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This chapter examines the nexus between the between tourism growth and income inequality in the top 10 tourist destinations in the world by using the advanced econometric technique namely quantile-on-quantile (QnQ). This approach combines the two approaches, that is, the nonparametric estimation and quantile regression and regresses the quantile of the tourism growth onto income inequality quantiles, thus enabling the effect of the income inequality on across different conditional tourism growth distribution. It also allows to explain a comprehensive picture of the overall interdependence and nonlinear relationship between the examined variables. The result from QnQ approach shows a negative association between income inequality and tourism growth, however, the country-specific analysis shows wide variations within and across different quantiles of variables. Notably, on the one hand, a strong negative association between the variables is found in China, France, Spain, Italy, Russia and the USA implying that tourism expansion minimizes the income inequality. On the other hand, a strong positive association is noted in Germany, Turkey, Mexico and the UK, which means that growth in tourism widens the income inequality. These outcomes provide important policy direction for tourism management in the respective countries.

In the new global economy, environmental degradation is still among the crucial struggles braving policymakers. The intention of the current analysis, therefore, is to investigate the asymmetric impact of energy use, trade openness, population changes and urbanization, on the ecological footprint (EF) in four ASEAN countries by using time span data extending from 1972 to 2018.

The stationarity of the variables was first demonstrated by using a quantile autoregression unit root test. Then the cointegration relationship among quantiles was verified. In the third step, this study investigated the pattern of causality in quantiles which allowed them to model any locational asymmetry in such a relationship. In the final part of the paper, the asymmetric quantile approaches the methods adopted to address the ways in which the considered variables impacted on the EF.

The outcomes demonstrated that the estimated coefficient of the variables was generally found significant and in line with the expected impact sign. Likewise, locational asymmetry was detected from the fact that the considered variables at the upper tails did not operate in the same way as those in the lower ones. In this case, the results suggest that a rise in energy consumption, as well as a negative shock to economic growth and/or trade openness, all diminish environmental quality. In contrast, promoting economic growth, a positive shock to trade openness, and human capital reduce environmental degradation.

As far as is known, the current study among the early attempt to explore the asymmetric impact of trade openness, energy use, population changes and urbanization, on the EF in the ASEAN countries.

The purpose of this study, the nonlinear relationship between the real estate market and the stock market was investigated in Iran. For this intent, the monthly data from 2012:4 to 2022:5 is used.

In this study, the quantile-on-quantile estimation method is used, which is a combination of the nonparametric estimation methods and the quantile regression.

The research results show that, in the low quantiles, the effect of stock market return on the housing market return is negative or zero. In fact, in this situation, the increasing returns in the stock market will shift part of the financial resources of the economy to the market and create stagnation or even negative returns in the housing market. This situation is seen more strongly in some other quantiles, including the 0.25 and 0.75 quantiles; in contrast, the effect of high quantiles of stock market returns is positive on the housing market.

It seems that the demand in the housing market increase in a situation where the returns of the stock market are growing, and the market is in a bullish condition, and this causes an increase in the price and returns in this market. In addition, the results show that the effect of stock market returns on capital market returns is asymmetric and nonlinear.

This paper investigates the impact of global sentiment and various coronavirus disease 2019 (COVID-19)-related media coverage news (Media-Hype index; Panic Index; Media Coverage Index, infodemic index and coronavirus statistics) on the dynamics of bitcoin returns during the COVID-19 pandemic using an asymmetric framework.

The authors use an asymmetric framework based on quantile regression (QR) and quantile-on-quantile regression.

QR results show that COVID-19 panic news negatively affects bitcoin market returns at times of extreme bearish. However, COVID-19 bullish sentiment negatively impacts bitcoin market returns during bullish market conditions. Quantile-on-quantile approach's (QQA) empirical results show that the effects of COVID-19-related news on bitcoin returns were heterogeneous, mainly negative and varied across quantiles.

