Nonparametric mixed exponentially weighted moving average-moving average control chart.

This research designed a distribution-free mixed exponentially weighted moving average-moving average (EWMA-MA) control chart based on signed-rank statistic to effectively identify changes in the process location. The EWMA-MA charting statistic assigns more weight to information obtained from the recent w samples and exponentially decreasing weights to information accumulated from all other past samples. The run-length profile of the proposed chart is obtained by employing Monte Carlo simulation techniques. The effectiveness of the proposed chart is evaluated under symmetrical distributions using a variety of individual and overall performance measures. The analysis of the run-length profile indicates that the proposed chart performs better than the existing control charts discussed in the literature. Additionally, an application from a gas turbine is provided to demonstrate how the proposed chart can be used in practice.

Energy consumption and innovation-environmental degradation nexus in BRICS countries: new evidence from NARDL approach using carbon dioxide and nitrous oxide emissions.

The BRICS nations-Brazil, Russia, India, China, and South Africa-have grown significantly in importance over the past few decades, playing a vital role in the development and growth of the global economy. This expansion has not been without cost, either, since these countries' concern over environmental deterioration has risen sharply. Both researchers and decision-makers have focused a lot of attention on the connection between economic growth and ecological sustainability. By using nonlinear autoregressive distributed lag (NARDL) approach, the complex relationships were analyzed between important economic indicators-such as gross domestic product (GDP), ecological innovations (EI), energy consumption (ENC), institutional performance (IP), and trade openness (TOP)-and their effect on carbon emissions and nitrous oxide emissions in the BRICS countries from 1990 to 2021, this study seeks to contribute to this important dialog. Principal component analysis is formed for technological innovations and institutional performance using six (ICT service exports as a percentage of service exports, computer communications as a percentage of commercial service exports, fixed telephone subscriptions per 100 people, internet users as a percentage of the population, number of patent applications, and R&D expenditures as a percentage of GDP) and twelve (government stability, investment profile, socioeconomic conditions, internal conflict, external conflict, military in politics, control of corruption, religious tensions, ethnic tensions, law and order, bureaucracy quality, and democratic accountability) distinct indicators, respectively. The results of nonlinear autoregressive distributed lag estimation show that increase in economic growth would increase carbon dioxide and nitrous oxide emissions. The positive and negative shocks in trade openness have positive and significant impact on carbon dioxide and nitrous oxide emissions in BRICS countries. Furthermore, the positive shock energy consumptions have positive and significant effect on Brazil and India when carbon dioxide and nitrous oxide emissions are used. However, EKC exists in BRICS countries when carbon dioxide and nitrous oxide emissions are used. According to long-term estimation, energy consumption and technological innovations in the BRICS countries show a strong and adverse link with nitrous oxide and a favorable relationship with carbon dioxide emissions. In the long run, environmental indicators are seen to have a major and unfavorable impact in BRICS nations. Finally, it is proposed that BRICS nations can assure environmental sustainability if they support creative activities, enhance their institutions, and support free trade policies.

The determinants of carbon emissions in Belt and Road Initiative countries: analyzing the interactive role of information and communication technologies.

Belt and Road Initiative (BRI) countries have benefited greatly from the intelligent growth of the green economy made possible by the widespread adoption of internet and mobile phone technologies. In addition, renewable energy consumption endorses sustainable development. Therefore, the purpose of this research is to determine if the use of information and communication technology (ICT) and renewable energy consumption has an effect on sustainable development in BRI countries, while using the augmented mean group (AMG) model, AMG robustness test, and panel Dumitrescu-Hurlin causality test to get robust results. According to the results of the study, the information and communication technology, renewable consumption, human capital, and urbanization reduces the emission of carbon dioxide emission in BRI countries while economic growth enhances the CO2 emission. Therefore, it is recommended that BRI countries increase their inter-regional cooperation in order to boost investment in renewable energy, effectively use the spillover effect of technology and knowledge, and end the resource curse in environmental policy. Based on the results, the authors of this paper propose a number of important steps toward environmental sustainability.

The nexus between government spending, economic growth, and tourism under climate change: testing the CEM model for the USA.

This study examines the impact of government spending, income, and tourism consumption on CO2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO2 emissions varies across states, with some US states experiencing a decrease while others see an increase.

Interconnecting sustainable development goals 7 and 13: the role of renewable energy innovations towards combating the climate change.

