Modelling extreme risks for green bond and clean energy

Value at Risk and Expected Shortfall are two traditional tools used to measure extreme risk in financial markets. However, there is little research on measuring extreme risk in emerging markets such as green bonds and clean energy. This paper uses both semi-parametric models with simultaneous excitation functions and traditional models to estimate extreme risk in SP500 Green Bond (GB) and Global Clean Energy (GCE), selecting Expected Shortfall (ES) and Value at Risk (VaR) as the indices of extreme risk. Then, the paper uses a breakpoint scan of the predictions of the different types of models. The results find that the green bond market was relatively stable while the global clean energy market experienced sharp fluctuations after the COVID-19 pandemic outbreak. Representative models in GCE have at least two breakpoints, but those for GB have no breakpoints. The GARCH model with normal innovations performs the best among all target models, and the GARCH-FZ model fits the best among all semi-parametric candidates. Our research could help governments, companies, and investors with risk management and improve model accuracy and mechanisms for measuring extreme risks.

On the convergence of ecological footprint in African countries: New evidences from panel stationarity tests with factors and gradual shifts

Convergence of the environmental indicators has been one of the significant research areas for researchers since the study of Strazicich and List (2003) was published. Earlier papers have concentrated on investigating the existence of the convergence of indicators of the environment by using carbon emissions as a pollution indicator. However, some researchers have criticized the use of carbon emission as a one-dimensional indicator and proposed using ecological footprint as a more comprehensive indicator. The primary aim of this paper is to examine whether stochastic convergence of ecological footprint exists in 49 African countries from 1973 to 2018 by employing a battery of traditional stationarity methods and a newly proposed stationary method with smooth shifts and a combination of p-values. The empirical results show that panel findings of the conventional stationarity test with no structural shifts reveal that ecological footprint follows a stationary process. In contrast, panel findings of the traditional stationarity method with sharp and smooth changes and the newly developed stationary method with smooth shifts and a combination of p-values reveal that ecological footprint follows a non-stationary process. Moreover, the majority of individual results show that the ecological footprint follows a convergent pattern in 38 African countries, whereas it follows a divergent pattern in the remainder. Therefore, the main finding indicates the stochastic convergence of ecological footprint in African countries is validated. The policy outcomes of the empirical results are given in the body of the paper.

Assessment of food-energy-environmental pollution nexus in Iran: the nonlinear approach

Iran's agricultural production has expanded significantly in recent years. Environmental pollution caused by the use of energy and chemical fertilizers, depletion of groundwater resources, and soil erosion, on the other hand, demonstrates a lack of attention to the environmental dimension of production in this country. In addition to these issues, climate change has exacerbated the agriculture sector's difficulties. This study intends to investigate the asymmetric relationship between energy consumption, chemical fertilizer consumption, CO₂ emissions, temperature changes, and production from 1961 to 2019 using the NARDL approach and Granger causality test in the frequency domain (Breitung and Candelon.). Short-term and long-term estimates revealed that the positive and negative shock effects of energy consumption on production are both positive. As a result, it was observed that the negative shock of increased energy consumption had a greater influence on agricultural output than the positive shock. In the long run, the positive shock of fertilizer use has a positive effect on and improves production. But the effect of a negative shock is insignificant. Furthermore, the negative shock of CO₂ emission has a positive effect on production. Finally, positive and negative shocks in temperature changes were discovered to have an increasing and reducing influence on production. The results of the Granger causality test in the frequency domain test showed that there is a bidirectional causality relationship between energy consumption and agro-production in the long term. There is also unidirectional causality from CO₂ emissions and fertilizer consumption to production and from production to climate change. According to the findings, reforming energy prices, investing in mechanized agriculture, shifting away from fossil fuel consumption towards renewable energy, and tending to green growth are all necessary to achieve multiple goals such as optimizing energy consumption, reducing environmental pollution, and improving efficiency.