The authors find some significant differences regarding the impact of news on bitcoin return dynamics compared to stock markets, suggesting the safe-haven role of bitcoin against stock during the ongoing epidemic.

The authors find some significant differences regarding the impact of news on bitcoin return dynamics compared to stock markets, suggesting the safe-haven role of bitcoin against stock during the ongoing epidemic.

This study contributes to understanding the dynamics of bitcoin returns using various COVID-19 media news.

The purpose of the research is to analyze the impact of world uncertainty and pandemic uncertainty on Islamic financial markets. For representing Islamic financial markets four different Islamic indices (DJ Islamic index, DJ Islamic Asia–Pacific index, DJ Islamic-Europe index and DJ Islamic-US) are taken.

The study employs quantile-on-quantile regression approach to see the overall dependence structure of variables based on quarterly data ranging from 1996Q1 to 2020Q4. This technique considers how quantiles of world uncertainty and pandemic uncertainty asymmetrically affect the quantiles of Islamic stocks by giving an appropriate framework to apprehend the overall dependence structure.

The findings of the study confirm a strong negative impact of world uncertainty and world pandemic uncertainty on regional Islamic stock indices but the strength of the relationship varies according to economic conditions and across the regions. However, the world pandemic effect remains the same and does not change. Conversely, pandemic uncertainty has a larger effect on Islamic indices as compared to world uncertainty.

Our findings have significant implications for investors and policymakers to take proper steps before any uncertainty arise. A coalition of the central bank, government officials and investment bank regulators would be needed to tackle this challenge of uncertainty.

To the best of the authors' knowledge, none of the current works has considered the asymmetric impact of world and pandemic uncertainties on Islamic stock markets at both the bottom and upper quantiles of the distribution of data.

Might the impact of the financial stress on exchange markets be asymmetric and exposed to regime changes? Departing from the existing literature, highlighting that the domestic and foreign financial stress in terms of money market have substantial effects on exchange market, this paper aims to investigate the impacts of the bond yield spreads of three emerging countries (Mexico, Russia, and South Korea) on their exchange market pressure indices using monthly observations for the period 2010:01–2019:12. Additionally, the paper analyses the impact of bond yield spread of the US on the exchange market pressure indices of the three mentioned emerging countries. The authors hypothesized whether the negative and positive changes in the bond yield spreads have varying effects on exchange market pressure indices.

To address the research question, we measure the bond yield spread of the selected countries by using the interest rate spread between 10-year and 3-month treasury bills. At the same time, the exchange market pressure index is proxied by the index introduced by Desai et al. (2017). We base the empirical analysis on nonlinear vector autoregression (VAR) models and an asymmetric quantile-based approach.

The results of the impulse response functions indicate that increases/decreases in the bond yield spreads of Mexico, Russia and South Korea raise/lower their exchange market pressure, and the effects of shocks in the bond yield spreads of the US also lead to depreciation/appreciation pressures in the local currencies of the emerging countries. The quantile connectedness analysis, which allows for the role of regimes, reveals that the weights of the domestic and foreign bond yield spread in explaining variations of exchange market pressure indices are higher when exchange market pressure indices are not in a normal regime, indicating the role of extreme development conditions in the exchange market. The quantile regression model underlines that an increase in the domestic bond yield spread leads to a rise in its exchange market pressure index during all exchange market pressure periods in Mexico, and the relevant effects are valid during periods of high exchange market pressure in Russia. Our results also show that Russia differs from Mexico and South Korea in terms of the factors influencing the demand for domestic currency, and we have demonstrated the role of domestic macroeconomic and financial conditions in surpassing the effects of US financial stress. More specifically, the impacts of the domestic and foreign financial stress vary across regimes and are asymmetric.

This study enriches the literature on factors affecting the exchange market pressure of emerging countries. The results have significant economic implications for policymakers, indicating that the exchange market pressure index may trigger a financial crisis and economic recession.

This study examines the inter-linkages between Bitcoin prices and CEE stock markets (Hungary, the Czech Republic, Poland, Romania and Croatia).