ABSTRACTThis research examines the trends in environmental footprints through energy innovations, digital trade, economic freedom, and environmental regulation from the context of G7 economies. Quarterly observations from 1998-2020 have been utilized for the advanced-panel model entitled Method of Moments Quantile Regression (MMQR). The initial findings confirm slope heterogeneity, interdependence between the cross-sectional units, stationarity properties, and panel cointegration. The results through FM-OLS, D-OLS, and FE-OLS justify that energy innovations, digital trade, and environmental regulations control ecological damages. In contrast, economic freedom and growth are causing more damage to nature, like ecological footprints (EFP). Similarly, the results through MMQR confirm that the impact of energy innovations, digital trade, and environmental regulations is accepted as a panacea to control environmental degradation in G7. However, the magnitude of the coefficient varies across different quantiles. More specifically, the findings show that the impact of energy innovations is highly significant at 0.50th quantile. In contrast, through digital trade, the impact on EFP is only significant under medium and higher order quantiles (i.e. 0.50th, 0.75th-1.0th). Contrarily, economic freedom is causing more EFP across all the quantiles, where the findings are highly significant at 0.75th quantile. Besides, a few other policy implications are also discussed.

Impact of COVID-19 on China's business and economic conditions: the importance of quantile asymmetries.

China has remained a growth engine for the global economy for the last several years. In this study, we assess the impact of COVID-19 on China's business and economic conditions; employing the quantile-on-quantile (QQ) regression and the quantile causality approaches. These econometrics batteries suit our research postulation, as they are capable to delineate underlying asymmetries across the whole distribution, based on which we can infer whether the response of China's business and economic conditions towards COVID-19 is heterogenous or homogenous. Utilizing the novel business and economic conditions measures, we observed that COVID-19 had initially disrupted both business and economic conditions in China. However, they showcased recovery over time. Our in-depth analysis allowed us to infer that the effect of COVID-19 on China's business and economic conditions is heterogeneous across different quantiles, and there is reliable evidence of asymmetry. The outcomes of quantile causality in mean and variance corroborate our primary estimations. These findings educate policymakers, companies, and other stakeholders to understand the nuances of China's business and economic conditions vis-a-vis COVID-19 in the short-run and as time elapsed.

Are economic growth and environmental pollution a dilemma?

For the first time, this study introduces-proposes using the Armey curve hypothesis (ACH) for testing the environmental Kuznets curve hypothesis (EKCH) in the relevant literature. The rationale for this new proposed methodology is that both hypotheses are expected to have similar inverted U-shaped curves. Hence, we combine the aforementioned hypotheses to obtain a single composite model. This single model may allow us to calculate a maximum (optimum) level of government expenditures that will increase or decrease CO2 emissions for USMCA (the USA-Mexico-Canada Agreement) countries. To this end, our study employs an augmented mean group (AMG) estimator. The results demonstrate that the EKCH is verified by way of the AC model only for Mexico. Additionally, with the advantage of this approach, we calculated the optimal government spending level, which will increase both per capita real GDP (RGDPPC) and CO2 emissions in this country by around 26.4% of RGDPPC. This level of spending will be a kind of threshold point for the Mexican government's policymakers. Hence, they will know that if they continue to spend more than this level, both the RGDPPC and CO2 emissions will decrease, implying either a lower RGDPPC or a cleaner environment. The primary purpose of the proposed methodology in this study is to reveal the possible effects of the government's economic growth-oriented increased public expenditures on the environment in a single composite model. In other words, the relationship between economic growth and the environment is approached from the perspective of public spending, and it is reminded that governments should have harmonious and sustainable public spending policies for both economic growth and a cleaner environment.

Impact of COVID-19 and economic policy uncertainty on China's stock market returns: evidence from quantile-on-quantile and causality-in-quantiles approaches.

