Does US monetary policy uncertainty affect returns of Asian Developed, emerging, and frontier equity markets? Empirical evidence by using the quantile-on-quantile approach.

This paper examines the impact of the Monetary Policy Uncertainty (MPU) of the United States on Asian developed, emerging, and frontier stock markets using a Quantile-on-Quantile (QQR) approach by using monthly data from January 2006 to December 2022 of 14 Asian countries. The study finds that US monetary policy significantly negatively influences Asian stock markets. This is primarily due to the widespread use of the US dollar as a universal currency, resulting in substantial ripple effects on other nations through trade relationships. In Asian developed markets, MPU is negatively related to Australia and New Zealand. At the same time, it has a positive relationship with Hong Kong and Japan at the upper quantiles. Among Asian emerging markets, MPU negatively impacts Taiwan's, India's, and China's returns, increasing this negative relationship at higher MPU quantiles. Additionally, MPU has a significant negative relationship with Thailand, Indonesia, Korea, and Malaysia returns. In contrast, higher quantiles of MPU have no discernible impact on the Philippines stock returns. In Asian frontier markets, MPU negatively impacts Pakistan's and Sri Lanka's returns. The implications of these findings are twofold: for investors, this study provides valuable insights for hedging activities, allowing for more informed decisions based on the MPU of other countries to identify profitable stocks. For policymakers, this research aids in formulating effective monetary policy strategies. Furthermore, future studies can build upon these results by exploring other markets and comparing their outcomes with the findings presented in this study.

The impact of natural resource abundance on ecological footprint: evidence from Algeria.

The relationship between natural resources and the ecological footprint is a debate issue and shows inconclusive results. Therefore, the present study attempts to examine the role of natural resource abundance in shaping Algeria's ecological footprint over the period 1970-2018 using autoregressive distributed lags (ARDL) and quantile-on-quantile regression (QQR). Empirical findings from the ARDL technique suggest that natural resource rents, GDP per capita, gross fixed capital formation, and urbanization increase ecological footprint. The QQR methodology, however, provided more insightful and in-depth findings compared to those of the ARDL. Interestingly, the findings of the QQR uncovered that while the impact of natural resources on ecological footprint is positive and substantial at the middle and upper quantiles, it gets weaker at the lower quantiles. This further implies that the over-extraction of natural resources would generate impacts on environmental degradation, while lesser natural resource extraction appears to be less detrimental to the environment. The QQR also reveals that economic growth, gross fixed capital formation, and urbanization have a positive effect on the ecological footprint in the majority of quantiles, with the exception of the lower quantiles of urbanization, where the effect is negative, indicating that the lowest degree of urbanization improved environmental quality in Algeria. Policymakers in Algeria are urged to pay critical attention to the management of the country's natural resources, promote renewable energy sources, and develop public awareness to secure environmental sustainability.

COVID-19 pandemic and stock market performance: A comparative study of emerging economies.

The paper investigates the co-movement of COVID-19 pandemic and performance of stock markets of four emerging economies. The Quantile-on-Quantile regression model was applied to daily share prices of stock markets from March 13, 2020 to November 30, 2021 in these economies. The results indicate varied relationships across various quantiles of COVID-19 cases and share prices. Whilst both positive and negative relationships are established at different quantiles of share prices for Brazil and Kenya, negative co-movements are recorded for India and South Africa for all quantiles of share prices. The varying dependence between COVID-19 and stock markets provide critical insights to policy makers.

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.

Asymmetric impacts of geopolitical risk on stock markets: A comparative analysis of the E7 and G7 equities during the Russian-Ukrainian conflict.

In a nonparametric quantile-on-quantile regression model, we analyze the asymmetric financial impact of the Russian-Ukrainian conflict-induced geopolitical risk (GPR) on the top-seven emerging (E7) and developed (G7) stock markets. Our findings indicate that the impact of GPR on stock markets is not only market-specific but also asymmetric. Except for Russia and China, all E7 and G7 stocks respond positively to GPR in normal conditions. Among the E7 (G7) countries, stock markets from Brazil, China, Russia, and Turkey (France, Japan, and the US) are resilient to GPR in bearish stages. The portfolio and policy implications of our findings have been highlighted.

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.

