This paper employs individual firm data in order to check the existence of industry-spatial effects alongside other microeconomic determinants of R&D investment. Spatial proximity is defined by a measure of firms’ industry distance based on trade intensity between sectors. The spatial model specified here refers to the combined spatial-autoregressive model with autoregressive disturbances. In modelling the outcome for each location as dependent on a weighted average of the outcomes of other locations, outcomes are determined simultaneously. The results of the spatial estimation suggest that in their R&D decision firms benefit from spillovers originating from neighbouring industries.
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Oliviero A. Carboni (2013) studied this question.
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