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This study aims to examine the relationship between financial development (FD), financial risk, green finance and innovation related to carbon emissions in the G7 economies.

This quantitative study examines the roles that financial development [FD: Domestic credit to private sector by banks as percentage of gross domestic product (GDP)], economic growth (GDP: Constant US$ 2015), financial risk index (FRI), green finance (GFIN: Renewable energy public research development and demonstration (RD&D) budget as percentage of total RD&D budget), development of environment-related technologies (DERTI: percentage of all technologies) and human capital (HCI: index) have on the environmental quality of developed economies. Based on panel data, the study uses a novel approach method of moments quantile regression as a main method to tackle the issue of cross-sectional dependency, slope heterogeneity and nonnormality of the data.

The study confirms that increasing economic development increases emissions and negatively impacts the environment. However, efficient resource allocation, improved financial systems, and green innovation are likely to contribute to emission mitigation and the overall development of a sustainable viable economy. Furthermore, the study highlights the importance of risk management in financial systems for future emissions prevention.

The study uses a reliable estimation procedure, which extends the discussion on climate policy from a COP-27 perspective and offers practical implications for policymakers in developing more effective emission mitigation strategies.

The study offers policy suggestions for a sustainable economy, focusing on both COP-27 and the G7 countries. Recommendations include implementing carbon pricing, developing carbon capture and storage technologies, investing in renewables and energy efficiency and introducing financial instruments for emission mitigation. From a COP-27 standpoint, the G7 should prioritize transitioning to low-carbon economies and supporting developing nations in their sustainability efforts to address the pressing challenges of climate change and global warming.

In comparison to the literature, this study examines the importance of financial risk for G7 economies in promoting a sustainable environment. More specifically, in the context of FD and national income with carbon emissions, previous researchers have disregarded the importance of green innovation and human capital, so the current study fills the gap in the literature related to G7 economies by exploring the link between the identified variables related to carbon emissions.

This study aims to attempt to investigate the time-varying causality and price spillover effects between crude oil and exchange rate markets in G7 economies during the COVID-19 and Russia–Ukraine crises.

This study uses time-varying Granger causality test and spillover index.

This study finds a time-varying causality between exchange rate returns and oil prices, implying that crude oil prices have the predictive power of the foreign exchange rate markets in G7 economies in their domain. Furthermore, the total spillover index is estimated to fall significantly around COVID-19 and war events. However, this index is relatively high – more than 57% during the first wave of COVID-19 and decreasing slightly during the Russia–Ukraine conflict.

This outcome supports the hypothesis that the majority of the time-varying interaction between exchange rates and oil prices takes place in the short term. As a result, the time-varying characteristics provide straightforward insight for investors and policymakers to fully understand the intercorrelation between oil prices and the G7 exchange rate markets.

First, this study has reexamined the oil–exchange rate nexus to highlight new evidence using novel time-varying Granger causality model recently proposed by Shi et al. (2018) and the spillover index proposed by Diebold and Yilmaz (2012). These approaches allow the author to improve understanding of time-varying causal associations and return transmission between exchange rates and oil prices. Second, compared to past papers, this paper has used data from December 31, 2019, to October 31, 2022, to offer a fresh and accurate structure between the markets, which indicates the unique experience of the COVID-19 outbreak and Russia–Ukraine war episodes. Third, this study analyzes a data set of seven advanced economies (G7) exhibiting significant variations in their economic situations and responding to global stress times.

This paper attempts to assess the economic growth prospects of the BRICS countries and their potential ability to challenge and overtake the G7 countries. Specifically, the purpose of this paper is to answer the following question: Do the BRICS represent a tangible economic threat to surpass the G7, and if so, how?

The authors adopt a qualitative research method based on secondary data sources, such as journal publications, reports published by international organizations, and newspaper and magazine articles. Data from these different sources is compiled and presented in tabular form to provide logical support to the arguments.

Based on the data analysis, the authors conclude that the BRICS have the potential to overtake the G7 in the long run. However, this objective is not likely to be as easy as presumed by economists, since a number of factors and uncertainties may deter the growing economic power and influence of the BRICS.

At present, there is hardly any study or research in the available literature that compares these two blocs of countries. Hence, this comparative study will contribute significantly toward the advancement of future comparative economic studies.

This paper investigates the probable differential impact of the confirmed cases of COVID-19 on the equities markets of G7 and Nordic countries to ascertain possible interdependencies, diversification and safe haven prospects in the era of the COVID-19 pandemic over the short-, intermediate- and long-term horizons.

