This paper considers why the determinants of the inter- and intra-industry variance in R&D intensity in U.S. manufacturing differ markedly even though response parameters are similar across industries. A similar aggregation effect is noted by Grunfeld and Griliches (1960), and this paper gives that effect operational content in terms of grouped data estimation procedures. Observationally equivalent aggregation results can be generated by errors in variables models (see Aigner and Goldfeld [1974]).A later section considers specifications which identify the empirical importance of both these problems. Finally, a summary of the empirical results on the determinants of R&D intensity is provided.
*Published:
Pakes, Ariel. (1) "On the Asympotic Bias of Wald-Type Estimates of a Straight Line When Both Variables are Subject to Error." Inter. Econ. Rev. June 82, pp. 491-497. (2) "On Group Effects & Errors in Variables in Aggregation ." Rev. of Econ. & Statistics. February 1983, pp. 168-173.
You may purchase this paper on-line in .pdf format
from SSRN.com ($5) for electronic delivery.
Machine-readable bibliographic record -
MARC,
RIS,
BibTeX
