Renewable and non-renewable energy consumption, energy technology investment, green technological innovation, and environmental sustainability in the United States: Testing the EKC and LCC hypotheses with novel Fourier estimation.

The energy sector represents one of the key contributors to environmental degradation. In this context, actions taken within the energy sector are paramount in the global effort to combat climate change. This study aims to investigate the impacts of renewable and non-renewable energy consumption, energy technology investment, and green technological innovation on environmental sustainability in the context of EKC and LCC hypotheses in the USA from 1980 to 2015. While many studies in the literature focus on the EKC hypothesis, this study offers a comparative analysis of the EKC and LCC hypotheses with relevant variables. For this aim, the study uses the novel Fourier estimation methods. According to the results, the EKC and the LCC hypotheses are valid in the USA. Moreover, non-renewable energy consumption increases the ecological footprint. On the other hand, non-renewable energy consumption decreases the load capacity factor while renewable energy consumption increases it. Finally, energy technology investment and green technological innovation have an insignificant impact on the ecological footprint and the load capacity factor in both models. All results except energy technology investment and green technological innovation are consistent with our expectations. The USA has the potential to realize green growth. Policymakers should support the green technological innovation process and increase green investments.

The validity of Okun's Law in the case of Central Asia: The role of weather and energy factors.

This study investigates a modified version of the Okun's Law that incorporates energy consumption and temperature for five Central Asian countries, while it employs the ARDL methodology, spanning the period 1995-2018. While the original Okun's Law is not supported, the analysis does find support for the modified Law, suggesting the importance of regional specific factors. The results document the presence of a negative association between unemployment and real GNP both in the short and in the long run. The impact of energy consumption on unemployment is positive in the long run, while the temperature impacts unemployment both in the short and in the long run.

The role of the COVID-19 pandemic in US market volatility: Evidence from the VIX index.

We examine how the implied volatility in the US financial market has been affected by the COVID-19 pandemic. We decompose the Chicago Board Options Exchange (CBOE) Volatility Index (VIX) into two implied volatility conditions (i.e., low and high), and COVID-19 pandemic cases and deaths into two categories (i.e., low and high). Our novel quantile-on-quantile regression approach allows us to better examine the dynamic relationship between the COVID-19 pandemic and implied volatility. Our empirical results show that increased death rates tend to increase fear in the US financial market. Specifically. we find that high COVID-19 cases have a significant impact on implied volatility under high uncertainty conditions, but low COVID-19 cases appear to have no impact on implied volatility in the US market. Our findings offer support to the US policy response by the Federal Reserve Board and the government to limit the instability effect of the COVID-19 shock on the financial markets.

The connectedness between green and conventional bond yields during the COVID-19 crisis: The role of the vaccination process.

This study explores the role of COVID-19 in the connectedness between green and conventional bonds. The findings document spillovers from conventional to green bonds. The results imply that the new green bond market cannot be ignored during a stressful period.

Investigating the association among CO2 emissions, renewable and non-renewable energy consumption in Uzbekistan: an ARDL approach.

This paper examines for the first time the relationship between CO2 emissions and the consumption of renewable and non-renewable energy in Uzbekistan, spanning the period 1985-2020. The analysis uses the Autoregressive Distributed Lags (ARDL) model to estimate the long-run dynamic multipliers and short-run elasticity coefficients of energy consumption variables. Economic factors, such as GDP, are excluded in the analysis as they may cause multicollinearity problems. The empirical results document that in the short- and long-run, hydropower (renewable) energy consumption negatively impacts CO2 emissions per capita, showing a unidirectional causal effect. As regards with non-renewable energy consumption, natural gas and oil energy consumption have a positive impact on CO2 emissions per capita both in the short and long run. Coal consumption positively impacts CO2 emissions in the short run, while it is negative in the long run. Policy measures to enhance the collection of energy from additional renewable energy sources, in particular hydropower, should be taken into account in order to increase the share of renewable energy, and thus, to compensate non-renewable energy consumption which is the main contributor to CO2 emissions. Moreover, solar and wind energy should be explicitly taken into consideration as an additional renewable energy source, which has the lack of attention by policymakers. Furthermore, policy actions, such as the involvement of the private sector into renewable energy projects and the implementation of effective carbon tax policies, could be further options to reduce CO2 emissions.

