Dynamic models of R&D, innovation and productivity : panel data evidence for Dutch and French manufacturing

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Abstract

This paper introduces dynamics in the R&D to innovation and innovation to productivity relationships, which have mostly been estimated on cross-sectional data. It considers four nonlinear dynamic simultaneous equations models that include individual effects and idiosyncratic errors correlated across equations and that differ in the way innovation enters the conditional mean of labor productivity: through an observed binary indicator, an observed intensity variable or through the continuous latent variables that correspond to the observed occurrence or intensity. It estimates these models by full information maximum likelihood using two
unbalanced panels of Dutch and French manufacturing firms from three waves of the Community Innovation Survey. The results provide evidence of robust unidirectional causality from innovation to productivity and of stronger persistence in productivity than in innovation.
Original languageEnglish
Place of PublicationMaastricht
PublisherUNU-MERIT, Maastricht Economic and Social Research and Training Centre on Innovation and Technology
Number of pages33
Publication statusPublished - 1 Jan 2013

Publication series

SeriesUNU-MERIT Working Papers
Number025

Cite this

Raymond, W., Mairesse, J., Mohnen, P., & Palm, F. C. (2013). Dynamic models of R&D, innovation and productivity : panel data evidence for Dutch and French manufacturing. UNU-MERIT, Maastricht Economic and Social Research and Training Centre on Innovation and Technology. UNU-MERIT Working Papers, No. 025