Nexus between macroeconomic uncertainty, oil prices, and exports: evidence from quantile-on-quantile regression approach.

International trade is key to boosting the economic growth and development of an economy. Hence, it becomes critical to analyze its determinants. The present study attempts to empirically analyze the determinants of trade exports of Pakistan with its top-5 trade partners. The prior literature suffers from biased findings due to deploying the aggregate data and ignoring the likely asymmetries in the drivers of the exports. The present study has used the monthly data of oil prices and macroeconomic uncertainty in order to empirically investigate the determinants of exports. For the purpose of analysis, several advanced econometric (quantile unit root, cointegration, and granger causality) tests and (quantile-on-quantile regression) techniques are utilized to handle the issue of asymmetries in the modeled series. The findings reveal a positive and significant relationship between oil prices in Pakistan and exports. Furthermore, macroeconomic uncertainty has a significantly negative impact on the country's exports. Based on the results, key policy implications are provided.

The Dynamic Nexus Between International Tourism and Environmental Degradation in Top Twenty Tourist Destinations: New Insights From Quantile-on-Quantile Approach.

Tourism is one of the important factors that can affect the environmental and economic situation of any economy. This study investigates the relationship between tourist arrivals and CO2 emission in the top 20 tourist destinations using data from quarterly observations from 1995 to 2018. A unique technique via quantile-on-quantile regression and Granger causality in quantiles was used. In particular, how the quantiles of tourist arrivals impact quantiles of CO2 emission was analyzed. The empirical results suggest a combination of both positive and negative effects of tourist arrivals and CO2 emission in most tourist destinations. Predominantly, at both high and low tails, in the USA, Spain, Hong Kong, and Austria, tourist arrival has a positive effect on CO2 emission, whereas in the case of Canada, France, Germany, Mexico, and Malaysia, the association was negative. On the other hand, China, Greece, Russia, Japan, Italy, South Korea, Thailand, and Turkey have both positive and negative effects of tourism on CO2 emissions at low and high tails. Tourism can be an important factor while formulating policy for environmental and climate aspects.

Re-visiting the resource curse hypothesis in the MINT economies.

Natural resources are extremely important to the economy, particularly in emerging nations such as the MINT (Mexico, Indonesia, Nigeria, and Turkey) nations. To improve their economic performance, such nations put a priority on maximizing the use of natural resources. These natural materials are the basis on which all living creatures rely, and they are the primary motivation behind contemporary production. Therefore, the current research utilizes a dataset spanning the period from 1970 to 2019 to assess the effect of natural resource on economic growth for the MINT nations. The present study uses a unique quantile-on-quantile regression (QQR) approach to assess this interrelationship. Furthermore, we apply the novel quantile causality suggested by Troster (2018), which identifies causality across quantiles. The findings from the QQR reveal that in the majority of the quantiles, the effect of natural resources on economic expansion is positive in Nigeria and Mexico, while it is negative in Indonesia and Turkey. In addition, a feedback causality is found between economic growth and natural resources for Mexico, Indonesia, and Nigeria. Based on the results, it is paramount for policymakers to develop policies or frameworks that promote cleaner energy sources and more effective use of natural resources, which can aid the country's economic growth.

Modelling the asymmetric effect of COVID-19 on REIT returns: A quantile-on-quantile regression analysis.

The COVID-19 pandemic has affected all sectors of the economy resulting in unprecedented challenges for market participants, policymakers, and practitioners. This study envisages this issue from the perspective of real estate investment trusts (REITs), which is a relatively less analysed segment. We examine the impact of the COVID-19 pandemic on REIT returns for 12 top REIT regimes spread across America, Asia, and Europe under the bullish, bearish, and normal market conditions over the COVID-19 period (specifically from February 02, 2020, to January 24, 2022). We employ the quantile-on-quantile regression and causality-in-quantiles approach. We document a strong (weak) predictive power of COVID-19 cases on REIT returns within the lower (upper) conditioned quantiles. Our findings are of importance to market participants, practitioners, and regulators across REIT regimes.

The criticality of financial risk to environment sustainability in top carbon emitting countries.