The authors apply a unique methodology in a denoised frequency-domain entropy paradigm to the selected equities markets (Li et al. 2020).

The authors’ findings reinforce the operability of the entrenched market dynamics in the COVID-19 pandemic era. The authors divulge that different approaches to fighting the pandemic do not necessarily drive a change in the deep-rooted fundamentals of the equities market, specifically for the studied markets. Except for an extreme case nearing the end (start) of the short-term (intermediate-term) between Iceland and either Denmark or the US equities, there exists no potential for diversification across the studied markets, which could be ascribed to the degree of integration between these markets.

The authors’ findings suggest that politicians should pay closer attention to stock market fluctuations as well as the count of confirmed COVID-19 cases in their respective countries since these could cause changes to market dynamics in the short-term through investor sentiments.

The authors measure the flow of information from COVID-19 to G7 and Nordic equities using the entropy methodology induced by the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), which is a data-driven technique. The authors employ a larger sample period as a result of this, which is required to better comprehend the subtleties of investor behaviour within and among economies – G7 and Nordic geographical blocs – which largely employed different approaches to fighting the COVID-19 pandemic. The authors’ focus is on diverging time horizons, and the ICEEMDAN-based entropy would enable us to measure the amount of information conveyed to account for large tails in these nations' equity returns. Furthermore, the authors use a unique type of entropy known as Rényi entropy, which uses suitable weights to discern tailed distributions. The Shannon entropy does not account for the fact that financial assets have fat tails. In a pandemic like COVID-19, these fat tails are very strong, and they must be accounted for.

The study aims to empirically estimate the role of public supports for energy efficiency financing and presents the way forward to mitigate the energy financing barriers that incurred during the COVID-19 crisis.

Using the G7 countries data, the study estimated the nexus between the constructs. Generalized method of moments (GMM) and conventional increasing-smoothing asymptotic of GMM are applied to justify the study findings. Wald econometric technique is also used to robust the results.

The study findings reported a consistent role of public support on energy efficiency financing indicators, during the COVID-19 crisis period. G7 countries raised funds around 17% through public supports for energy efficiency financing, and it raised 4% of per unit energy usage to GDP, accelerated 16% energy efficiency and 24% output of renewable energy sources, during COVID-19. By this, study findings warrant a maximum support from public offices, energy ministries and other allied departments for energy efficiency optimization.

The study presents multiple policy implications to enhance energy efficiency through different alternative sources, such as, on-bill financing, direct energy efficiency grant, guaranteed financial contracts for energy efficiency and energy efficiency credit lines. If suggested policy recommendations are applied effectively, this holds the potential to diminish the influence of the COVID-19 crisis and can probably uplift the energy efficiency financing during structural crisis.

The originality of the recent study exists in a novel framework of study topicality. Despite growing literature, the empirical discussion in the field of energy efficiency financing and COVID-19 is still shattered and less studied, which is contributed by this study.

Analyses factors determining the outflows from unemployment to employment across regions in Poland over the years 1992‐98, employing the concept of the augmented matching function. Explores also the influence of the economic growth and the employment structure of the regional labour markets in Poland. Concludes that the values of outflows from unemployment to employment are closely and positively related to the number of unemployed and the number of vacancies, as well as to the economic growth rate; and that the employment structure of regional labour markets has a strong impact on outflows from unemployment to employment. The more a regional employment structure resembles the structure in European G7 countries, the higher the outflows from unemployment to employment.

This study investigates the nexus between the returns on oil prices (OP) and unemployment (UR) while taking into account the influences of two of the most representative measures of uncertainty, the Baker et al. (2016) and Caldara and Iacovello (2021) indexes of economic policy uncertainty (EP) and geopolitical risks (GP), in the relationship.

The authors use data on the US, Canada, France, Italy, Germany and Japan from January 2000 to February 2022 and the UK from January 2000 to December 2021. The authors then apply the continuous wavelet transform (CWT), wavelet coherence (WC), partial wavelet coherence (PWC) and multiple wavelet coherence (MWC) to examine the returns within a time and frequency framework.

