Such statistics, produced by BEA, are used frequently to gauge which industries are heavy users of advanced technologies. However, underlying source data are extremely sparse and very strong assumptions are required to produce these statistics (see Becker et al., 2006). More generally, the ability to disaggregate data down to the firm level has practical applications for both the measurement and interpretation of business statistics. For measurement, anomalies can be identified through scrutiny of the underlying source data. For interpretation, observed changes may reflect fundamental compositional changes in the mix of firms that are important for understanding the business cycle or secular trends in the economy.
It is possible to connect some key aggregate statistics, such as employment and payroll, to the underlying firm-level data, and recent programs at BLS and at the Census Bureau exploit this micro-macro link. However, for most key aggregate statistics, particularly those that require combining nominal values (such as nominal gross output) and prices, this is not feasible. The reason is that nominal activity measures for firms are collected by the Census Bureau, whereas nominal prices are collected by BLS; these data cannot be shared and thus they cannot be integrated at the firm level. Even with data sharing, coordination and integration of the administrative and survey data would be required to permit such drilling down from aggregate statistics. In short, for key national statistics such as real value added, real capital expenditures, or real productivity growth of a sector, it is impossible to connect back to firm-level statistics. Again, this shortcoming reflects data gaps as well as lack of data integration.
This report is primarily about the importance of measuring changes in businesses. As has been emphasized throughout, the existing system of accounts and underlying source data focus on measuring the level and cross-sectional variation in the levels of activity. The neglect of business dynamics and the role of young and small businesses in accounting for growth are related to the data gap problems discussed above. In order to capture the contribution of young and small businesses, the underlying administrative data tracking businesses must include them in a consistent and coordinated manner across the statistical agencies. Moreover, administrative data, while a powerful source of information on U.S. businesses, do not include a number of important firm characteristics that must therefore be collected by surveys. The neglect of young and small businesses by the existing system implies that a number of these key measures are not collected in a representative manner.
To explore these data gaps for measuring business dynamics, this chapter reviews the nature of data coverage of U.S. businesses past and present. Since administrative data sources can be used to track business dynamics, and in particular young and small businesses, we then turn our attention to data gaps in the business registers. However, since administrative data must