Natural resources,green energy,and sustainable development are closely linked with concepts that carry mutual goals to endorse social equity,economic prosperity,and ecological stability while curtailing the harmful in...Natural resources,green energy,and sustainable development are closely linked with concepts that carry mutual goals to endorse social equity,economic prosperity,and ecological stability while curtailing the harmful influence on the globe.However,the recognition of the Sustainable Development Goals(SDG-7,SDG-13)is closely entangled with digital economy.In this pursuit,this study scrutinizes the effect of dig-italization,renewable energy,and natural resources on the ecological footprint in China from 1990Q1-2022Q4.The empirical analyses are carried out by employing the Quantile-on-Quantile regression,and cross-quantile and partial cross-quantile correlation approaches to inspect the tail dependence of model parameters.The empirical outcomes highlight how China’s environmental quality is influenced by exoge-nous variables,including digitalization index,renewable energy consumption,and natural resources.Digitalization has adverse impact on the ecological footprint in lower quantiles,while insignificant in higher quantiles.Moreover,a strong adverse association exists between ecological footprint and renew-able energy,which syndicate all the quantiles of renewable energy with linking over lower to middle quantiles and weak in higher quantiles of ecological footprint.Besides,the estimated analysis discloses nuanced dependencies across various quantiles.Similarly,it can be found that the strong negative effect of natural resources on ecological footprint in initial quantiles,moderate in middle quantiles,and less positive effect in higher quantiles.By explaining these dynamics,the current study offers valuable intu-itions designed at controlling China toward its dual-carbon target and encouraging the development of a sustainable digital and green economy and thereby,continuing towards achieving SDG-7,and SDG-13 objectives.展开更多
The link between crude oil price and stock returns of the Group of Seven(G7)countries(Canada,France,Germany,Italy,Japan,the United Kingdom,and the United States)was analyzed in this study using monthly data from Janua...The link between crude oil price and stock returns of the Group of Seven(G7)countries(Canada,France,Germany,Italy,Japan,the United Kingdom,and the United States)was analyzed in this study using monthly data from January 1999 to March 2020.We adopt a similar approach to Kilian(Am Econ Rev 99(3):1053–1069,2009)and construct a structural vector autoregression framework to decompose crude oil price shocks into oil supply shock,oil aggregate demand shock,and oil-specific demand shock.We then explore the distinct effects of different kinds of oil price shocks from various sources.Based on the decomposed oil price shocks,we apply the connectedness approach and QQ regression to find time-varying co-movements and tail dependence between oil price shocks and G7 stock returns.There is no general correlation between the decomposed oil prices and stock returns in these countries.The effects of oil price shocks on stock returns across different stock market conditions appear to be heterogeneous.Oil supply shock appears to be a net transmitter of spillover effects for all G7 countries within the sample period.展开更多
In this paper,we propose an easily implementable combination forecast method to examine whether systemic risk can predict macroeconomic activity.Our method uses various weighting schemes to combine common individual s...In this paper,we propose an easily implementable combination forecast method to examine whether systemic risk can predict macroeconomic activity.Our method uses various weighting schemes to combine common individual systemic risk measures.Empirical results demonstrate that our novel forecasting strategy provides better and more stable out-of-sample performance than a set of established methods.Furthermore,the forecast combination puzzle identified by Stock and Watson(2004)is also present in systemic risk.Our findings further reveal that institution-specific risk measures,such as MES and△CoVaR_(d),consistently provide reliable information to inform predictions of future macroeconomic downturns across most regions.The strength and direction of those asymmetric relationships are closely associated with the risk levels(i.e.,quantiles of independent variables)of systemic risk indicators.展开更多
Natural resources represent the base of our living and the entire economic activity.Their depletion is a major challenge for the economic development of both developed and developing economies.Their effi-cient use is ...Natural resources represent the base of our living and the entire economic activity.Their depletion is a major challenge for the economic development of both developed and developing economies.Their effi-cient use is an indispensable requirement and must be the aim of the public policies designed by the authorities worldwide.In this research,we have investigated the impact of the natural resources rent on the economic growth in some major wealthy economies of the world(P5+1 countries namely:US,UK,France,China,Russia,and Germany).We have applied a quantile-on-quantile regression to analyse this impact on different quantiles and a cross-sectional autoregressive distributed lag(CS-ARDL)approach for the panel of these six countries.The Dumitrescu-Hurlin panel causality test was also used to check the causality between natural resource rents and economic growth in these countries.Results show a negative relationship between natural resources rent and economic growth for the panel but a different impact on quantiles in each country.Only for China and the US,a positive effect can be noticed for both lower and higher quantiles of natural resources and economic growth.The Dumitrescu-Hurlin causality test shows that natural resources can predict economic growth only in China,the U.S.,and the panel.In contrast,no causality was found for the other four countries included in the panel.We suggest that nations invest in wind and solar projects,use biofuels and nuclear energy,introduce a temporary profit tax to protect consumers from escalating energy prices,and increase energy efficiency in buildings and industry.Businesses would benefit from a regulatory framework that is uniform and exhaustive,as well as easier to traverse and more receptive to innovation and creativity.Public-private partnership investments in innovation,innovation incentives,and environmental sector opportunities may foster long-term economic growth。展开更多