Pathways to Argentina's 2050 carbon-neutrality agenda: the roles of renewable energy transition and trade globalization

The government of Argentina has recently declared its objective of turning the nation carbon-neutral by 2050. Thus, it is essential to identify the relevant factors which can facilitate the attainment of this environmental development target. Against this backdrop, this study aims to evaluate the impacts of renewable electricity output, trade globalization, economic growth, financial development, urbanization, and technological innovation on sectoral carbon dioxide emissions in Argentina during the 1971-2014 period. The findings, overall, suggest that enhancing renewable electricity output share in the total electricity output figure of the nation helps to curb carbon dioxide emissions generated from Argentina's energy, manufacturing and industry, residential and commercial buildings, and transportation sectors. Contrarily, greater trade globalization is evidenced to boost carbon dioxide emissions in almost all the aforementioned economic sectors. Besides, the findings also validate the existence of the carbon dioxide emission-induced environmental Kuznets curve hypothesis for all four sectors. In addition, financial development and urbanization are also evidenced to exert carbon dioxide emission-stimulating impacts, while technological innovation is witnessed to be necessary for curbing sector-based carbon dioxide emissions in Argentina. Accordingly, to decarbonize the economy, this study recommends the government of Argentina to adopt necessary policies for fostering renewable energy transition within the electricity sector, greening the trade globalization strategies, achieving environmentally sustainable economic growth, developing the financial sector by introducing green financial schemes, planning sustainable urbanization, and financing technological development-oriented projects.

Developing long- and short-run nexus between industrial growth, economic growth, and trade balance of China

The study examined the short- and long-run nexus between industrial growth, economic growth, oil production, inflation, and trade deficit of China, using quarterly data from 1995Q1 to 2020Q4. We used autoregressive distributed lag model (ARDL), after affirmation of long-run relationship and uni-directional causality. To examine short-run dynamics, an error correction model (ECM) was specified, and Granger causality test was conducted to find the direction of causality between variables. Empirical findings confirmed cointegration between trade deficit and industrial growth, economic growth, inflation, and oil production. Further, uni-directional causality between trade deficit and all independent variables was found, running from independent variables towards trade deficit. Results revealed that growth of industrial production index play a substantial role in determining trade balance of China. The study further confirms the effectiveness of economic growth and inflation for trade deficit, in both short run and long run. The findings are consistent with extant literature. On the policy front, a couple of suggestions including trade policies with special focus on industrial reforms, and loose monetary policies are made on the basis of derived conclusions.

Mitigating energy production-based carbon dioxide emissions in Argentina: the roles of renewable energy and economic globalization

The energy sector of Argentina is predominantly reliant on fossil fuels. Consequently, such fossil fuel dependency within the nation's power sector, in particular, has aggravated the environmental quality in Argentina by amplifying the nation's energy production-based carbon emission levels. However, keeping into consideration the international commitments pledged by Argentina under the Paris Accord and the Sustainable Development Goals agenda, it is pertinent for this South American country to curb its energy production-based emission of greenhouse gases, especially carbon dioxide. Against this milieu, this study examines the impacts of renewable electricity generation, economic globalization, economic growth, and urbanization on carbon dioxide emissions generated from the production of electricity and heat in the context of Argentina. Using annual frequency data from 1971 to 2016, recent econometric methods are applied to control for multiple structural breaks in the data. The major findings from the ecnometric analyses affirmed long-run associations between renewable electricity generation, economic globalization, economic growth, urbanization, and energy production-based carbon dioxide emissions in Argentina. Besides, enhancing renewable electricity output shares is found to curb these emissions while economic globalization and urbanization are witnessed to boost them. Moreover, renewable electricity generation and economic globalization are found to jointly reduce the energy production-related carbon dioxide emissions in Argentina. The results also validate the authenticity of the Environmental Kuznets Curve (EKC) hypothesis. Finally, the causality analysis reveals evidence of unidirectional causalities running from renewable electricity generation, economic globalization, economic growth, and urbanization to energy production-related carbon dioxide emissions in Argentina. In line with these findings, this study recommends several viable policies which can be implemented to help Argentina control the growth of its energy production-based carbon dioxide emissions.