Impacts of renewable energy on output elasticities and implications for factor shares in European countries: fresh evidence from panel threshold models.

The objective of this paper is to examine, for a panel of seven countries from the European Union, spanning the period 1986-2015, whether the use of renewable energy impacts their output elasticities of capital and labor and, thereby, influences the factor shares. By applying a set of models from threshold analysis, the analysis detects-for the first time-the presence of thresholds in the use of renewable energy with nontrivial consequences; notably, once the thresholds are crossed, the output elasticity of capital declines, while the output elasticity of labor rises. These changes in the elasticities indicate substantial changes in factor shares triggered by the identified threshold level of renewable energy consumption. This paper also finds changes in output elasticities of factors of production for other threshold variables including energy production from oil and gas or coal. These findings portray a complex and non-linear relationship between energy sources (e.g., renewables and non-renewables) vis-à-vis the economic growth level (e.g., GDP), with far-reaching consequences for factor shares from using renewables vis-à-vis non-renewables. Accordingly, it can be assumed that the changes in factor shares can, in turn, shape the incentives for the adoption of renewables within the selected European nations. Hence, future economic policies should emphasize the augmentation of renewable energy in the national energy system in order to sustain the rate of economic growth.

How do foreign direct investment flows affect carbon emissions in BRICS countries? Revisiting the pollution haven hypothesis using bilateral FDI flows from OECD to BRICS countries.

Foreign direct investment (FDI) flows from developed to developing countries may increase carbon emissions in developing countries as developing countries are seen as pollution havens due to their lenient environmental regulations. On the other hand, FDI flows from the developed world may improve management practices and advanced technologies in developing countries, and an increase in FDI flows reduces carbon emissions. Most of the existing studies examine the relationship between FDI flows and carbon emissions by using aggregate FDI flows; however, this paper contributes to the literature by analyzing the impact of FDI flows on carbon emissions in Brazil, Russia, India, China, and South Africa (BRICS) between 1993 and 2012 using bilateral FDI flows from eleven OECD countries. According to our empirical results, from which OECD country FDI flows to BRICS countries matters for carbon emissions in BRICS countries. Our results confirm that FDI flows to BRICS countries from Denmark and the UK increase carbon emissions in BRICS countries, confirming the pollution haven hypothesis. On the other hand, FDI that flows from France, Germany, and Italy reduced carbon emissions in the BRICS countries, confirming the pollution halo effect. FDI flows from Austria, Finland, Japan, Netherlands, Portugal, and Switzerland have no significant impact on carbon emissions in BRICS countries. The BRICS countries should promote clean FDI flows by reducing environmental damages, and investing countries should be rated based on their environmental damage in the host countries.

Hotel Revenue Convergence: Evidence Across Star Hotels in Chinese Provinces.

This paper analyses, for the first time, potential convergence patterns of hotel revenues across provinces in China. Through the club clustering methodology, the analysis uses a unique dataset of all hotels across all Chinese provinces. The findings document that these hotel revenues follow a diverging pattern on a national level, while a converging pattern is identified across certain provinces, thus forming specific clubs. When the analysis is extended to identify potential drivers for such diverging or converging behavior, the new results illustrate the role of productivity trends, management strategies and tax policies as those factors that drive such patterns. The results could be of substantial value, primarily for tourism policymakers to further improve the current framework of the Chinese hotel industry to introduce practices and policies that will allow the industry to catch up with the global market. Supplementary Information: The online version contains supplementary material available at 10.1007/s11293-022-09745-6.

Do gasoline and diesel prices co-move? Evidence from the time-frequency domain.

This study investigates the co-movements of gasoline and diesel prices in three European countries (i.e. Germany, France, and Italy) with different fuel tax systems in place. The methodology follows a time-frequency approach, allowing us to analyse the co-movements at different frequencies and moments in time. As a novelty, we study the impact of fuel tax systems and international oil price dynamics on gasoline and diesel price co-movement. Using weekly data spanning the period from January 2005 to June 2021, the wavelet coherence analysis shows co-movements between gasoline and diesel at all frequencies, as well as during specific periods, but stronger in the long run. This evidence is recorded across all three countries, regardless of their tax systems. However, in decoupling the effect of international oil prices, the partial wavelet coherence analysis shows co-movements emerging also in the short run, with them being stronger around the global financial crisis (2008-2009). Although gasoline taxes are generally higher than diesel taxes, the analysis highlights that fuel tax systems do not influence the co-movements of fuel prices. Thus, shedding new light on the co-movement between commodity prices is fundamental, particularly in light of the current international geopolitical scene.

