Working Paper #2013-025
Dynamic models of R&D, innovation and productivity: Panel data evidence for Dutch and French manufacturing
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 labour 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.
- Keywords
-
- R&D
- Innovation
- Productivity
- Panel data
- Dynamics
- Simultaneous equations
- JEL codes
-
- C33
- C34
- C35
- L60
- O31
- O32
Cite this as
APA 7th ed.Raymond, W., Mairesse, J., Mohnen, P., & Palm, F. (2013). Dynamic models of R&D, innovation and productivity: Panel data evidence for Dutch and French manufacturing (UNU-MERIT Working Paper No. 2013-025). UNU-MERIT. https://unu-merit.nl/publications/working-papers/abstract/?id=4912