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Managerial Tenure, Business Age And Small Business Dynamics
September 1992
Working Paper Number:
CES-92-11
This paper studies a Census Bureau survey of the small business sector that contains information on business age, business size and other proxies for business quality, information, typically available on business data sets, as well as proxies for the quality of the manager of each business, information that is not common to such data sets. One of the key proxies for managerial quality is the length of time the manager has been running the business, that is, managerial tenure. With proxies for both the underlying quality of each business and for the quality of the manager running the business, we are able to begin separating the influences of the manager from that of the underlying business on such factors as business discontinuance and business transfer. An example of the questions we explore is: Holding business quality fixed, what is the impact of the manager on the probability of business discontinuance? Regarding this question, we find that managers have a large impact on the course of their businesses, in particular, among businesses of the same age, managerial tenure has a significant impact on the probability of business discontinuance and transfer.
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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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Multiple Classification Systems For Economic Data: Can A Thousand Flowers Bloom? And Should They?
December 1991
Working Paper Number:
CES-91-08
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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Published 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.
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The Classification of Manufacturing Industries: an Input-Based Clustering of Activity
August 1990
Working Paper Number:
CES-90-07
The classification and aggregation of manufacturing data is vital for the analysis and reporting of economic activity. Most organizations and researchers use the Standard Industrial Classification (SIC) system for this purpose. This is, however, not the only option. Our paper examines an alternative classification based on clustering activity using production technologies. While this approach yields results which are similar to the SIC, there are important differences between the two classifications in terms of the specific industrial categories and the amount of information lost through aggregation.
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An Analysis of Small Business Size and Rate of Discontinuance
January 1990
Working Paper Number:
CES-90-02
This study investigates small business failure rates in relation to several measures of firm size. Utilizing the new Characteristics of Business Owners ( CBO ) data base, a nationwide sample of firms is utilized that is representative of the small business universe. One subset--small business employers--is shown to have relatively low rates of failure, while another group--very small firms with no employees--exhibits relatively high rates of business discontinuance. The finding that the probability of firm failure is strongly (inversely) related to firm size is shown to hold up as well when the age of the business is controlled for.
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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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USING LINKED CENSUS R&D-LRD DATA TO ANALYZE THE EFFECT OF R&D INVESTMENT ON TOTAL FACTOR PRODUCTIVITY GROWTH
January 1989
Working Paper Number:
CES-89-02
Previous studies have demonstrated that productivity growth is positively correlated with the intensity of R&D investment. However, existing studies of this relationship at the micro (firm or line of business) level have been subject to some important limitations. The most serious of these has been an inability to adequately control for the diversified activities of corporations. This study makes use of linked Census R&D - LRD data, which provides comprehensive information on each firms' operations at the 4-digit SIC level. A marked improvement in explaining the association between R&D and TFP occurs when we make appropriate use of the data by firm by industry. Significant relationships between the intensities of investment in total, basic, and company-funded R&D, and TFP growth are confirmed.
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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 Longitudinal Research Database (LRD): Status And Research Possibilities
July 1988
Working Paper Number:
CES-88-02
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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