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Threshold Policy Effects and Directed Technical Change in Energy Innovation

This paper analyzes the effect of environmental policies on the direction of energy innovation across countries over the period 1990-2012. Our novelty is to use threshold regression models to allow for discontinuities in policy effectiveness depending on a country's relative competencies in renewable and fossil fuel technologies. We show that the dynamic incentives of environmental policies become effective just above the median level of relative competencies. In this critical second regime, market-based policies are moderately effective in promoting renewable innovation, while command-and-control policies depress fossil based innovation. Finally, market-based policies are more effective to consolidate a green comparative advantage in the last regime. We illustrate how our approach can be used for policy design in laggard countries.
- Sciences Po France
- Eni (Italy) Italy
- Eni United Kingdom
Q42, Directed Technical Change, Environmental Policies, Policy Mix, Q48, Directed technical change, Research and Development/Tech Change/Emerging Technologies, O34, Policy mix, Threshold models, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Q55, Threshold Models, Q58, Environmental policies, jel: jel:Q42, jel: jel:Q48, jel: jel:Q55, jel: jel:O34, jel: jel:Q58, ddc: ddc:330
Q42, Directed Technical Change, Environmental Policies, Policy Mix, Q48, Directed technical change, Research and Development/Tech Change/Emerging Technologies, O34, Policy mix, Threshold models, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Q55, Threshold Models, Q58, Environmental policies, jel: jel:Q42, jel: jel:Q48, jel: jel:Q55, jel: jel:O34, jel: jel:Q58, 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).6 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 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