This research examines the linkage between financial risk and carbon emissions using a quarterly dataset spanning from 1991 to 2019 for top carbon emitting countries. To achieve the study objective, this study apply quantile-on-quantile regression (QQR), the quantile regression (QR) approach for robustness check, and the nonparametric predictive test that identifies causality in mean and variance. Empirical findings from the QQR technique disclose the following: (i) financial risk decreases carbon emissions in the USA, Russia, Germany, and Canada; (ii) in China, India, Japan, Brazil, and Indonesia, financial risk enhances carbon emissions (iii) while we find mixed reactions in the case of South Korea. The outcomes of the conventional quantile regression also confirm the QQR outcomes, while that of nonparametric causality discloses evidence of causality in majority of quantiles from financial risk to carbon emissions. Based on these empirical outcomes, policymakers in the financial risk-induced-environmental degradation regions should consider implementing policies or reforms that would keep financial systems sound, in order to prevent shocks to the environment, and its attendant multiplier impact on the environmental sustainability targets implemented to protect both the immediate and the future generations.

Impacts of globalization and energy consumption on environmental degradation: what is the way forward to achieving environmental sustainability targets in Nigeria?

One of the major problems the world is currently facing is climate change. This is due to the use of fossil fuel combustion, which increases the presence of CO2 emissions and other greenhouse gases in the atmosphere in several countries of the world, which Nigeria is not exempted from. Against this background, this study examines the impacts of globalization, real income, urbanization, and energy consumption on environmental degradation; and proffer way forward to achieving environmental sustainability targets in Nigeria, using quarterly frequency time series data over a period 1971-2018. To achieve our study objectives, this study makes use of quantile-quantile (Q-Q) approach, developed by Sim and Zhou J Bank Financ 55:1-8, (2015). This approach groups together nonparametric estimation and quantile regression. Empirical results show that, in all quantiles, globalization, real income, urbanization, and energy consumption impact positively on environmental degradation. Thus, we are of the opinion that for the nation to achieve any meaningful environmental sustainability targets, (i) it must shift from economic activities that are dependent and driven by non-renewable energy sources; (ii) enact environmental laws and regulations that prevent indigenous and multinationals firms from using non-renewable energy sources in production activities; (iii) discourage rural-urban migration by enacting policies that would improve life in the rural areas, such as diverting investment of indigenous and multinational companies to be situated in the rural areas; and lastly, (iv) learn from jurisdictional experiences that have successfully replaces non-renewable energy sources with renewable ones for an overall economic growth and environmental sustainability targets for both the immediate and future generations.

Does information and communication technology impede environmental degradation? fresh insights from non-parametric approaches.

Although ICT has played a critical role in the socio-economic growth of human cultures, it has also brought with it significant environmental risks. Nevertheless, scholars remain divided on this topic; some believe that ICT has had a positive influence on the quality of the environment, while others believe that ICT has created major environmental issues. Hence, this research is another effort to assess the effects of ICT on CO2 emissions in the top 10 ICT nations (Denmark, Japan, Luxemburg, South Korea, Netherlands, Iceland, Norway, Sweden, Switzerland, and the United Kingdom) using a dataset from the period between 1986Q1 and 2019Q4. All prior studies have established symmetric association between ICT and CO2. As a result, we applied the novel non-parametric approaches (quantile-on-quantile regression and Granger causality in quantile) to assess this association. The findings from the QQR uncovered that in the majority of the quantiles, for Denmark, Japan, Luxemburg, Netherland, Norway, Sweden, United Kingdom and Switzerland, the effect of ICT on CO2 emissions is negative, while in the majority of the quantiles, the effect of ICT on CO2 emissions is positive for the Netherlands, South Korea, and Iceland. Furthermore, we applied the novel Granger causality in the quantiles approach and the outcomes provided evidence of bidirectional causality between CO2 emissions and ICT in all the selected nations. The study proposes that sustainable ICT should be used to improve carbon reduction and energy savings potential by optimizing other industries, including managing and monitoring energy usage.

Asymmetric impact of temperature on COVID-19 spread in India: Evidence from quantile-on-quantile regression approach.

