Latviešu valodas versija nav pieejama
Petra Kelly
- 17 June 2024
- WORKING PAPER SERIES - No. 2946Details
- Abstract
- 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.
- JEL Code
- O44 : Economic Development, Technological Change, and Growth→Economic Growth and Aggregate Productivity→Environment and Growth
Q52 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Pollution Control Adoption Costs, Distributional Effects, Employment Effects
Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy
- 23 May 2023
- WORKING PAPER SERIES - No. 2820Details
- Abstract
- This paper analyses the impact of changes in environmental regulations on productivity growth at country- and firm-level. We exploit several data sources and the environmen-tal policy stringency index, to evaluate the Porter hypothesis, according to which firms’ productivity can benefit from more stringent environmental policies. By using panel local projections, we estimate the regulatory impact over a five-year horizon. The identification of causal impacts of regulatory changes is achieved by the estimation of firms’ CO2 emissions via a machine learning algorithm. At country- and firm-level, policy tightening affects high-polluters’ productivity negatively and stronger than their less-polluting peers. However, among high-polluting firms, large ones experience positive total factor productivity growth due to easier access to finance and greater innovativeness. Hence, we do not find support for the Porter hypothesis in general. However for technology support policies and firms with the required resources, policy tightening can enhance productivity.
- JEL Code
- O44 : Economic Development, Technological Change, and Growth→Economic Growth and Aggregate Productivity→Environment and Growth
Q52 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Pollution Control Adoption Costs, Distributional Effects, Employment Effects
Q58 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Government Policy