COVID-19 unexpectedly ensnared the entire world and wreaked havoc on global economic and financial systems. The stock market is sensitive to black swan events, and the COVID-19 disaster was no exception. Against this backdrop, this study explores the impact of COVID-19 and economic policy uncertainty (EPU) on Chinese stock markets' returns for the period spanning January 23, 2020 to August 04, 2021. The outcomes of the novel quantile-on-quantile regression analysis revealed that both COVID-19 and EPU had a significant negative impact on both Shanghai and Shenzhen stock market returns, while COVID-19 aggravated the level of economic uncertainty in both financial markets. The quantile causality approach of Troster et al. (2018) validates our main estimations. We conclude that COVID-19 and a high level of EPU enervated the returns of China's leading stock markets. Our study provides key insights to policymakers and market participants to determine the behavior of China's stock market returns vis-à-vis COVID-19 during the peak of the pandemic and beyond. Specifically, our findings apprise portfolio investors to augment their portfolio diversification fronts.

Research Methods in a Multinational Business Environment and Implications for Capital Formation: Application of Cross-Sectional Autoregressive Distributed Lag Methods.

We explore whether foreign direct investment outflows augment or obstruct public or private capital in developing countries by decomposing domestic capital into private and public capital. While developed countries are the primary source of foreign direct investment outflows (FDIOs), developing economies have become the primary source of FDIO over the past 30 years. We apply cross-sectional autoregressive distributed lag (CS-ARDL) methods to overcome the issue of endogeneity and cross-sectional dependency in our dataset. This study analyzes the interaction effects of foreign direct investment and institutional quality (IQ) in promoting aggregate domestic capital formation in developing countries. Our empirical results show that FDI outflows augment private capital formation and additionally, IQ also upsurges private capital formation. Conversely, as per results, FDI outflows obstruct public capital formation, and IQ crowds out public capital formation significantly while private capital crowds out FDI inflows. As per result estimations, we notice that FDIO crowds in private capital formation, thus we conclude that the private sector controls the majority of the sectors for developing countries and the role of the public sector is quite minimal. We conclude that private and public capital possess different attributes; thus clubbing them together might result in aggregation bias. Our result estimations provide several useful policy implications.

"Does Institutional Quality, Natural Resources, Globalization, and Renewable Energy Contribute to Environmental Pollution in China? Role of Financialization".

Our study explores the impact of financialization on carbon emissions by utilizing diverse financialization proxies, particularly for China. We examine the impact of financialization, institutional quality, globalization, natural resources, trade openness, and renewable and nonrenewable energy consumption on environmental pollution over the period 1996-2017 by utilizing dynamic autoregressive distributed lag (ARDL) simulations. The empirical findings of the study indicate that institutional quality, trade, globalization, natural resources, and renewable energy consumption significantly decrease environmental pollution in the long run, while foreign direct investment and financialization have neutral effects on carbon emissions. Our findings demonstrate that a 1% increase in institutional quality, trade, IFDI, renewable energy, and globalization leads to a decrease in CO2 emissions by 0.198, 0.016, 0.075, 0.010, and 0.072%, respectively. Even though financialization indexes contributed insignificantly to environmental degradation, other explanatory variables significantly affected carbon emissions through indirect effects of financialization. Financialization indexes behave in a similar context, and these proxy indicators are good parameters to understand the complex nature of financialization. Moreover, in order to achieve low carbon emissions and sustainable development, countries need viable financial institutions that focus on green growth by promoting clean production process strategies to ensure the reduction of CO2 emissions.

The role of economic policy uncertainty in the energy-environment nexus for China: Evidence from the novel dynamic simulations method.

Even though a great number of researches have explored the determinants of carbon emissions, the impact of economic policy uncertainty (EPU) on the environment has not been fully investigated in the energy-environment literature. Since recent studies show a strong relationship between the external environment and uncertainty, the present study for the first time in the literature aims to explore the function of EPU in the energy-environment nexus for China by using the novel bounds testing with dynamic simulations. The empirical results indicate that increases in the real income and energy intensity contribute to environmental pollution while increases in renewable energy lower the level of emissions. Besides, an increase in EPU causes an increase in the volume of carbon emissions. As EPU increases, the government's attention to implement environmental protection policies decreases, and the execution of the environment-related strategies is likely directed in an expected way. The empirical findings suggest that the government should establish consistency in economic and environmental policies to mitigate environmental pollution and thus to reach environmental sustainability.

Investigating household sector's non-renewables, biomass energy consumption and carbon emissions for Pakistan.

