The longitudinal research database: status and research possibilities

Survey of Current Business, Nov, 1988 by Robert H. McGuckin, George A. Pascoe, Jr.

The Longitudinal Research Database: Status and Research Possibilities

Introduction

THE Longitudinal Research Database (LRD) is a large micro database(1) of establishment-level data constructed by pooling information from the Census of Manufactures (CM) and the Annual Survey of Manufactures (ASM). It is housed within the Census Bureau at the Center for Economic Studies (the Center), which was established in 1982 to oversee the development of this database, to use the data to improve future Census Bureau data collection and reports, and to make the data available to outside users.

The construction of the database was itself a major achievement. It contains linked data from 5 censuses and 11 annual surveys. There are 2,311,794 individual establishment year records currently in the file, and it is updated as new data become available. Thus, the LRD is one of the most ambitious and comprehensive data sets available for the study of manufacturing, and it promises to provide an exciting and stimulating research environment for many years. At the same time, the sheer magnitude of the database, coupled with its complexity, means that researchers must take the time to fully understand the structure of the database before embarking on research. This paper outlines the development of the database, its structure and current status, and the possibilities for its use in economic research.

The discussion is organized into four sections. We begin with some general observations on the characteristics that researchers desire in a database. In particular, we focus on the need for micro-level detail to adequately examine many economic issues. These observations provide the framework for the more specific remarks in the remainder of the paper. These remarks include a brief section outlining the origins of the LRD. The main portion of the paper details the major components of the LRD, the kinds of information included in the database, and the related data sets available at the Center. Throughout, we try to describe the research conducted at the Center as a way of providing concrete examples of the kinds of activity the LRD will support. We then briefly discuss access to the database and conclude with some observations intended to provide an overall assessment of the usefulness and flexibility of the LRD.

The Need For Detail in a Database

Economic analysis has a profound influence on data development. Researchers often approach particular problems with a well-defined theory, sophisticated econometric or statistical techniques, and data that are inadequate or inappropriate for testing the theory. This situation provides the incentive for developing new data. The theory provides guidance and direction to the data development strategy. Unfortunately, the need for better data often occurs when an answer to a question is required in a timeframe too short to develop a new data set. Even if there is time, the costs of developing new data are often prohibitive. In these instances, the available data influence the theory and the econometric procedures used. Thus, data development also influences economic analysis.

In most research on production functions and total factor productivity, data availability dictates the estimation procedures. The absence of detailed data for specific producing units often causes researchers to use aggregate data in econometric specifications. Several recent papers using the LRD suggest the existence of substantial aggregation bias in estimates of productivity relationships.(2) Moreover, there are many productivity-related questions that simply cannot be examined with aggregate data. John Solow (1987) argues convincingly that it is impossible to determine whether energy is a complement or substitute for other inputs using aggregate data (for example, two-digit manufacturing industries).

As an example of the need for detailed data, consider the problem of the measurement of trade flows and the technological leadership of U.S. industry. Examinations of this problem have focused on the high-tech trade balance defined in terms of trade flows measured at the three-digit industry level. This level of aggregation was chosen because high-tech industries are distinguished from low-tech industries solely on the basis of research and development (R&D) to sales ratios. Use of this procedure means that low-tech products are often included in the high-tech industry category. For instance, the office and computing equipment industry (Standard Industrial Classification 357) includes high-tech products, such as electronic computers and peripheral computing equipment. It also includes low-tech products, such as adding machines and coin counters. Conclusions based on such aggregate numbers may be misleading.(3)

These examples show that the need for more detailed data is a central feature of economic research. This need cuts across all applied fields of economics. The LRD is a longitudinal micro database that consists of individual establishment (plant) data and that provides a substantial source of detailed data.