The DOI matches its Crossref record; 91 of the 91 references it cites were found in a registry or an index.
The effects of environmental innovations on CO2 emissions: Empirical evidence from Europe
Open accessAbstract
Abstract Environmental innovations are key enablers of transition towards greener economies. Despite their importance, empirical studies examining the effect of green technologies on CO2 emissions are still limited. Using an autoregressive distributed-lag model (ARDL), we analyze the impact of environmental innovations, the consumption of renewable energies, GDP per capita, and degree of economic openness on CO2 emissions for 15 European countries over 23 years. Our results indicate that, in the long-term, environmental innovations tend to lower CO2 emissions, whereas in the short-term the observed effect is the opposite, suggesting the existence of a rebound effect. This study recommends introducing new policies that combine tools of environmental economics with those of ecological economy to integrate economic incentives with regulatory changes and encourage individuals to consume differently by favouring products and/or services with a less negative impact on the environment.
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Cites
Bounds testing approaches to the analysis of level relationships
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001) · Journal of Applied Econometrics · doi:10.1002/jae.616 · Cited by 20,385
Another look at the instrumental variable estimation of error-components models
Arellano, M., & Bover, O. (1995) · Journal of Econometrics · doi:10.1016/0304-4076(94)01642-d · Cited by 19,880
Testing for unit roots in heterogeneous panels
Im, K. S., Pesaran, M. H., & Shin, Y. (2003) · Journal of Econometrics · doi:10.1016/s0304-4076(03)00092-7 · Cited by 15,435
Unit root tests in panel data: asymptotic and finite-sample properties
Levin, A., Lin, C.-F., & James Chu, C.-S. (2002) · Journal of Econometrics · doi:10.1016/s0304-4076(01)00098-7 · Cited by 12,849
A simple panel unit root test in the presence of cross‐section dependence
Pesaran, M. H. (2007) · Journal of Applied Econometrics · doi:10.1002/jae.951 · Cited by 12,787
Economic Growth and Income Inequality
Kuznets, S. (2019) · The Gap between Rich and Poor · doi:10.4324/9780429311208-4 · Cited by 8,064
Environmental Impacts of a North American Free Trade Agreement
Grossman, G., & Krueger, A. (1991) · National Bureau of Economic Research · doi:10.3386/w3914 · Cited by 7,595
Pooled Mean Group Estimation of Dynamic Heterogeneous Panels
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10474156 · Cited by 6,683
Pedroni, P. (2004) · Econometric Theory · doi:10.1017/s0266466604203073 · Cited by 6,669
Patent Statistics as Economic Indicators: A Survey
Griliches, Z. (1990) · National Bureau of Economic Research · doi:10.3386/w3301 · Cited by 5,828
Cited by
Ahmad, M., & Wu, Y. (2022) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.113980 · Cited by 298
Technological Progress and Climate Change: Evidence from the Agricultural Sector
Da Mata, D., Dotta, M., & Lobo, T. (2023) · doi:10.2139/ssrn.4358828 · Cited by 4
Cardinal Masters in Public Administration, L. U. T., & Zulqarnain, F. (2026) · International Journal of Scientific Interdisciplinary Research · doi:10.63125/28gejw48 · Cited by 3
Metadata
- Authors
- Mongo, M., Belaïd, F., & Ramdani, B.
- Venue
- Environmental Science & Policy
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 118
- Pages
- 1-9
- ISSN
- 1462-9011 (ISSN-L)
- OpenAlex
- W3122262261
- Cited by
- 334
- References
- 91
- FWCI
- 44.27
- Type
- journal article
- Language
- en
- Open access
- bronze
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