The CWT tracks the movement and evolution of individual return series with evidence of high variances and heterogenous tendencies across frequencies that also align with critical events such as the GFC and COVID-19 pandemic. The WC reveals the presence of a bidirectional relationship between OP and UR across economies, showing that the two variables affect each other. The authors’ findings establish the predictive influence of oil price on unemployment in line with theory and also show that the variation in UR can impact the economy and alter the dynamics of OP. The authors employ the PWC and MWC to capture the impact of uncertainty indexes in the co-movement of oil price and unemployment in line with the theory of “investment under uncertainty”. Taking into account the common effects of EP and GP, PWC finds that uncertainty measures significantly drive the co-movement of oil prices and unemployment. This result is robust when the authors control for the influence of economic activity (proxied by the GDP) in the co-movement. Furthermore, the MWC reveals the combined intensity, strength and significance of both oil prices and the uncertainty measures in predicting unemployment across countries.

This study investigates the relationship between oil prices, uncertainty measures and unemployment under a time and frequency approach.

1. Wavelet approaches are used to examine the relationship between oil prices and unemployment in the G7.

2. We account for uncertainty measures in the dynamics of oil prices and unemployment.

3. We observe a bidirectional relationship between oil prices and unemployment.

4. Uncertainty measures significantly drive oil prices and unemployment co-movement.

5. Both oil prices and uncertainty measures significantly drive unemployment.

Wavelet approaches are used to examine the relationship between oil prices and unemployment in the G7.

We account for uncertainty measures in the dynamics of oil prices and unemployment.

We observe a bidirectional relationship between oil prices and unemployment.

Uncertainty measures significantly drive oil prices and unemployment co-movement.

Both oil prices and uncertainty measures significantly drive unemployment.

The purpose of this paper is to propose and test empirically an inflation model containing permanent and transitory heteroskedastic components for the G7 countries. More specifically, recent evidences from the literature are gathered to construct a model with a heteroskedastic global component capturing comovements amongst G7 economies. Moreover, evidence of asymmetric generalized autoregressive conditionally heteroskedastic effects both in the transitory and in the permanent components are taken into account, and the time‐varying variance of each component allows their influence over the observable inflation to change over time. Out‐of‐sample forecasting exercises are used to test the model validity.

The model is written in state‐space form and estimation is carried out in one step via quasi‐maximum likelihood using the augmented Kalman filter, which allows us to compute smoothed estimates of permanent and of transitory components of inflation rates. Out‐of‐sample forecasts are compared against a random walk (RW) and an autoregressive (AR) model of order one. The significance of the differences in forecast accuracy is tested using the Diebold‐Marino test, the forecast encompassing test, and the Pesaran and Timmermann test.

The proposed model fits the data quite well and has good forecasting capabilities when compared to RW and to AR models of order one. The volatility of the global inflation trend extracted from the model captures the international effects of the “Great Moderation” and of the “Great Recession”. An increase in correlation of inflation for certain country pairs since the start of the “Great Recession” is observed. Moreover, there is evidence of asymmetry in inflation volatility, which is consistent with the idea that higher inflation levels lead to greater uncertainty about future inflation.

This article introduces a new global inflation model with permanent and transitory heteroskedastic components incorporating many recent findings of the literature, and proposes a one step estimation procedure for it. The model fits very well the data and produces good out‐of‐sample forecasts.

Examines the recent turnaround in UK productivity compared to other leading industrial nations and whether the improvement is sustainable, with reference to trade unions. Considers the policies required to further improve productivity, the distribution of the benefits among shareholders and workers, and wider community concerns such as the environment. Concludes that there has been no UK “economic miracle” in the 1980s, and that the signs for continued growth are not encouraging.

The authors investigate the impact of the US stock market on the economies of the BRICS and major industrialized economies (G7).

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. Global vector autoregressive (GVAR) empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.

The authors summarize the results in four points: (1) financial integration variables increase the effect of the US stock market on the BRICS and G7, (2) the US shock produces similar responses in these groups regarding industrial production, stock markets and confidence but different responses regarding domestic currencies: in the BRICS, the authors detect appreciation of the currencies, while in the G7, the authors find depreciation, (3) G7 stock markets and policy rates are more sensitive to the US shock than the BRICS and (4) the estimates point out to heterogeneities such as the importance of industrial production to the transmission shock in Japan and China, the exchange rate to India, Japan and the UK, the interest rates to the Eurozone and the UK and confidence to Brazil, South Africa and Canada.

The results reinforce the importance of taking into account different levels of economic development.

The authors construct the world economy and the vulnerability between economies using three economic integration variables: bilateral trade, bilateral direct investment and bilateral equity positions. GVAR empirical studies usually adopt trade integration to estimate models. The authors complement these studies by using bilateral financial flows.