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Issues in Assessing the Effect of Interindustry R&D Spillovers

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  • Bruno Van Pottelsberghe De La Potterie

Abstract

This paper aims to clarify three issues concerning the weighting methodol ogy generally used to evaluate interindustry R&D spillovers. These issues concern the likely nature of the spillovers estimated through different types of supporting matrices; the similarity between input-output (IO), technology flows and technological proximity matrices; and the relevance of the assumption that a single matrix can be used for different countries. Data analyses of weighting components show that technology flows matrices are in an intermediate position between IO matrices and technological proximity matrices, but closer to the former. The various IO matrices, as well as the three technological proximity matrices, are very similar to each other. The panel data estimates of the effect of different types of interindustry R&D spillovers on industrial productivity growth in the G7 countries reject the hypotheses that a technology flows matrix can be approximated by an IO matrix and that a single IO matrix can be usedfor different countries. By transitivity, the procedure that comprises using a single technology flow for several countries is not reliable. The international comparison shows that each country benefits from different types of R&D externality. In Japan and, to a lesser extent, in the US, the rate of return to direct R&D is very high and is likely to compensate for relatively weak interindustry R&D spillover effects. In the five other industrialized countries, the reverse observation is true: strong social rates of return to R&D counterbal ance the poor performances of direct R&D.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Economic Systems Research.

Volume (Year): 9 (1997)
Issue (Month): 4 ()
Pages: 331-356

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Handle: RePEc:taf:ecsysr:v:9:y:1997:i:4:p:331-356

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Related research

Keywords: Interindustry R&D spillovers; rate of return to R&D; social return to R&D; international comparison; panel data analysis;

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