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This study examines the short-run and long-run impact of macroeconomic variables such as industrial production index, inflation, exchange rate, interest rate, foreign direct investment and trade balance, on KSE 100 index and sectorial stock indices under bearish, bullish and normal states of the stock market prices. Moreover, we take into account the effect of three crises observed from 2005 to 2009.

This study uses quantile autoregressive distributed lag (QARDL) model for examining the short-run and long-run effect across various quantiles of the dependent variables and compare its' results standard autoregressive distributed lag (ARDL) model.

ARDL estimates indicate that, in the long-run, industrial production index, trade balance and foreign direct investment significantly affect stock prices. These findings remain same when three crises have been taken into consideration. In addition, estimates from QARDL model indicate that, in the short-run, the effect of exchange rate, interest rate, consumer price index and foreign direct investment, varies across bearish, bullish and normal states of the overall stock prices. Moreover, the short-run findings for Auto Assembler, Cement, Commercial Banks sector are consistent with overall stock indices, whereas other sectors, such as, Oil and Gas and Power Generation and distribution are asymmetrically affected by all macroeconomic variables. In the long-run, the effect of all macro-variables varies across different states of the stock markets except industrial production index for Auto Assembler sector, Oil and Gas sector and composite index of KSE 100 index.

We take into account the effect of three crises observed from 2005 to 2009 and also examine the macroeconomic effect across bullish, bearish and normal states of the sectorial stock indices and composite index of Pakistan stock exchange. Finally, we use novel approach, called QARDL model, which has several advantages over other techniques.

The purpose of this study is to quantify the impact of electricity power outages on the local housing market in South Africa.

This study uses the autoregressive distributive lag (ARDL) and quantile autoregressive distributive lag (QARDL) models on annual time series data, for the period 1971–2014. The interest rate, real income and inflation were used as control variables to enable a multivariate framework.

The results from the ARDL model show that real income is the only factor influencing housing price over the long run, whereas other variables only have short-run effects. The estimates from the QARDL further reveal hidden cointegration relationship over the long run with higher quantile levels of distribution and transmission losses raising the residential price growth.

Overall, the findings of this study imply that the South African housing market is more vulnerable to property devaluation caused by power outages over the short run and yet remains resilient to loadshedding over the long run. Other macro-economic factors, such as real income and inflation, are more influential factors towards long-run developments in the residential market.

To the best of the authors’ knowledge, this is the first study to examine the empirical relationship between power outages and housing price growth.

This paper aims to explore the quantile-specific short- and long-term effects of economic policy uncertainty (EPU) on the efficiency of the green bond market.

This study examines the long-term cointegration relationship and the short-term fluctuation relationship of EPU, WTI crude oil price (WTI) and European Union Allowances price (EUA) with the green bond market efficiency (GBE) using the quantile autoregressive distributed lag method. Additionally, the authors analyze the differences before and after the Covid-19 pandemic.

EPU has a significant positive impact on the GBE before the outbreak. However, during the crisis period, the impact of EPU and WTI was greatly weakened, whereas the impact of EUA was strengthened.

This paper demonstrates the dynamics of GBE and its influencing factors under different periods. The findings provide insights for market participants and policymakers to gain a clearer understanding of the green bond market.

This paper extends the study of green bonds by quantifying the GBE and elucidating the nonlinear relationship between efficiency and independent variables at different quantiles over different periods.

Increased trapped heat in the atmosphere leads to global warming and economic activity is the primary culprit. This study proposes the nonlinear impact of economic activity on cooling degree days to develop a climate Kuznets curve (CKC). Further, this study explores the moderating role of higher education and renewable energy in diminishing the climate-altering effects of economic activity.

All the selected BRICS economies range from 1992 to 2020. The CKC analysis uses a distribution and outlier robust panel quantile autoregressive distributed lagged model.

Results confirmed a U-shaped CKC, controlling for population density, renewable energy, tertiary education enrollment and innovation. The moderating role of renewable energy and education can be exploited to tackle the progressively expanding climate challenges. Hence, education and renewable energy intervention can help in reducing CKC-based global warming.

This study highlighted the incorporation of climate change mitigating curriculum in education, so that the upcoming economic agents are well equipped to reduce global warming which must be addressed globally.

This study is instrumental in developing the climate change-based economic activity Kuznets curve and assessing the potential of higher education and renewable energy policy intervention.

