Articles | Volume 3, issue 2
https://doi.org/10.5194/esd-3-173-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/esd-3-173-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
21 Nov 2012
Research article |
| 21 Nov 2012
Polynomial cointegration tests of anthropogenic impact on global warming
M. Beenstock
Department of Economics, the Hebrew University of Jerusalem, Mount Scopus Campus, Jerusalem, Israel
Y. Reingewertz
Department of Economics, the George Washington University, 2115 G St, Washington DC, USA
N. Paldor
Fredy and Nadine Herrmann Institute of Earth Sciences, the Hebrew University of Jerusalem, Edmond J. Safra Campus, Givat Ram, Jerusalem, Israel
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- Problems with Statistical Tests of Atmospheric Greenhouse Gas Concentration Data Derived from Ice Cores J. McCown https://doi.org/10.2139/ssrn.3304901
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- Robust cointegration testing in the presence of weak trends, with an application to the human origin of global warming G. Chevillon https://doi.org/10.1080/07474938.2014.977080
- Climate change, state capacity and uneven growth: A disaggregated analysis of India N. Kumar & D. Maiti https://doi.org/10.1016/j.econmod.2025.107311
- Econometric modelling of climate systems: The equivalence of energy balance models and cointegrated vector autoregressions F. Pretis https://doi.org/10.1016/j.jeconom.2019.05.013
- A Multicointegration Model of Global Climate Change S. Bruns et al. https://doi.org/10.2139/ssrn.3117015
- Detection of type of trends in surface air temperature in China X. Li et al. https://doi.org/10.1016/j.jhydrol.2021.126061
- Climate Econometrics: An Overview J. Castle & D. Hendry https://doi.org/10.1561/0800000037
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- Could detection and attribution of climate change trends be spurious regression? D. Cummins et al. https://doi.org/10.1007/s00382-022-06242-z
- Comparing ecological memory effects of the bimodal radial growth in the Qinling Mountains and Mediterranean forests H. Yan et al. https://doi.org/10.1016/j.fecs.2025.100402
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- Sea level oscillations in Japan and China since the start of the 20th century and consequences for coastal management - Part 1: Japan A. Parker https://doi.org/10.1016/j.ocecoaman.2018.12.031
- Anthropogenic CO 2 warming challenged by 60-year cycle F. Gervais https://doi.org/10.1016/j.earscirev.2016.02.005
31 citations as recorded by crossref.
- Granger causality from changes in level of atmospheric CO2 to global surface temperature and the El Niño–Southern Oscillation, and a candidate mechanism in global photosynthesis L. Leggett & D. Ball https://doi.org/10.5194/acp-15-11571-2015
- Problems with Statistical Tests of Atmospheric Greenhouse Gas Concentration Data Derived from Ice Cores J. McCown https://doi.org/10.2139/ssrn.3304901
- Cointegration in Panel, Spatial and Spatio‐Temporal Models: Some Recent Advances and Applications D. Tjøstheim https://doi.org/10.1111/obes.70059
- A realistic expectation of sea level rise in the Mexican Caribbean A. Boretti https://doi.org/10.1016/j.joes.2019.06.003
- Latitudinal variability of the dynamic linkage between temperature and atmospheric carbon dioxide concentrations U. Triacca & F. Di Iorio https://doi.org/10.1007/s00704-018-2535-0
- Sea level patterns around Korea and Japan A. Boretti https://doi.org/10.1016/j.rsma.2024.103720
- Robust cointegration testing in the presence of weak trends, with an application to the human origin of global warming G. Chevillon https://doi.org/10.1080/07474938.2014.977080
- Climate change, state capacity and uneven growth: A disaggregated analysis of India N. Kumar & D. Maiti https://doi.org/10.1016/j.econmod.2025.107311
- Econometric modelling of climate systems: The equivalence of energy balance models and cointegrated vector autoregressions F. Pretis https://doi.org/10.1016/j.jeconom.2019.05.013
- A Multicointegration Model of Global Climate Change S. Bruns et al. https://doi.org/10.2139/ssrn.3117015
- Detection of type of trends in surface air temperature in China X. Li et al. https://doi.org/10.1016/j.jhydrol.2021.126061
- Climate Econometrics: An Overview J. Castle & D. Hendry https://doi.org/10.1561/0800000037
- A panel data study of causality links between CO2 concentration and temperature M. Amendola et al. https://doi.org/10.1088/1748-9326/addad9
- A multicointegration model of global climate change S. Bruns et al. https://doi.org/10.1016/j.jeconom.2019.05.010
- Relative sea-level rise and land subsidence in Oceania from tide gauge and satellite GPS A. Boretti https://doi.org/10.1515/nleng-2020-0007
- Anthropogenic and natural causes of climate change D. Stern & R. Kaufmann https://doi.org/10.1007/s10584-013-1007-x
- Quantifying Time-Lagged Vegetation Responses to Hydroclimatic Factors in Dam-Influenced Arid Regions Using VAR Modeling and Remote Sensing R. Almalki et al. https://doi.org/10.1007/s00267-025-02328-6
- Pacific Sea Levels Rising Very Slowly and Not Accelerating A. Parker & C. Ollier https://doi.org/10.2478/quageo-2019-0007
- Absolute and relative sea-level rise in the New York City area by measurements from tide gauges and satellite global positioning system A. Boretti https://doi.org/10.1016/j.joes.2020.05.001
- Nonlinear absolute sea-level patterns in the long-term-trend tide gauges of the East Coast of North America A. Boretti https://doi.org/10.1515/nleng-2021-0001
- More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models D. Stephenson et al. https://doi.org/10.3390/su151612142
- Could detection and attribution of climate change trends be spurious regression? D. Cummins et al. https://doi.org/10.1007/s00382-022-06242-z
- Comparing ecological memory effects of the bimodal radial growth in the Qinling Mountains and Mediterranean forests H. Yan et al. https://doi.org/10.1016/j.fecs.2025.100402
- Comment on "Polynomial cointegration tests of anthropogenic impact on global warming" by Beenstock et al. (2012) – some hazards in econometric modelling of climate change F. Pretis & D. Hendry https://doi.org/10.5194/esd-4-375-2013
- Testing the historic tracking of climate models M. Beenstock et al. https://doi.org/10.1016/j.ijforecast.2016.02.010
- The pattern of sea-level rise across the North Atlantic from long-term-trend tide gauges A. Boretti https://doi.org/10.1016/j.ocecoaman.2020.105309
- Quantifying the lagged effects of climate factors on vegetation growth in 32 major cities of China W. Tang et al. https://doi.org/10.1016/j.ecolind.2021.108290
- Anthropogenic greenhouse gas concentrations and global temperature: a smooth transition analysis N. Michail et al. https://doi.org/10.1007/s42452-019-0670-6
- Nonlinear absolute sea-level patterns in the long-term-trend tide gauges of the West Coast of North America A. Boretti https://doi.org/10.1515/nleng-2020-0024
- Sea level oscillations in Japan and China since the start of the 20th century and consequences for coastal management - Part 1: Japan A. Parker https://doi.org/10.1016/j.ocecoaman.2018.12.031
- Anthropogenic CO 2 warming challenged by 60-year cycle F. Gervais https://doi.org/10.1016/j.earscirev.2016.02.005
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