This study focuses on the impact of R&D policies in Flanders. We conduct a treatment effects analysis at the firm level to investigate possible crowdingout effects on the input side of the innovation process. Different specifications of R&D activity are considered as outcome variables in the treatment effects analysis. Applying a non-parametric matching, we conclude that subsidized firms would have invested significantly less in R&D activities, on average, if they had not received public R&D funding. Thus, crowding-out effects can be rejected in this case.

Aerts, Kris and Dirk Czarnitzki (2004), Using Innovation Survey Data to Evaluate R&D Policy: The Case of Belgium, ZEW Discussion Paper No. 04-55, Mannheim. Download


Aerts, Kris
Czarnitzki, Dirk


R&D, Subsidies, Policy Evaluation, Non-parametric matching