Energy use occupies an important place among the service activities offered to tourists that guide the tourism industry. The realization of basic needs such as heating, cooling, ventilation, lighting and decontamination in these enterprises are among the important factors that directly affect energy use. In order to obtain the energy needed for the sustainability of services at a more affordable cost, renewable energy sources should be put into operation. In this direction, it makes it more advantageous for businesses in the tourism sector to invest by turning to renewable energy sources in order to maintain their activities more economically. In this context, the main purpose of the study carried out in this part of the book is to reveal the latest developments in the field of evaluation of renewable energy sources in tourism enterprises. Bibliometric analysis was carried out by using the Web of Science (WoS) database in the research and with the findings obtained, it was concluded that the field is new and up-to-date and needs to be studied more. When looking at the WoS categories of studies titled renewable energy in tourism enterprises; it was concluded that more energy fuel, green sustainable science technology, science themes were given weight. According to the network analysis, the most cited authors and countries' densities were determined and the intensive expressions in the network keywords in their studies titled renewable energy in tourism enterprises are renewable energy, renewable energy sources, sustainable tourism, sustainability, carbon dioxide (CO₂) emissions, green marketing, blue economy, and energy efficiency.

The study's objectives are to conduct a comprehensive review of existing knowledge, thoroughly understand the present state of green finance, identify emerging research trends, perform content analysis and offer valuable guidance for advancing this field.

Data has been collected by selecting highly indexed databases, Scopus and Web of Science. These databases are well-known repositories of academic papers, journals and other scholarly publications related to various fields of study. This research uses the PRISMA methodology for conducting a structured literature review and employs a bibliometric approach to summarize the findings of the previous studies. “R” studio and Biblioshiny are used to clean the data and visualize the results. The TCCM framework is utilized to propose potential avenues for future research in the domain of green finance.

The research uncovers the potential areas in the domain of green finance for future work, encompassing green bonds, the green economy, connectivity, forces, constraints and sustainable development. Furthermore, this process enhances the theoretical underpinnings of scholarly investigations within the discipline by succinctly synthesizing and evaluating preexisting literature. This contribution could facilitate more informed and focused research endeavors in green finance.

The research findings have practical implications for researchers, practitioners, regulators, legislators, issuers and investors involved in green finance. The results can take initiatives to improve practices related to issuing and pricing green financial products and enhance the understanding of interconnectedness within the field.

This ground-breaking research sheds light on various emerging areas by taking a new approach, including the most widely read articles, authors and journals and the broader conceptual and intellectual framework. That includes finding and expanding original research streams, summarizing the most seminal works, and suggesting new research pathways.

Motivated by the 2030 UN Sustainable Development Goals (SDG-7: clean and affordable energy, SDG-8: sustainable economic growth, SDG-13: climate action), this study aims to investigate the role of economic complexity, disaggregated energy consumption in addition to economic growth, financial development, globalization and urbanization on the ecological footprint of United Arab Emirates (UAE).

This study adopts unit root tests (with and without a structural break), autoregressive distributed lag (ARDL) bounds test and dynamic ordinary least squares.

The results obtained from the ARDL model suggest that economic complexity (EC), nonrenewable energy and economic growth increase the ecological footprint in both the short and long run, thus deteriorating the environment. However, renewable energy and urbanization reduce the ecological footprint in UAE during the two periods, thus improving environmental quality. Globalization and financial development have different influences on ecological footprint during these periods. These findings are robust to other estimation techniques.

Based on these results, this study offers significant policy implications such as increasing renewable energy supply, particularly solar energy and aligning the product manufacturing structure and complexity toward producing environmentally friendly products which can be used to realize the nation’s agenda of reducing fossil fuels consumption to 38% by 2050 and achieving sustainable environment and growth.

This study provides an empirical attempt to investigate the influence of EC and renewable and nonrenewable energy on the ecological footprint of the UAE.

This paper aims to model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016.

The authors use both the linear (symmetric) autoregressive distributed lag (ARDL) by Pesaran et al. (2001) and non-linear (asymmetric) ARDL by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models.

The results indicate that the strength of this relationship varies across sectors, albeit asymmetric and breaks. The authors identify two structural breaks that occur in 2008 and 2010/2011, which coincidentally correspond to the global financial crisis and the Arab spring (Libyan shutdowns), respectively. Moreover, the authors observe strong support for asymmetry and structural breaks for some sectors in the reaction of sector returns to movement in oil prices. These findings are robust and insensitive when considering different oil proxies. While further extensions can be pursued, the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling this nexus.

This study is one of the very few studies that have investigated the sectoral behaviour of stocks to oil price shocks, particularly in Nigeria. This paper contributes to the oil stock literature using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and stock returns.

This study aims to investigate the long-run relationship between financial inclusion and agricultural growth in Pakistan for the period of 1960–2018.

The autoregressive distributed lag (ARDL) approach, the Johansen co-integration test and the dynamic ordinary least squared (DOLS) method are used for the evaluation.

The results show that in both short- and long run, domestic credit has a significantly negative impact on the agricultural growth, while broad money and cropped area positively affected the agricultural growth in Pakistan in both cases.

The government and policymakers need to develop strategies that bring together agriculturalists on a single platform so that the government can clearly distinguish the interests of these farmers and can obtain precise information for allocating agricultural expenditure and easing access to credit for small-scale agriculturalists.

This is the first study to evaluate the impact of financial inclusion on the agricultural growth in Pakistan by using different econometric techniques, including the ARDL-bound approach, Johansen co-integration test and DOLS method.