Chapter 4: Sectoral Characteristics
INTRODUCTION In the last chapter we started to shed some light on the issue of local geographical spillovers between university research and high-technology innovations, taking an aggregate perspective. Our point of departure was Jaffe’s (1989: 968) often-cited finding that ‘there is only weak evidence that spillovers are facilitated by geographic coincidence of universities and research labs within the state’. We approached this issue from an explicit spatial econometric perspective and implemented the classic Griliches–Jaffe knowledge production framework for high-technology innovations in 43 US states as well as in 125 MSAs. This yielded more precise insight into the range of spatial externalities between innovation and R&D in the MSA and university research both within the MSA and in surrounding counties. In the current chapter we extend the empirical evidence in three important respects: 1. We broaden the cross-sectional basis for empirical analysis by utilizing data for four high-technology sectors. Whereas the analysis in the last chapter studied local geographic spillovers based on an aggregate of high-technology industries, the disaggregated approach followed in this chapter opens up the possibility to study likely variations across industries. As before, the data are measured at the geographic scale of the MSA. Specific measures of local geographic spillovers are developed. These measures are based on a modification of the spatial lag variable previously used. They are intended to capture research activities in concentric rings around the MSA as well as in the MSA itself. In the analysis of the sectorally disaggregated data we explicitly...
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