our results indicate that price dispersion is widespread throughout manufacturing and that for at least one industry, Hydraulic Cement, it is not the result of differences in product quality.
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The Extent and Nature of Establishment Level Diversification in Sixteen U.S. Manufacturing Industries
August 1990
Working Paper Number:
CES-90-08
This paper examines the heterogeneity of establishments in sixteen manufacturing industries. Basic statistical measures are used to decompose product diversification at the establishment level into industry, firm, and establishment effects. The industry effect is the weakest; nearly all the observed heterogeneity is establishment specific. Product diversification at the establishment level is idiosyncratic to the firm. Establishments within a firm exhibit a significant degree of homogeneity, although the grouping of products differ across firms. With few exceptions, economies of scope and scale in production appear to play a minor role in the establishment's mix of outputs.
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Evidence on IO Technology Assumptions From the Longitudinal Research Database
May 1993
Working Paper Number:
CES-93-08
This paper investigates whether a popular IO technology assumption, the commodity technology model, is appropriate for specific United States manufacturing industries, using data on product composition and use of intermediates by individual plants from the Census Longitudinal Research Database. Extant empirical research has suggested the rejection of this model, owing to the implication of aggregate data that negative inputs are required to make particular goods. The plant-level data explored here suggest that much of the rejection of the commodity technology model from aggregative data was spurious; problematic entries in industry-level IO tables generally have a very low Census content. However, among the other industries for which Census data on specified materials use is available, there is a sound statistical basis for rejecting the commodity technology model in about one-third of the cases: a novel econometric test demonstrates a fundamental heterogeneity of materials use among plants that only produce the primary products of the industry.
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Price Dispersion in U.S. Manufacturing
October 1989
Working Paper Number:
CES-89-07
This paper addresses the question of whether products in the U.S. Manufacturing sector sell at a single (common) price, or whether prices vary across producers. The question of price dispersion is important for two reasons. First, if prices vary across producers, the standard method of using industry price deflators leads to errors in measuring real output at the firm or establishment level. These errors in turn lead to biased estimates of the production function and productivity growth equation as shown in Abbott (1988). Second, if prices vary across producers, it suggests that producers do not take prices as given but use price as a competitive variable. This has several implications for how economists model competitive behavior.
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Primary Versus Secondary Production Techniques in U.S. Manufacturing
October 1994
Working Paper Number:
CES-94-12
In this paper we discuss and analyze a classical economic puzzle: whether differences in factor intensities reflect patterns of specialization or the co-existence of alternative techniques to produce output. We use observations on a large cross-section of U.S. manufacturing plants from the Census of Manufactures, including those that make goods primary to other industries, to study differences in production techniques. We find that in most cases material requirements do not depend on whether goods are made as primary products or as secondary products, which suggests that differences in factor intensities usually reflect patterns of specialization. A few cases where secondary production techniques do differ notably are discussed in more detail. However, overall the regression results support the neoclassical assumption that a single, best-practice technique is chosen for making each product.
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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.
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