
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Effects of policies on patenting in wind-power technologies

Abstract This paper explores the effects of policies and other factors driving innovation in wind power technologies in twelve OECD countries over more than two decades. Patent counts are used as an indicator for innovation. The factors considered are generally derived from the systems of innovation literature. Count data econometric model were used for the estimations. The suggest that patenting in wind power technology is positively related to public R&D in wind power (reflecting supply-side policy), the stock of wind capacity (reflecting learning effects), the number of patents per capita (reflecting a country's innovative capacity), and the share of Green party voters (reflecting the legitimacy of the technology). In particular, the presence of production or capacity targets for wind power or renewable energy sources and a stable policy environment (reflecting policy process) appear to be favourable for patenting wind power technologies. These results are robust to various model specifications, distributional assumptions, and alternative classifications of wind power technologies in the patent search.
- Virginia Tech United States
- Fraunhofer Institute for Systems and Innovation Research Germany
- Fraunhofer Society Germany
- Grenoble School of Management France
count data econometrics, demand-side regulation, supply-side regulation, wind power, patent analysis, innovation, ddc: ddc:330
count data econometrics, demand-side regulation, supply-side regulation, wind power, patent analysis, innovation, ddc: ddc:330
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).85 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