The emergence of new coronavirus (SARS-CoV-2) has become a significant public health issue worldwide. Some researchers have identified a positive link between temperature and COVID-19 cases. However, no detailed research has highlighted the impact of temperature on COVID-19 spread in India. This study aims to fill this research gap by investigating the impact of temperature on COVID-19 spread in the five most affected Indian states. Quantile-on-Quantile regression (QQR) approach is employed to examine in what manner the quantiles of temperature influence the quantiles of COVID-19 cases. Empirical results confirm an asymmetric and heterogenous impact of temperature on COVID-19 spread across lower and higher quantiles of both variables. The results indicate a significant positive impact of temperature on COVID-19 spread in the three Indian states (Maharashtra, Andhra Pradesh, and Karnataka), predominantly in both low and high quantiles. Whereas, the other two states (Tamil Nadu and Uttar Pradesh) exhibit a mixed trend, as the lower quantiles in both states have a negative effect. However, this negative effect becomes weak at middle and higher quantiles. These research findings offer valuable policy recommendations.

Climate indicators and COVID-19 recovery: A case of Wuhan during the lockdown.

The world needs to get out of the COVID-19 pandemic smoothly through a thorough socio-economic recovery. The first and the foremost step forward in this direction is the health recovery of the people infected. Our empirical study addresses this neglected point in the recent research on COVID-19 and specifically aims at exploring the impact of the environment on health recovery from COVID-19. The sample data are taken during the lockdown period in Wuhan, i.e., from 23rd January 2020 to 8th April 2020. The recently developed econometric technique of Quantile-on-Quantile regression, proposed by Shin and Zhu (2016) is employed to capture the asymmetric association between environmental factors (TEMP, HUM, PM2.5, PM10, CO, SO2, NO2, and O3) and the number of recovered patients from COVID-19. We observe significant heterogeneity in the association among variables across various quantiles. The findings suggest that TEMP, PM2.5, PM10, CO, NO2, and O3 are negatively related to the COVID-19 recovery, while HUM and SO2 show a positive association at most quantiles. The study recommends that maintaining a safe and comfortable environment for the patients may increase the chances of recovery from COVID-19. The success story of Wuhan, the initial epicenter of the novel coronavirus in China, can serve as an important case study for other countries to bring the outbreak under control. The current study could be conducive for the policymakers of those countries where the COVID-19 pandemic is still unrestrained.

Does political stability contribute to environmental sustainability? Evidence from the most politically stable economies.

The study evaluates the effect of political risk on CO2 emission in the top 10 most politically stable economies (Australia, Canada, Germany, Finland, Denmark, Norway, Netherlands, New Zealand, Sweden, and Switzerland) from 1991/Q1 and 2019/Q4. To the investigators' understanding, this is the first empirical analysis that inspects the effect of political risk on CO2 emissions in the top 10 most politically stable economies. Therefore, the current paper fills a gap in the existing literature. Innovative quantile-on-quantile regression and quantile causality approaches are applied to explore this nexus. The quantile-on-quantile regression results reveal that in the majority of the quantiles, political risk enhances environmental quality for the case of Norway, Sweden, Canada, and Switzerland. Moreover, political risk degrades the quality of the environment in Australia, Germany, and Denmark, while the outcomes were mixed for the rest. Since political stability has encouraged international corporations to invest. As a result, guaranteeing political stability will attract more foreign investment, pressuring the governments of these countries to treat the climate catastrophe more urgently. Moreover, reforms should be aimed at sustaining existing environmental policies related to the green economy, while local and international firms should vigorously pursue investments in renewable energy sources and energy-saving-efficient technologies.

The asymmetric effects of renewable energy consumption and trade openness on carbon emissions in Sweden: new evidence from quantile-on-quantile regression approach.

With the passage of time, the continued burning of fossil fuels is proving to be one of the world's most serious issues. In response, the current research aims to assess the critical linkage between carbon emissions and renewable energy, trade openness, and economic growth in Sweden utilizing a dataset from 1965 to 2019. The study applied the novel quantile-on-quantile regression (QQ) approach to assess this relationship. The main objectives are to address the following questions: (i) What are the effects of trade openness on CO2 emissions in each quantile? (ii) Does renewable energy consumption mitigates CO2 emissions in each quantile? What is the impact of economic growth on CO2 emissions in each quantile? The outcomes from the QQ approach revealed that at low and medium quantiles (0.1-0.6), the effect of trade openness on CO2 emissions is negative. Furthermore, at lower and higher quantiles (0.1-0.90) of combination of renewable energy consumption and CO2 emissions, the effect of renewable energy consumption on CO2 emissions is negative. Finally, at majority of the quantiles, the effect of economic growth on CO2 emissions is negative. Moreover, the present study applied the quantile regression (QR) approach as a robustness check. The findings of the QR validate the findings of the QQR approach. The study proposes that policy-makers in Sweden should place greater emphasis on raising public awareness regarding the issues of renewable energy since it mitigates environmental degradation.

