How does the EU's COVID-19 economic recession impact the renewable energy of other countries? The spillover effect
Tài liệu tham khảo
Wang, 2021, Preventing a rebound in carbon intensity post-COVID-19 – lessons learned from the change in carbon intensity before and after the 2008 financial crisis, Sustain. Prod. Consum., 27, 1841, 10.1016/j.spc.2021.04.024
2021
Klemea, 2020, Minimising the present and future plastic waste, energy and environmental footprints related to COVID-19, Renew. Sustain. Energy Rev., 127
Jiang, 2021, Impacts of COVID-19 on energy demand and consumption: challenges, lessons and emerging opportunities, Appl. Energy, 285, 10.1016/j.apenergy.2021.116441
Le Quéré, 2020, Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement, Nat. Clim. Change, 10, 647, 10.1038/s41558-020-0797-x
2020
Hosseini, 2020, An outlook on the global development of renewable and sustainable energy at the time of COVID-19, Energy Res. Social Sci., 68, 10.1016/j.erss.2020.101633
Bhattacharya, 2016, The effect of renewable energy consumption on economic growth: evidence from top 38 countries, Appl. Energy, 162, 733, 10.1016/j.apenergy.2015.10.104
Nicola, 2020, The socio-economic implications of the coronavirus pandemic (COVID-19): a review, Int. J. Surg., 78, 185, 10.1016/j.ijsu.2020.04.018
Hartono, 2021, Effect of COVID-19 on energy consumption and carbon dioxide emissions in Indonesia, Sustain. Prod. Consum., 28, 391, 10.1016/j.spc.2021.06.003
Aktar, 2021, Global economic crisis, energy use, CO2 emissions, and policy roadmap amid COVID-19, Sustain. Prod. Consum., 26, 770, 10.1016/j.spc.2020.12.029
Hoang, 2021, Impacts of COVID-19 pandemic on the global energy system and the shift progress to renewable energy: opportunities, challenges, and policy implications, Energy Pol., 154, 10.1016/j.enpol.2021.112322
2021
Wang, 2022, Underestimated impact of the COVID-19 on carbon emission reduction in developing countries – a novel assessment based on scenario analysis, Environ. Res., 204, 10.1016/j.envres.2021.111990
Balsalobre-Lorente, 2021, The carbon dioxide neutralizing effect of energy innovation on international tourism in EU-5 countries under the prism of the EKC hypothesis, J. Environ. Manag., 298, 10.1016/j.jenvman.2021.113513
Ivanov, 2021, OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: managerial insights and research implications, Int. J. Prod. Econ., 232, 10.1016/j.ijpe.2020.107921
Karmaker, 2021, Improving supply chain sustainability in the context of COVID-19 pandemic in an emerging economy: exploring drivers using an integrated model, Sustain. Prod. Consum., 26, 411, 10.1016/j.spc.2020.09.019
Eroglu, 2020, 1
Leitão, 2020, The linkage between economic growth, renewable energy, tourism, CO2 emissions, and international trade: the evidence for the European union, Energies, 13, 4838, 10.3390/en13184838
Shah, 2021, Regime switching effect of COVID-19 pandemic on renewable electricity generation in Denmark, Renew. Energy, 175, 797, 10.1016/j.renene.2021.05.028
Deshwal, 2021, How will COVID-19 impact renewable energy in India? Exploring challenges, lessons and emerging opportunities, Energy Res. Social Sci., 77, 10.1016/j.erss.2021.102097
Naderipour, 2020, Effect of COVID-19 virus on reducing GHG emission and increasing energy generated by renewable energy sources: a brief study in Malaysian context, Environ. Technol. Innovat., 20
Jia, 2021, The effects and reacts of COVID-19 pandemic and international oil price on energy, economy, and environment in China, Appl. Energy, 302, 10.1016/j.apenergy.2021.117612
Leitão, 2021, The effects of corruption, renewable energy, trade and CO2 emissions, Economies, 9, 62, 10.3390/economies9020062
Leitão, 2021, The impact of renewable energy and economic complexity on carbon emissions in BRICS countries under the EKC scheme, Energies, 14, 4908, 10.3390/en14164908
Jebli, 2016, Testing environmental Kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in OECD countries, Ecol. Indicat., 60, 824, 10.1016/j.ecolind.2015.08.031
Wang, 2022, Renewable energy and economic growth revisited: the dual roles of resource dependence and anticorruption regulation, J. Clean. Prod., 337, 10.1016/j.jclepro.2022.130514
Inglesi-Lotz, 2016, The impact of renewable energy consumption to economic growth: a panel data application, Energy Econ., 53, 58, 10.1016/j.eneco.2015.01.003
Sadorsky, 2009, Renewable energy consumption and income in emerging economies, Energy Pol., 37, 4021, 10.1016/j.enpol.2009.05.003
Santiago, 2020, The relationship between public capital stock, private capital stock and economic growth in the Latin American and Caribbean countries, Int. Rev. Econ., 67, 293, 10.1007/s12232-019-00340-x
Frondel, 2010, Economic impacts from the promotion of renewable energy technologies: the German experience, Energy Pol., 38, 4048, 10.1016/j.enpol.2010.03.029
Menegaki, 2011, Growth and renewable energy in Europe: a random effect model with evidence for neutrality hypothesis, Energy Econ., 33, 257, 10.1016/j.eneco.2010.10.004
Chica-Olmo, 2020, Spatial relationship between economic growth and renewable energy consumption in 26 European countries, Energy Econ., 92, 10.1016/j.eneco.2020.104962