Concerns over the observed rising trend towards carbon emissions and the resulting adverse effects of climate change on human activities are the main challenges facing human beings. This study examines household sector's non-renewables and biomass energy consumption magnitude and how much carbon is emitted from non-renewable and biomass energy in Pakistan by using the PSLM 2018-2019 survey. In addition, using STIRPAT model, this study investigates the effect of income, household size, and clean energy on non-renewables and biomass energy choices of the household sector. The results show that 77% of households rely on the consumption of biomass energy. An average household uses firewood at the largest magnitude of 142.06 kg month-1 and kerosene usage at the smallest magnitude of 4.08 kg month-1 among non-renewables and biomass energy choices. The largest contributor to carbon on average is dang cake and its magnitude of carbon emissions is 0.87 tons household-1 year-1 followed by coal with a magnitude of 0.76 tons household-1 year-1. LPG is the lowest contributor to carbon and its carbon emission magnitude is 0.04 tons household-1 year-1. The income impact finding indicates that LPG, kerosene, firewood, and dang cake are necessities, whereas coal is an inferior commodity. The coefficient of household size indicates that large household uses firewood and dang cake, and small one uses LPG and kerosene. As such, households prefer to reduce non-renewable and biomass consumption by increasing clean energy. Therefore, the study suggests that to reduce non-renewable and biomass energy consumption and follow clean energy provision at household level without compromising on environmental quality. The rise in household income and reducing household size could also be a valid policy option for reducing the non-renewable and biomass energy consumption.

Globalization, sustainable development, and variation in cost of power plant technologies: A perspective of developing economies.

This study evaluates the sustainable power plant cost in the outlook of global power plant efficiency to reduce fossil fuel dependency and greenhouse gas emissions. For this purpose, the Global Change Assessment Model (GCAM) applied for conducting the cost assessment of power zone technologies for all principal electricity generation. This study considers the characteristics of essential factors (cement, price of resources, possible increases in employees, and metals) that affect costs. This study suggests that the cost of electricity-generating technologies significantly affects growth efficiency, reduction in production cost, and improving environmental conditions. It also suggests that the cost of electricity-generating technologies, combined with technology mixture, is the key factor behind replacing existing technology in the electricity sector. EPRI cost assessments expanded by around 30% and 50% during 2015-2016. Factors like competition amongst power plant owners, the ambiguous marketplace, production procedures, and lack of environment-related strategies have resulted in massive environmental degradation in developing economies like Pakistan. Based on empirical findings, this study recommends designing efficient technologies, which would reduce power plant costs and ensure vertical prospects related to environmental conditions in the future.

The impacts of different proxies for financialization on carbon emissions in top-ten emitter countries.

The nexus of financialization and carbon emissions has been widely discussed in the literature. A vast body of literature that estimates the impact of financialization on carbon emissions proxies financialization with either domestic credit or market capitalization. However, these representatives do not fully respond to the complicated nature of financial development. To fill the gaps in the existing literature, nine different proxies for financial development are used in the links with carbon emissions in the framework of EKC theory for the years 1980-2014. This study exposes reliable and robust empirical results due to the use of a number of proxies for financialization and second-generation econometric approaches in the empirical analysis. The quantile regression approach deals with unobserved heterogeneity for each cross-section and estimates different slope parameters at varying quantiles. Because non-normality and heterogeneity are detected in dataset, quantile regression provides more robust and reliable estimates than conventional econometric techniques. Results from quantile regression estimator support mixed effects of financial development on carbon emissions over quantiles; in addition, the impact of financial development on carbon emissions is varying not only for each quantile but also for different proxies of financial development. The EKC hypothesis is validated for the top-ten emitter economies. Interpretations and policy suggestions are further discussed in the present study.

The relationship between urbanization, technology innovation, trade openness, and CO2 emissions: evidence from a panel of Asian countries.

This paper explores the dynamic relationship between CO2 emissions, urbanization, trade openness, and technology innovation based on the panel data of 13 Asian countries over the period of 1985-2019. The STIRPAT model is used as a framework for the analysis. For estimation purpose, panel cointegration and FMOLS techniques are utilized. The causality between the concerned variables is also examined by estimating a panel VECM model. The results of panel cointegration reveal the presence of long-run relationship among the variables. FMOLS estimations show that energy consumption increases CO2 emissions while technology change, urbanization, and trade openness compact it. Panel causality analysis indicates bidirectional causality between urbanization and emissions, technology and emissions, trade and emissions, and trade and technology in the long run. Overall findings support the idea that urbanization, technology innovation, and trade openness can play important role to achieve environmental sustainability.