The dynamic contemporaneous nexus has been analyzed using both the multivariate DECO-GARCH model proposed by Engle and Kelly (2012) and quantile on quantile (QQ) methodology proposed by Sim and Zhou (2015). Our study is implemented using the daily data spanning from 6 September 2012 to 12 August 2019.

First, the findings show that the average return equicorrelation across Bitcoin prices and CEE stock indices are positive, even though it is found to be time-varying over the research period shown. Second, the Bitcoin-CEE stock market association has positive signs for most pairs of quantiles of both variables and represents a rather similar pattern for the cases of Poland, the Czech Republic and Croatia. However, a weaker and primarily negative connectedness is found for Hungary and Romania, respectively. Furthermore, the interconnectedness between the co-movements in the Bitcoin market and stock returns changes significantly across quantiles of both variables within each nation, indicating that the Bitcoin-stock market relationship is dependent on both the cycle of the stock market and the nature of Bitcoin price shocks.

The evidence documented in this study has significant implications for divergent economic agents, including global investors, risk managers and policymakers, who would benefit from a comprehensive knowledge of the Bitcoin-stock market relationship to build efficient risk-hedging models and to conduct appropriate policy reactions to information spillover effects in different time horizons.

This paper is the first study employing both the multivariate DECO-GARCH model and QQ methodology to shed light on the nexus between Bitcoin prices and the stock markets in CEE countries. The DECO model uses more information to compute dynamic correlations between each pair of returns than standard dynamic conditional correlation (DCC) models, declining the estimation noise of the correlations. Besides, QQ approach allows us to capture some nuanced features of the Bitcoin-stock market relationship and explore the interdependence in its entirely. Therefore, the main contribution of this article to the related literature in this field is significant.

本研究旨在探討比特幣的價格與中東歐股市(匈牙利、捷克共和國、波蘭、羅馬尼亞和克羅地亞) 之相互聯繫.

研究使用恩格爾與凱利(2012)(Engle and Kelly (2012)) 提出的多變量DECO-GARCH模型及Sim 與Zhou(2015)(Sim and Zhou ( 2015)) 研製的分位數-分位數方法來分析動態同期的聯繫。我們的研究使用由2012年9月6日至2019年8月12日期間取得的每日數據來進行.

首先、研究結果顯示、跨比特幣價格與中東歐股價指數的平均回報當量關聯是正相關的，即使在研究期間被發現是隨時間而變化的。第二、比特幣與中東歐股市之聯繫在大多數兩變數分位數對而言出現正相關跡象，而且，這聯繫在波蘭、捷克共和國及克羅地亞而言表現一個頗相似的模式。唯就匈牙利而言、這聯繫則較弱、而羅馬尼亞則主要是負聯繫。研究結果亦顯示: 比特幣市場內的聯動與股票回報間之內在關聯會在每個國家內跨兩個變數的分位數而顯著地改變，這顯示比特幣-股市關係是取決於股市的週期和比特幣價格衝擊的本質.

本研究所記載的證據、對不同的經濟行為者而言極具意義 (這包括國際投資者、風險管理經理和政策制定者)，因他們會受惠於對比特幣-股市關係的全面認識，他們可建立有效的風險對沖模型、及在不同時間範圍對資訊溢出效應進行適當的政策反應.

本文為首個研究使用多變量DECO-GARCH模型和分位數-分位數(QQ)方法、來解釋比特幣價格與中東歐國家之股市的關係。這DECO模型使用比標準動態條件關係模型更多資訊，來計算每對回報間之動態關係，這能減少估測雜訊，而且，QQ方法讓我們可以取得比特幣-股市關係的一些細微特徵及全面地探索其相互依賴性。因此，本文的主要貢獻是在這學術領域內有關的文獻上.

This study aims to investigate the relationship between stock markets, environmental, social and governance (ESG) factors and Shariah-compliant in an integrated framework.

