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This paper aims to contribute to the clarification of whether the dependence and causality between oil and the macrofundamentals change across different quantiles of the distribution function.

Within the context of an asymmetric quantile approach, we drop the assumption that variables operate at the upper tails of the distribution in the way that they operate at the mean.

Our innovative approach indicates that the response of oil prices not only differs according to the underlying source of the variables shock but also differs across the quantiles.

Although a number of recent studies are closely related to our present research, our novel findings offer some important insights that foreshadow the empirical results. The current research addresses to answer the following questions, in sequence: (i) Is there any extreme value dependence between the crude oil and macroeconomic variables? If yes, (ii) is the dependence symmetric or asymmetric? Finally, (iii) can this dependence be driven by the phases of the economic cycle?

This paper aims to investigate the nonlinear dynamics in the effects of oil price shocks on the exchange rate for a sample from the Group of Twenty (G20) over the period 1994:1-2019:1.

Using monthly time series data covering the period1994:1-2019:1, the author first use the non-parametric triples test of Randles et al. (1980) to ascertain the existence of asymmetric properties in the sample of exchange rates. Then the author used the nonlinear ARDL cointegration approach developed by Shin et al. (2014) to examine the reaction of these exchange rates to the oil price shocks.

This study has identified significant evidence that the exchange rate is asymmetrically distributed, with the effect that high appreciation of the exchange rate is followed by slower depreciation. The NARDL results support such asymmetry even more strongly because in the test the exchange rate is shown to react differently in the long term to positive and negative shocks in oil prices. Another major finding was that the speed of adjustment differed over the sample, as the cumulative dynamic multipliers effect highlighted.

This change in direction and the employment of non-linear technique can be to obtain better insight into the model specification, which the author believes, will not only enhance the findings in the literature but also enhance forecasting and decision-making.

A practical implication of this change is the possibility that policymakers and participants concerned with exchange rate stability should intervene in the market to alleviate the unfavourable impact of oil price shocks on the exchange rate.

Addressing this nonlinear dynamic in the effects of oil price shocks on the exchange rate have at least the following two important reasons: asymmetry and regime change are types of nonlinearities that affect the market dynamics, especially, over marked sample period with such financial crises as the global financial crises of 2007, thereby violating the linear models. Adopting an asymmetric cointegration technique permits to incorporate cointegrated positive and negative components of the considered series.

This study explores the interconnectedness and complexity of risk-varied climate initiatives such as green bonds (GBs), emissions trading systems (ETS) and socially responsible investments (SRI). The analysis covers the period from September 2011 to August 2022, using six indices: three representing climate initiatives and three indicating uncertainty.

To achieve this, the study first examines dynamic lead-lag relations and correlation patterns in the time-frequency domain to analyse the returns of the series. Additionally, it applies an innovative approach to investigate the predictability of uncertainty measurements of climate initiatives across various market conditions and frequency spillovers in the short, medium and long run.

The findings indicate changing relationships between the series, increased linkages during turbulent market periods and strong co-movements within the network. The ETS is recommended for diversification and hedging against uncertainty indices, whereas the GB may be suitable for long-term diversification.

This study highlights the role of climate initiatives as potential hedges and contagion amplifiers during crises, with implications for policy recommendations and the asymmetric effects on market connectedness.

The paper answers questions that previous studies have not and contributes to the literature regarding financial risk management and social responsibility.

This paper aims to assess the interaction between environmental challenges and policy interventions in shaping housing prices. It emphasises the need to understand how policy interventions and environmental conditions can disproportionately affect housing affordability, population growth and building density, especially for vulnerable communities.

The study uses a panel quantile ARDL regression model to thoroughly investigate the asymmetric impact on a sample of 16 UK cities spanning the period 2000–2023.

The study reveals that pollution significantly impacts house prices, with cleaner areas experiencing faster price changes. Cleaner air pollution has a greater impact on property prices in cities with cleaner air. Climate policies and superior environmental technologies also influence consumer purchases. Addressing affordability has little short-term effect on house values, but building activity temporarily affects pricing. Investment in clean technology and climate action legislation may boost house prices and attract environmentally conscious individuals.