Money Market Funds (MMFs) and the Covid-19 pandemic: Has the MMLF benefited money markets?

This paper explores the impact of Covid-19, and that of the MMLF program on US MMFs systemic risk through the CoVaR methodology. Using 149 listed prime MMFs, between January 2019 and April 2020, the results document that while Covid-19 increased their systemic risk, the MMLF facility scheme mitigated it.

COVID-19 and cryptocurrency volatility: Evidence from asymmetric modelling.

This paper analyzes the role of COVID-19 pandemic crisis in determining and forecasting conditional volatility returns for a set of eight cryptocurrencies through an asymmetric GARCH modeling approach. The findings report that the COVID-19 pandemic exerts a positive effect on the conditional volatility of those returns, while explicitly considering the pandemic event improves volatility predictions.

Nonlinear responses of consumption to wealth, income, and interest rate shocks.

Nonlinear adjustments of consumption to housing prices, stock prices, income, and interest rates were investigated by employing panel data from 25 countries, spanning the period 2000 to 2016. This is the first study which STAR family models and nonlinear impulse response functions based on the local projections employed alternatively. We present three main pieces of evidence: (1) housing prices, stock prices, interest rates, and income exposures of consumption show time-varying and asymmetric behaviours across all countries, (2) housing wealth effects show stronger persistency and are generally larger than financial wealth effects in most of the countries, and (3) time-varying housing and financial wealth effects are high (low) during expansionary (recessionary) periods across all countries. We suggest to consider both monetary and fiscal policies, as well as the asymmetric and time-varying nature of house prices, stock prices, income, and interest rates on the top of any potential impact of the level of transition in these variables.

Applying a dynamic ARDL approach to the Environmental Phillips Curve (EPC) hypothesis amid monetary, fiscal, and trade policy uncertainty in the USA.

It is well known that unemployment and environmental degradation are two critical issues across the globe. However, there is an extended dearth of literature that explores the nexus between unemployment and environmental degradation. Kashem and Rahman (Environ. Sci. Pollut. Res. 27(101): 31153-31170, 2020) put forward the Environmental Phillips Curve (EPC) hypothesis, which depicts a negative relationship between unemployment and environmental degradation. This study further explores the validity of the EPC hypothesis in the case of the USA. It also investigates the impact of monetary policy uncertainty (MU), fiscal policy uncertainty (FU), and trade policy uncertainty (TU) on carbon dioxide emissions. To this end, the analysis employs the novel methodology of the dynamic ARDL model. The results document that EPC does not hold in the short run, but it does in the long run. Furthermore, both in the short and long run, MU escalates CO2 emissions, while FU plunges emissions in both the short and long run. Finally, TU does not alter the level of CO2 emissions.

FDI, economic growth, and carbon emissions of the Chinese steel industry: new evidence from a 3SLS model.

Determine the main factors affecting carbon emissions of the Chinese steel industry is indispensable commitments to achieve the sustainable development of China. Hereby, based on the Stochastic Impacts by Regression on Population, Affluence and Technology (STIPRAT) model, this paper combines the economic growth function, carbon emission production function, and the FDI function of the Chinese steel industry, and uses the three-stage least square equation model (3SLS) to analyze the relationship between China's economic growth, carbon emissions in the steel industry, and FDI (foreign direct investment) inflows. The results document a complete two-way causal relationship of three variables in the whole country and the Western region, while the relationship in the Eastern region and the Central region is not complete. Moreover, there are no bidirectional causal relationship between carbon emissions and FDI in the Eastern region, while only bidirectional causality between carbon emissions and FDI in the Central region. These findings are of great significance for the Chinese steel industry to formulate effective emission reduction policies.

Does geopolitical risk escalate CO2 emissions? Evidence from the BRICS countries.