The authors employ the multivariate factor stochastic volatility (mvFSV) framework to extract the volatility of the different sectoral indices. Based on this evidence, the authors employ the quantile vector autoregressive (QVAR) approach to examine the dynamic spillover connectedness among the aforementioned indices.

The study emphasizes the following major findings: (1) significant time-varying spillover connectedness across quantiles, (2) bidirectional and asymmetric spillover effect among the ESG index and the other sectoral indices, (3) the strength of spillover connectedness is time-varying across quantiles, (4) based on the perspective of portfolio optimization, ESG market is a significant strong forecasting contributor to conventional and Shariah-compliant markets, (5) overall, the findings point out serious quantile pass-through effect among ESG index and the other sectoral indices during the COVID-19 health crisis.

This study extends the previous literature in the following ways. First, to the best of the researchers’ knowledge, none of the existing studies have investigated the relationship between stock markets, ESG factors and Shariah-compliant in an integrated framework. Second, this study extends the previous scholarships by applying the mvFSV. Third, the authors propose a new rolling version to estimate dynamic spillovers, namely the rolling-window quantile VAR method. This approach provides a great advantage in computing the dynamics of return and variance spillover between variables in terms not only of the overall factor but also of the net (pairwise) aspect.

Given the evolving market integration, this study aims to explore the connectedness of 12 real estate investment trusts (REITs) during the COVID-19 period.

The connectedness of 12 REITs was examined by considering three sample periods: full period, COVID peak period and COVID recovery period by using the quantile vector autoregressive (VAR) approach.

The findings ascertain that REIT markets are sensitive to COVID, revealing significant connectedness during each sample period. The USA and The Netherlands are the major shock transmitters; thus, these countries are relatively better options for the predictive behavior of the rest of the REIT markets. In contrast, Hong Kong and Japan are the least favorable REIT markets with higher shock-receiving potential.

The study recommends implications for real estate industry agents and investors to evaluate and anticipate the direction of return connectedness at each phase of the pandemic, such that they can incorporate those global REITs less vulnerable to unplanned crises. Apart from these implications, the study is limited to the global REIT markets and only focused on the period of COVID-19, excluding the concept of other financial and health crises.

This study uses a novel approach of the quantile-based VAR to determine the connectedness among REITs. Furthermore, the present work is a pioneer study because it is targeting different time periods of the pandemic. Additionally, the outcomes of the study are valuable for investors, policymakers and portfolio managers to formulate future development strategies and consolidate REITs during the period of crisis.

Since financial sector plays a critical economic role in Hong Kong, the current research aims to comprehensively analyze the association between financial development and economic growth in the country to draw correct conclusions about the impact that financial sector's development has on the growth of the economy. This requires both using of more comprehensive data that includes all or nearly all elements of the country's financial sector and utilizing advanced econometrics techniques to provide more reliable evidence based on the findings. In the study, both issues have been addressed more academically to aid the relevant authorities better.

This study empirically examines the financial development-economic growth nexus in Hong Kong employing data covering 1980–2019. The quantile-on-quantile (QQ) approach of Sim and Zhou (2015) is utilized to investigate certain subtle aspects of the association linking financial development and economic growth. In addition, the authors benefit from applying the nonlinear Granger causality test of Diks and Panchenko (2006) to assess the variables' nexus in a nonlinear manner.

In contrast to the evidence of a unidirectional linkage documented in many related studies, the empirical findings suggest that a bi-directional relationship exists between financial development and economic growth for Hong Kong. This is a helpful input for the relevant policymakers and implies that they can set appropriate policies and regulations to balance financial development and economic growth in this country.

The originality of this study can be divided into two parts. Methodologically, unlike past studies that utilized mostly linear and parametric methods, the paper contributes to the literature by applying the more robust nonparametric and nonlinear methodologies. Theoretically, most researchers have used various financial development indicators, which led to very different conclusions. Therefore, this study attempts to resolve this deficiency in the literature by using a more comprehensive index for financial development.