Convergence of per capita CO2 emissions across the globe: Insights via wavelet analysis. (August 2017)
- Record Type:
- Journal Article
- Title:
- Convergence of per capita CO2 emissions across the globe: Insights via wavelet analysis. (August 2017)
- Main Title:
- Convergence of per capita CO2 emissions across the globe: Insights via wavelet analysis
- Authors:
- Ahmed, Mumtaz
Khan, Atif Maqbool
Bibi, Salma
Zakaria, Muhammad - Abstract:
- Abstract: This paper examines the convergence of per capita carbon dioxide (CO2 ) emissions for 162 countries across the globe covering all income groups (high-income OECD, high-income non-OECD, middle-income and low-income countries) as categorized by the World Bank. The incidence of stochastic convergence is analysed by making use of recently developed wavelet based unit root tests. The existing studies on this subject make use of conventional unit root tests using time series and/or panel data. A serious drawback of these tests is that they analyse the stochastic behaviour of any series in time domain only whereas the stochastic process may behave differently across different frequencies as well. Thus, wavelet methods are an obvious solution as they consider frequency dimension as well in addition to time dimension when analyzing the stochastic behaviour of any data series and hence these methods encompass the conventional unit root testing methodologies by providing a clear and complete picture of the stochastic process. Our empirical findings, based on latest available time series annual data from 1960 to 2010, lend support in favor of convergence among 38 countries including 18 high income OECD countries, 2 high income non-OECD countries, 13 middle income countries and 5 low income countries while for the rest of 124 countries, the CO2 emission series is found to be non-stationary suggesting the divergence in these countries. These findings are in contrast with theAbstract: This paper examines the convergence of per capita carbon dioxide (CO2 ) emissions for 162 countries across the globe covering all income groups (high-income OECD, high-income non-OECD, middle-income and low-income countries) as categorized by the World Bank. The incidence of stochastic convergence is analysed by making use of recently developed wavelet based unit root tests. The existing studies on this subject make use of conventional unit root tests using time series and/or panel data. A serious drawback of these tests is that they analyse the stochastic behaviour of any series in time domain only whereas the stochastic process may behave differently across different frequencies as well. Thus, wavelet methods are an obvious solution as they consider frequency dimension as well in addition to time dimension when analyzing the stochastic behaviour of any data series and hence these methods encompass the conventional unit root testing methodologies by providing a clear and complete picture of the stochastic process. Our empirical findings, based on latest available time series annual data from 1960 to 2010, lend support in favor of convergence among 38 countries including 18 high income OECD countries, 2 high income non-OECD countries, 13 middle income countries and 5 low income countries while for the rest of 124 countries, the CO2 emission series is found to be non-stationary suggesting the divergence in these countries. These findings are in contrast with the most of the existing studies, which may be due to the use of wavelet based unit root tests, that are of course better alternatives. Some policy implications evolve from the empirical findings. … (more)
- Is Part Of:
- Renewable & sustainable energy reviews. Volume 75(2017)
- Journal:
- Renewable & sustainable energy reviews
- Issue:
- Volume 75(2017)
- Issue Display:
- Volume 75, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 75
- Issue:
- 2017
- Issue Sort Value:
- 2017-0075-2017-0000
- Page Start:
- 86
- Page End:
- 97
- Publication Date:
- 2017-08
- Subjects:
- C22: Q54
CO2 emissions -- Wavelet unit root test -- Convergence
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13640321 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-and-sustainable-energy-reviews ↗ - DOI:
- 10.1016/j.rser.2016.10.053 ↗
- Languages:
- English
- ISSNs:
- 1364-0321
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.186000
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British Library HMNTS - ELD Digital store - Ingest File:
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