We examine the extent to which environmental regulation affects innovation and which policy types provide the strongest incentives to innovate. Using a local projection framework, we estimate the regulatory impact on patenting activity over a five-year horizon. As a proxy for environmental policy exposure, we estimate firm-level greenhouse gas emissions using a machine learning algorithm. At the country-level, policy tightening is largely associated with no statistically significant change in environmental technology innovation. At the firm-level, however, environmental policy tightening leads to higher innovation activity in technologies mitigating climate change, while the effect on innovation in other technologies is muted. This suggests that environmental regulation does not lead to a crowding-out of non-clean innovations. The policy type matters, as increasing the stringency of technology support policies and non-market based policies leads to increases in clean technology patenting, while we do not find a statistically significant impact of market-based policies.
Authors
European Central Bank, Benatti, Nicola, Grois, Martin, Kelly, Petra, Lopez-Garcias, Paloma
- Catalogue number
- QB-AR-24-063-EN-N
- Citation
- European Central Bank, Benatti, N., Grois, M., Kelly, P. et al., The impact of environmental regulation on clean innovation – Are there crowding out effects? , European Central Bank, 2024, https://data.europa.eu/doi/10.2866/905142
- DOI
- https://data.europa.eu/doi/10.2866/905142
- ISBN
- 978-92-899-6756-3
- ISSN
- 1725-2806
- Pages
- 57
- Published in
- Belgium
- Themes
- Scientific and technical research , Environment — Ecology
Table of Contents
- The impact of environmental regulation on clean innovation: are there crowding out effects? 1
- Abstract 2
- Non-technical summary 3
- 1 Introduction 5
- 2 Literature review 7
- 3 Hypotheses 10
- 4 Data 12
- 4.1 Evironmental policy stringency 12
- 4.2 Firm-level data 14
- 4.3 Patent data 16
- 4.4 Emission estimation 19
- 5 Empirical strategy 20
- 5.1 Identification 21
- 5.2 Local projections 22
- 6 Results 26
- 6.1 Country-level results 26
- 6.2 Firm-level results 27
- 6.3 Robustness & discussion 31
- 7 Conclusion 33
- References 35
- Appendix 39
- Descriptives 39
- Main results - regression tables 43
- Alternative specifications of the dependent variable 45
- Heterogeneity results 46
- Sector interactions 47
- Intensive/extensive margin 48
- Additional figures 50
- Acknowledgements & Imprint 57