Asymmetric effect of COVID-19 pandemic on E7 stock indices: Evidence from quantile-on-quantile regression approach.

Various studies have been conducted to examine the effect of COVID-19 on stock prices. However, these studies failed to examine the effect across quantile distributions of both dependent and independent variables. This study pays particular attention to the emerging 7 countries and examines the effect of the novel coronavirus 2019 (COVID-19) pandemic on stock prices. We use quantile unit root and quantile cointegration tests to examine the integrating properties of COVID-19 cases and deaths with stock prices and use quantile-on-quantile regression (QQR) to examine the relationship across quantile distributions of both dependent and independent variables. Quantile cointegration estimates indicate that stock prices are integrated with COVID-19 cases whereas QQR estimates indicate a weak positive relationship at the upper quantiles of stock prices, and a strong negative effect is found at the lower quantiles of stock prices. Policy implications are recommended based on the findings of this study.

Carbon tax and energy innovation at crossroads of carbon neutrality: Designing a sustainable decarbonization policy.

Decarbonation has been a primary policy prerogative for Sweden, and carbon tax has been a primary policy instrument in this pursuit, and the revenue generated out of carbon tax has been a driver for energy innovation. However, the benefits of energy innovation have not been experienced across various sectors in Swedish economy, and it might be anticipated that the potential aim of achieving carbon neutrality might not be accomplished to the fullest. Hence, being faced with the need of policy realignment for Sweden, this study has made an attempt to discover the dynamics between carbon tax revenue and energy innovation over a period of 1990-2019, following Quantile-on-Quantile Regression framework. The results obtained from the study show that the impact of carbon tax revenue on energy innovation might turn out to be ineffective beyond a certain threshold limit. A similar pattern has also been observed for the impact of energy innovation on carbon tax revenue. This study gives an indication that there might be a non-linear association between both these model parameters. The study outcomes have paved a way to design a policy framework for helping Swedish economy to attain the objectives of Sustainable Development Goals, while paving the ways to achieve carbon neutrality.

Asymmetric nexus between urban agglomerations and environmental pollution in top ten urban agglomerated countries using quantile methods.

The rapid urbanization growth has not only improved the living standards of people but also raised concerns for environmental sustainability over the globe. In this regard, the issue of excessive urban concentration or over-agglomeration in metropolitan areas is nowadays the prime concern for urban planning and building energy-efficient and eco-friendly infrastructures. In response to rising interest in the dynamic linkage between urban concentration and environment, the current research empirically examines the crucial nexus between urban agglomerations and environmental degradation in top ten urban agglomerated countries in the world from 1960Q1 to 2014Q4. The current research is the pioneer empirical work in the area of urbanization by applying recently developed and innovative methods of quantile-on-quantile (QQ) approach and quantile Granger causality in relatively less explored area of urban agglomeration at the cross-country level. Our mainstream findings indicate that urban agglomeration has a strong positive effect on CO2 emissions in most of our sample countries, and this effect is more pronounced in higher quantiles of respective variables. These results imply that excessive levels of urban concentration in big cities cause environmental degradation, which could be attributed to extreme population density, overcrowding, traffic congestion and extensive demand for energy consumption. However, some countries such as Israel, Paraguay and Columbia exhibit overall declining and negative trends about the relationship between urban agglomerations and CO2 emissions. Moreover, quantile Granger causality results confirm the previous findings of QQ regression and verify the existence of bidirectional causal nexus between urban agglomerations and CO2 emissions in the majority of the lower, middle and upper quantiles in our selected top ten countries except for Kuwait. However, the unidirectional causal relationship also exists for several countries for extreme lower, middle and extremely higher quantiles. Our findings extend the previous work on agglomeration-environment nexus by determining the asymmetric magnitude of linkage between these two variables demanding cautious and individual-focused policies for urban planning and environmental sustainability.