High levels of CO2 emissions are extensively cited as one of the main global concerns nowadays. Therefore, researchers have been investigating the factors that affect CO2 emissions. In the prior literature, several social, economic, and political drivers of CO2 emissions have been investigated; however, there is a dearth of the literature on the impact of geopolitical risks (GPR) on CO2 emissions. Hence, the objective of this study is to explore the impact of GPR on CO2 emissions in the case of the BRICS countries while controlling the effects of population, GDP, non-renewable energy, and renewable energy consumption. The study uses the recently developed GPR index, proposed by Caldara and Iacoviello (2018), and the AMG (augmented mean group) estimator method. The findings document that GPR escalates CO2 emissions. That is, a 1% increase in GPR escalates CO2 emissions by 13%. Moreover, it also reports that renewable energy consumption impedes CO2 emissions. In contrast, GDP, population, and non-renewable energy consumption surge CO2 emissions. The study also proposes a few policy implications based on the findings: (1) policymakers and government officials should try to limit GPR through peace treaties, agreements, and negotiations; (2) share of renewable energy in total energy consumption should be increased in order to plunge CO2 emissions.

Exploring a new perspective of sustainable development drive through environmental Phillips curve in the case of the BRICST countries.

Considering that the rigor of economic activities has widely been linked with the turbulent nature of the increasing global atmospheric and environmental hazards thus hampering environmental sustainability, it then presented a suggestive dilemma realizing that increasing unemployment, i.e., de-economizing human activities posit a desirable environmental quality effect. Given this backdrop, and employing the more recent estimation techniques, the current study probes the validity of the novel environmental Phillips curve (i.e., negative relationship between unemployment and environmental degradation) opined by Kashem and Rahman (Environ Sci Pollut Res 1-18, 2020). In this case, the panel of BRICST (Brazil, Russia, India, China, South Africa, and Turkey) economies for the selected data set over the experimental period 1992-2016 is analyzed. After using related approaches that are designed to account for probable country-specific factors, i.e., the cross-sectional dependence concern, the findings from the PMG-ARDL model affirmed the validity of the environmental Phillips curve for the BRICST countries. Thus, there is a significant trade-off between unemployment and environmental degradation. Moreover, this study concludes that renewable energy consumption improves the environmental quality, while conventional energy sources remained detrimental factors to environmental quality in the panel of the examined countries. Therefore, the study identified that the share of renewable energy in the energy mix should be escalated to improve environmental quality and maintain or improve the employment level, thus advancing the sustainable development goals (SDGs) of the BRICST countries.

Impact of economic policy uncertainty on CO2 emissions: evidence from top ten carbon emitter countries.

Over the last few decades, economic policy uncertainty (EPU) has surged across the globe. Furthermore, EPU affects economic activities, which may also generate strong CO2 emissions. The goal of this study is to explore the impact of EPU (measured by the world uncertainty index) on CO2 emissions in the case of the top ten carbon emitter countries, spanning the period 1990 to 2015. The findings from the PMG-ARDL modelling approach document that the world uncertainty index (WUI) affects CO2 emissions in both the short and the long run. In the short run, a 1% increase in WUI mitigates CO2 emissions by 0.11%, while a 1% rise in WUI escalates CO2 emissions by 0.12% in the long run. The findings could have some substantial practical effects on economic policies through which policy makers try to shrink any uncertainty by organizing and participating in international summits and treaties. In addition, international organizations could also launch certain programs to shrink uncertainties associated with economic policy. Finally, these countries should introduce innovation, renewable energy, and enforce alternative technologies that are environment friendly. Overall, governments must provide strong tax exemptions on the use of clean energy, while R&D budgets should also expand.

Convergence of per capita carbon dioxide emissions among developing countries: evidence from stochastic and club convergence tests.

This exploratory study extends the literature on the convergence of per capita carbon dioxide emissions in analyzing stochastic and club convergence within a panel framework for developing countries. The results from Pesaran (Journal of Applied Econometrics, 22(2), 265-312, 2007) and Bai and Carrion-i-Silvestre (Review of Economic Studies, 76(2), 471-501, 2009) panel unit root tests with allowance for cross-sectional dependence confirm stochastic convergence for low-income, lower middle-income, and combined country panels. Further analysis using the nonlinear time-varying factor model of Phillips and Sul (Econometrica, 75(6), 1771-1855, 2007; Journal of Applied Econometrics, 24(7), 1153-1185, 2009) to test for convergence reveals the emergence of multiple convergence clubs within each of the three country panels examined. We observe geographic proximity among many of the countries within the respective convergence clubs.