Eickmeier, 2011
Chudik, 2010
Samargandi, 2020, Equity market and money supply spillovers and economic growth in BRICS economies: a global vector autoregressive approach, N. Am. J. Econ. Finance, 51, 10.1016/j.najef.2019.101060
Samargandi, 2016, Private credit spillovers and economic growth: evidence from BRICS countries, J. Int. Financ. Mark. Inst. Money, 44, 56, 10.1016/j.intfin.2016.04.010
Mohaddes, 2016, Country-specific oil supply shocks and the global economy: a counterfactual analysis, Energy Econ., 59, 382, 10.1016/j.eneco.2016.08.007
Dees, 2016, Credit, asset prices and business cycles at the global level, Econ. Modell., 54, 139, 10.1016/j.econmod.2015.12.027
Bettendorf, 2019, Spillover effects of credit default risk in the euro area and the effects on the Euro: a GVAR approach, Int. J. Finance Econ., 24, 296, 10.1002/ijfe.1663
Gurara, 2013
Feldkircher, 2012
Chudik, 2016
Wang, 2022, Does urbanization redefine the environmental Kuznets curve? An empirical analysis of 134 Countries, Sustain. Cities Soc., 76, 10.1016/j.scs.2021.103382
2021
2021
2021
Li, 2021, Per-capita carbon emissions in 147 countries: the effect of economic, energy, social, and trade structural changes, Sustain. Prod. Consum., 27, 1149, 10.1016/j.spc.2021.02.031
Maddala, 1999, A comparative study of unit root tests with panel data and a new simple test, Oxf. Bull. Econ. Stat., 61, 631, 10.1111/1468-0084.0610s1631
Park, 1995, Alternative estimators and unit root tests for the autoregressive process, J. Time Anal., 16, 415, 10.1111/j.1467-9892.1995.tb00243.x
Wang, 2022, Official development assistance and carbon emissions of recipient countries: a dynamic panel threshold analysis for low- and lower-middle-income countries, Sustain. Prod. Consum., 29, 158, 10.1016/j.spc.2021.09.015
Johansen, 1992, Cointegration in partial systems and the efficiency of single-equation analysis, J. Econom., 52, 389, 10.1016/0304-4076(92)90019-N
Zhou, 2019, Investigating interior driving factors and cross-industrial linkages of carbon emission efficiency in China's construction industry: based on Super-SBM DEA and GVAR model, J. Clean. Prod., 241, 10.1016/j.jclepro.2019.118322
Umechukwu, 2022, US oil supply shocks and economies of oil-exporting African countries: a GVAR-Oil Resource Analysis, Resour. Pol., 75, 10.1016/j.resourpol.2021.102480
Ploberger, 1992
Nyblom, 1989, Testing for the constancy of parameters over time, J. Am. Stat. Assoc., 84, 223, 10.1080/01621459.1989.10478759
Quandt, 1960, Tests of the hypothesis that a linear regression system obeys two separate regimes, J. Am. Stat. Assoc., 55, 324, 10.1080/01621459.1960.10482067
Hansen, 1992, Tests for parameter instability in regressions with I(1) processes, J. Bus. Econ. Stat., 10, 321
Andrews, 1992, Optimal tests when a nuisance parameter is present only under the alternative, Econometrica, 62, 1383, 10.2307/2951753
Koop, 1996, Impulse response analysis in nonlinear multivariate models, J. Econom., 74, 119, 10.1016/0304-4076(95)01753-4
Pesaran, 1998, Generalized impulse response analysis in linear multivariate models, Econ. Lett., 58, 17, 10.1016/S0165-1765(97)00214-0
2021
Li, 2022, Germany's contribution to global carbon reduction might be underestimated – a new assessment based on scenario analysis with and without trade, Technol. Forecast. Soc. Change, 176, 10.1016/j.techfore.2021.121465
Asafu-Adjaye, 2000, The relationship between energy consumption, energy prices and economic growth: time series evidence from Asian developing countries, Energy Econ., 22, 615, 10.1016/S0140-9883(00)00050-5
Gaspar, 2017, The traditional energy-growth nexus: a comparison between sustainable development and economic growth approaches, Ecol. Indicat., 75, 286, 10.1016/j.ecolind.2016.12.048
Tsionas, 2016, Bayesian GVAR with k-endogenous dominants & input–output weights: financial and trade channels in crisis transmission for BRICs, J. Int. Financ. Mark. Inst. Money, 42, 1, 10.1016/j.intfin.2016.01.001
2021
Jing, 2020, China's renewable energy trade potential in the "Belt-and-Road" countries: a gravity model analysis, Renew. Energy, 161, 1025, 10.1016/j.renene.2020.06.134
Wang, 2021, The effects of trade openness on decoupling carbon emissions from economic growth – evidence from 182 countries, J. Clean. Prod., 279, 10.1016/j.jclepro.2020.123838
Murshed, 2020, Are trade liberalization policies aligned with renewable energy transition in low and middle income countries? An instrumental variable approach, Renew. Energy, 151, 1110, 10.1016/j.renene.2019.11.106
Wang, 2021, Integrating digital technologies and public health to fight covid-19 pandemic: key technologies, applications, challenges and outlook of digital healthcare, Int. J. Environ. Res. Publ. Health, 18, 6053, 10.3390/ijerph18116053
Chudik, 2016, Theory and practice of GVAR modelling, J. Econ. Surv., 30, 165, 10.1111/joes.12095
Assaf, 2019, Modeling and forecasting regional tourism demand using the bayesian global vector autoregressive (BGVAR) model, J. Trav. Res., 58, 383, 10.1177/0047287518759226