opment on Productivity Growth, in order to better identify and break down these indirect effects, BLS would prefer to use data by detailed industry, much like the line-of-business series produced by the Federal Trade Commission, determine the precise effect of federal R&D expenditures on private nonfarm productivity (U.S. Bureau of Labor Statistics, 1989).

Occupational Employment Projections

The Bureau of Labor Statistics also makes extensive use of the NSF industry data in its program of occupational employment projections. BLS staff report that more extensive use of the data would be made if the NSF data (1) provided a measure for total technology-oriented resources; (2) were further disaggregated by industry category; and (3) were a measure of output rather than intensity of effort. Despite these shortcomings, it is expected that BLS use of the NSF data will grow in the future because a competing series derived from the Occupational Employment Survey has been discontinued.

Program Management

Integration of R&D activities into the national accounts and for productivity estimates are not the only interest in R&D at the national level. Both tax credit and subsidy policies are important, and the details in each of those areas can depend on differences across industries. Currently not enough reliable data on industries are available to enable policy makers to tailor tax credits by industry. Subsidies are typically keyed to broad industry categories: the Defense Advanced Research Projects Agency targets defense applications, grants flow to specific broad areas via appropriations to the National Institutes of Health and the departments of Energy, Transportation, and Homeland Security. Even general-purpose grant programs like NSF and the National Institute of Standards and Technology’s Advanced Technology Program are organized along fairly specific technology areas.

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