COVID-19 Pandemic and firm-level dynamics in the USA, UK, Europe, and Japan

This paper examines the impact of the coronavirus pandemic during its first and second waves for the USA, UK, Europe, and Japan. We explore the firm-level dynamics and exhibit the impact of coronavirus events on large and small firms and firms' idiosyncratic risk. We find that the intensity of the impact of the coronavirus pandemic events is not uniform for firms. The Blank Swan events in March 2020 exhibit stronger impact the second wave till April 2021. The second wave analysis reveals the sign of recovery and receding effect of the pandemic. The idiosyncratic analysis shows the positive impact of the coronavirus and stringency measures on the idiosyncratic risk.

An empirical investigation of nuclear energy and environmental pollution nexus in India: fresh evidence using NARDL approach

Environmental pollution caused by carbon emissions is an emerging issue to study among researchers. The nexus between environmental pollution and carbon emissions has motivated researchers to evaluate the impact of cleaner energy on carbon emissions. This study further contributes to the research by examining the above relationship by studying the asymmetric influence of nuclear energy (NE), industrial productivity (IP), and economic growth rate (GDP) on carbon emissions (CO₂) in India from 1975 to 2018 using the asymmetric autoregressive distribution lag approach. The results of the bound test and the Wald test show that in the long run, there is an asymmetric relationship between CO₂, NE, GDP, and IP, and in the short run, there is a symmetric relationship between CO₂, GDP, and IP. The result implies that increased usage of nuclear energy over fossil fuels and improvement in industrial productivity, in the long run, reduces CO₂ emission in India. Furthermore, the study concludes that the government should consider the asymmetric relationship between the variables and devise appropriate policies to increased nuclear energy and industrial productivity in India for environmental sustainability.

Fractional unit-root tests allowing for a fractional frequency flexible Fourier form trend: predictability of Covid-19

In this study we propose a fractional frequency flexible Fourier form fractionally integrated ADF unit-root test, which combines the fractional integration and nonlinear trend as a form of the Fourier function. We provide the asymptotics of the newly proposed test and investigate its small-sample properties. Moreover, we show the best estimators for both fractional frequency and fractional difference operator for our newly proposed test. Finally, an empirical study demonstrates that not considering the structural break and fractional integration simultaneously in the testing process may lead to misleading results about the stochastic behavior of the Covid-19 pandemic.

Asymmetrical ARDL correlation between fossil fuel energy, food security, and carbon emission: providing fresh information from Pakistan

The core objective of our study seeks to examine the asymmetrical impact of agriculture, fossil fuel consumption, and food security on carbon emission (CO2) in Pakistan from 1969 to 2018. The current study applied multiple unit root tests (ADF, PP, and KPSS, Z&A) to check data stationarity and structural breaks. We used the population data as a food security proxy indicator. The outcomes disclosed that there is a long-term asymmetric relationship between the variables. The results also verified the atypical response of CO2 to adverse shocks in agricultural value-added. Furthermore, the results showed that population and fossil fuel consumption would further worsen environmental standards. Based on the results of the study, the government needs to take practical steps for active policy-making and assessing ecological challenges in Pakistan.

How to bend down the environmental Kuznets curve: the significance of biomass energy

Sources of renewable energy have received wide attention in the literature because of serious threats to the environment. However, some renewable resources, including biomass energy role is debatable in the energy economics literature. This empirical work focuses to analyze the role of biomass energy in carbon dioxide (CO₂) emissions using the framework of the environmental Kuznets curve (EKC) in Pakistan over the period from 1980 to 2015. The bound testing approach suggests there is cointegration among study variables. The study uses an auto-regressive distributed lag model (ARDL) with a structural break in the series. To summarize the findings of the study, it can be inferred that biomass energy increase CO₂ emissions. In addition, biomass energy helps to form a U-shaped relationship between income and CO₂ emissions that support the EKC hypothesis. Also, the feedback hypothesis is found between biomass energy and CO₂ emissions. The findings would guide policymaker with practical guidelines to formulate policies to utilize a high amount of biomass energy in a sustainable manner.