Based on these findings, policymakers seeking equitable and sustainable housing outcomes should consider these finding. It proposes evaluating city environmental features, eliminating environmental inequities, encouraging clean technology, balancing affordability and environmental concerns, monitoring and lowering pollutants and supporting sustainable building practices.

To the best of the author’s knowledge, this study is the first to analyse how environmental conditions, regulations on environmental action and demand-supply affect housing prices in 16 major UK cities. The connection between these factors is also examined in 8 cities with high and 8 cities with extremely low pollution. The research seeks to explore how environmental issues affect policy interventions to promote sustainable and equitable housing development. The asymmetric impact is examined using a panel quantile ARDL regression model. If property values are asymmetrical, the government should enforce severe environmental laws.

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.

This study seeks to determine in some detail whether the state of the economic cycle matters in considering the effects of fiscal policy shocks on output.

This issue leads us to two primary objectives: to define the economic cycle measuring the gap with the unobserved component model with a smoother trend, which can be used efficiently to generate gap measures for use in real-time decision-making and avoids the criticisms of measures based on contentious structural models; and to look empirically at the fiscal policy stance over the phases of the cycle, bearing in mind the short time variation and smooth change between the cycle regimes.

This paper provides evidence that the fiscal policy rule seems to operate with varied coefficients depending on whether the transition variable is below or above the estimated threshold value.

The asymmetric response gives policymakers the impetus to reconsider the fiscal policy framework because of specific circumstances, such as shocks that can dramatically affect the nominal features of the business cycle. Put differently, stable and moderate fiscal policies would at least not contribute to cyclical fluctuations, and therefore would be better than what we have typically experienced. There would, therefore, seem to be a distinct need to address the properties of economic cycles under different fiscal policy rules.

This study aims to investigate the dynamic relationship between renewable and non-renewable energy sources on the economic growth of eight countries, the capital stock and labour force being used as control variables in each case. Questions that need to be asked include the following: Is there is an asymmetric and, hence, a non-linear relationship between variables? If yes, how does economic growth interact with both renewable and non-renewable energy consumption (EC)? How different are these relationships in the countries highly rated in the performance of renewable EC compared to those lowly rated?

This paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables.

A newly developed asymmetric panel quantile approach suggests that EC has a significant effect on economic growth in both directions of shocks as well as for the considered sample. The results further support the findings in recent literature on renewable energy deployment, given the importance of renewable EC for economic growth with the increased levels of renewable EC, although the initial investments may have a negative effect on economic growth for some countries.

This study contributes to the literature in twofold. Firstly, it aims to contribute to the ongoing debate in literature by incorporating both renewable and non-renewable energy resources in the production function with labour and capital to test their asymmetric impact on economic growth. Secondly, this paper uses asymmetric quantile-based methods to extract possible asymmetric and, hence, non-linear relationships between the underlying variables. Another point that should be emphasised in this study is the need for studies analysing economic growth and EC for a sample of G20 countries based on a comparative view for the renewable and non-renewable EC in literature.

This paper aims to examine asymmetries in the house price cycle and to understand the dynamic of housing prices, incorporating macroeconomic variables at regional and country level, namely, housing affordability, the unemployment rate, mortgage rate and inflation rate.

To highlight significant differences in the asymmetric patterns of house prices between regions, the STAR model is adopted.

The authors highlight significant differences in the asymmetric patterns of house prices between regions, in which some areas showed asymmetric response over the housing cycle; here the LSTAR model outperforms other models. In contrast, some regions (the South West and the North West) showed symmetric properties in the tails of the cycle; therefore, the ESTAR model was adopted in their case.

Being limited to a few fundamentals, this study opens an avenue for further research to investigate this dynamic using in addition such demand-supply factors as land supply, construction cost and loans made for housing. These findings can also be used to examine whether other models such as ARIMA, exponential smoothing or artificial neural networks can more accurately forecast housing prices.

The present paper aims to highlight housing affordability as a cause of asymmetric behaviour in house prices. Put differently, the authors seek to understand the dynamics of housing prices with other fundamentals incorporating macroeconomic variables in regions and country level data as a means of achieving a more concise result.