文摘Natural resources,green energy,and sustainable development are closely linked with concepts that carry mutual goals to endorse social equity,economic prosperity,and ecological stability while curtailing the harmful influence on the globe.However,the recognition of the Sustainable Development Goals(SDG-7,SDG-13)is closely entangled with digital economy.In this pursuit,this study scrutinizes the effect of dig-italization,renewable energy,and natural resources on the ecological footprint in China from 1990Q1-2022Q4.The empirical analyses are carried out by employing the Quantile-on-Quantile regression,and cross-quantile and partial cross-quantile correlation approaches to inspect the tail dependence of model parameters.The empirical outcomes highlight how China’s environmental quality is influenced by exoge-nous variables,including digitalization index,renewable energy consumption,and natural resources.Digitalization has adverse impact on the ecological footprint in lower quantiles,while insignificant in higher quantiles.Moreover,a strong adverse association exists between ecological footprint and renew-able energy,which syndicate all the quantiles of renewable energy with linking over lower to middle quantiles and weak in higher quantiles of ecological footprint.Besides,the estimated analysis discloses nuanced dependencies across various quantiles.Similarly,it can be found that the strong negative effect of natural resources on ecological footprint in initial quantiles,moderate in middle quantiles,and less positive effect in higher quantiles.By explaining these dynamics,the current study offers valuable intu-itions designed at controlling China toward its dual-carbon target and encouraging the development of a sustainable digital and green economy and thereby,continuing towards achieving SDG-7,and SDG-13 objectives.
基金This work is supported by the National Natural Science Foundation of PRC(71971098).
文摘The link between crude oil price and stock returns of the Group of Seven(G7)countries(Canada,France,Germany,Italy,Japan,the United Kingdom,and the United States)was analyzed in this study using monthly data from January 1999 to March 2020.We adopt a similar approach to Kilian(Am Econ Rev 99(3):1053–1069,2009)and construct a structural vector autoregression framework to decompose crude oil price shocks into oil supply shock,oil aggregate demand shock,and oil-specific demand shock.We then explore the distinct effects of different kinds of oil price shocks from various sources.Based on the decomposed oil price shocks,we apply the connectedness approach and QQ regression to find time-varying co-movements and tail dependence between oil price shocks and G7 stock returns.There is no general correlation between the decomposed oil prices and stock returns in these countries.The effects of oil price shocks on stock returns across different stock market conditions appear to be heterogeneous.Oil supply shock appears to be a net transmitter of spillover effects for all G7 countries within the sample period.
基金supported by the Major Project of the Key Research Institute of Humanities and Social Sciences,Ministry of Education of China(22JD790067).
文摘In this paper,we propose an easily implementable combination forecast method to examine whether systemic risk can predict macroeconomic activity.Our method uses various weighting schemes to combine common individual systemic risk measures.Empirical results demonstrate that our novel forecasting strategy provides better and more stable out-of-sample performance than a set of established methods.Furthermore,the forecast combination puzzle identified by Stock and Watson(2004)is also present in systemic risk.Our findings further reveal that institution-specific risk measures,such as MES and△CoVaR_(d),consistently provide reliable information to inform predictions of future macroeconomic downturns across most regions.The strength and direction of those asymmetric relationships are closely associated with the risk levels(i.e.,quantiles of independent variables)of systemic risk indicators.
文摘Natural resources represent the base of our living and the entire economic activity.Their depletion is a major challenge for the economic development of both developed and developing economies.Their effi-cient use is an indispensable requirement and must be the aim of the public policies designed by the authorities worldwide.In this research,we have investigated the impact of the natural resources rent on the economic growth in some major wealthy economies of the world(P5+1 countries namely:US,UK,France,China,Russia,and Germany).We have applied a quantile-on-quantile regression to analyse this impact on different quantiles and a cross-sectional autoregressive distributed lag(CS-ARDL)approach for the panel of these six countries.The Dumitrescu-Hurlin panel causality test was also used to check the causality between natural resource rents and economic growth in these countries.Results show a negative relationship between natural resources rent and economic growth for the panel but a different impact on quantiles in each country.Only for China and the US,a positive effect can be noticed for both lower and higher quantiles of natural resources and economic growth.The Dumitrescu-Hurlin causality test shows that natural resources can predict economic growth only in China,the U.S.,and the panel.In contrast,no causality was found for the other four countries included in the panel.We suggest that nations invest in wind and solar projects,use biofuels and nuclear energy,introduce a temporary profit tax to protect consumers from escalating energy prices,and increase energy efficiency in buildings and industry.Businesses would benefit from a regulatory framework that is uniform and exhaustive,as well as easier to traverse and more receptive to innovation and creativity.Public-private partnership investments in innovation,innovation incentives,and environmental sector opportunities may foster long-term economic growth。