The influence of renewable and non-renewable energy consumption and real income on CO2 emissions in the USA: evidence from structural break tests

The objective of this study is to explore the influence of the real income (GDP), renewable energy consumption and non-renewable energy consumption on carbon dioxide (CO₂) emissions for the United States of America (USA) in the environmental Kuznets curve (EKC) model for the period 1980-2014. The Zivot-Andrews unit root test with a structural break and the Clemente-Montanes-Reyes unit root test with a structural break report that the analyzed variables become stationary at first-differences. The Gregory-Hansen cointegration test with a structural break and the bounds testing for cointegration in the presence of a structural break show CO₂ emissions, the real income, the quadratic real income, renewable and non-renewable energy consumption are cointegrated. The long-run estimates obtained from the ARDL model indicate that increases in renewable energy consumption mitigate environmental degradation whereas increases in non-renewable energy consumption contribute to CO₂ emissions. In addition, the EKC hypothesis is not valid for the USA. Since we use time-series econometric approaches that account for structural break in the data, findings of this study are robust, reliable and accurate. The US government is advised to put more weights on renewable sources in energy mix, to support and encourage the use and adoption of renewable energy and clean technologies, and to increase the public awareness of renewable energy for lower levels of emissions.

Heterogeneous autoregressive model with structural break using nearest neighbor truncation volatility estimators for DAX

High frequency financial data modelling has become one of the important research areas in the field of financial econometrics. However, the possible structural break in volatile financial time series often trigger inconsistency issue in volatility estimation. In this study, we propose a structural break heavy-tailed heterogeneous autoregressive (HAR) volatility econometric model with the enhancement of jump-robust estimators. The breakpoints in the volatility are captured by dummy variables after the detection by Bai–Perron sequential multi breakpoints procedure. In order to further deal with possible abrupt jump in the volatility, the jump-robust volatility estimators are composed by using the nearest neighbor truncation approach, namely the minimum and median realized volatility. Under the structural break improvements in both the models and volatility estimators, the empirical findings show that the modified HAR model provides the best performing in-sample and out-of-sample forecast evaluations as compared with the standard HAR models. Accurate volatility forecasts have direct influential to the application of risk management and investment portfolio analysis.

Trends and structural shifts in health tourism: evidence from seasonal time-series data on health-related travel spending by Canada during 1970-2010

There has been a growing interest in better understanding the trends and determinants of health tourism activities. While much of the expanding literature on health tourism offers theoretical or qualitative discussion, empirical evidences has been lacking. This study employs Canada's outbound health tourism activities as an example to examine the trends in health tourism and its association with changing domestic health care market characteristics. A time-series model that accounts for potential structural changes in the trend is employed to analyze the quarterly health-related travel spending series reported in the Balance of Payments Statistics (BOPS) during 1970-2010 (n = 156). We identified a structural shift point which marks the start of an accelerated growth of health tourism and a flattened seasonality in such activities. We found that the health tourism activities of Canadian consumers increase when the private investment in medical facilities declines or when the private MPI increases during the years following the structural-change. We discussed the possible linkage of the structural shift to the General Agreement on Trade in Services (GATS), which went into effect in January, 1995.

Structural breaks, tourism development, and economic growth: Evidence from Taiwan

Our paper differs from previous studies by examining the issue of whether regime changes have broken down the stability of the long-run relationships between tourism development and real GDP in Taiwan for the 1959-2003 period. We empirically investigate the co-movements and the causal relationships among real GDP, tourism development, and the real exchange rate in a multivariate model. We use two different tourism variables-international tourism receipts and number of international tourist arrivals. To employ the unit root tests and the cointegration tests allowing for a structural break, the empirical evidence clearly shows that the causality between tourism and economic growth is bi-directional. Lastly, the international and cross-strait political change, economic shocks, and the relaxing of some tourism control and policies would break down the stability of the relationships between tourism development and economic growth. Overall, we do find the structural breakpoints, and they look to match clearly with the corresponding critical economic, political, or tourist incidents.