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In spite of the certain risk imposed by financial stress on the real economy, the relationship between financial stress and economic activity is complicated and underresearched, meaning that important gaps still remain in the authors’ understanding of this critical relationship. Therefore, the current study aims to answer the significant question regarding whether a stressful financial sector has predictive power on the real sector and vice versa. Hence, the study examines the causal interrelationship between financial stress index (FSI) and economic activity in Luxembourg as a sample country.

In this study, accompanying the time domain Granger causality framework of Hacker and Hatemi-J (2012), the authors utilize the spectral causality technique of Breitung and Candelon (2006), which is based on the study of Geweke (1982) and Hosoya (1991). This method enables the researcher to measure the degree of a particular variation in time series. Moreover, it allows considering the nonlinearities and causality cycles. The authors further apply the recent method of Farné and Montanari (2018) that is a bootstrap framework on Granger-causality spectra, which allows for disambiguation in causalities.

The time-domain approach finds evidence of bidirectional causation between the variables. However, the spectral causality results indicate the causal linkages between the series are only valid under the medium-run frequency. This study’s findings emphasize covering the frequency causality to deliver a more comprehensive picture of the interrelationship between the variables.

There are many studies in this area that examine the nexus between financial stress and economic activity. However, the authors believe this paper is the first study in the context of Luxemburg. The authors focus on this country since its financial sector is designated as the most important pillar for the economy. Thus, a careful and reliable examination of the relationship between the financial sector and economic activity is likely to be of considerable interest to policymakers and researchers in this field.

This paper aims to examine the relationship between exchange rate and oil prices in Algeria over the period 2004Q1–2019Q4.

The nonlinear autoregressive distributed lag method is used to capture the potential asymmetric relationship among oil prices and the exchange rate. Frequency domain spectral Granger causality test is also applied to investigate the causal linkage between the two variables. The wavelet coherence is applied to analyze the evolution of this relationship both in time and frequency domains.

The empirical results reveal evidence of long-run asymmetric effects of oil price on Algeria’s real effective exchange rate (REER), implying that an increase in oil price causes a real exchange rate to appreciate, while a decrease in oil price leads to a real exchange rate to depreciate. More specifically, it is found that the impact of negative oil price shocks is higher than the one associated with positive shocks. The spectral Granger causality results further indicate that there is unidirectional causality running from oil price to REER in both medium and long run. The wavelet coherence findings provide evidence of some co-movement between the REER and oil price and point out that the oil price is leading real exchange rate in the medium and long terms.

This study contributes to the literature by investigating the asymmetric impact and the time domain causal linkage between oil price fluctuations and real exchange rate in Algeria.

The world is nowadays facing major environmental damage and climate change everywhere. Carbon dioxide emissions are major causes of such change. It is in this respect that the current study provides a fresh insight into the dynamic nexus between energy consumption (EC), economic growth (EG) and CO₂ emissions in Algeria, as it is considered as one of the top CO₂ emitters in Africa.

The authors use the wavelet approaches and Breitung and Candelon (2006) causality test to gauge the association between EC, EG and CO₂ emissions over the period 1971–2018. Specifically, this study implements the wavelet power spectrum (WPS) to identify the power and variability of each variable at different time scales. The wavelet coherence, phase differences and partial wavelet coherence are also used to assess the co-movement and lead lag relationship between economic growth, energy consumption and CO₂ emissions over different time scale. Finally, Breitung and Candelon (2006) causality test is used to find the causality among variables.

The wavelet power spectrum results indicate that economic growth, energy consumption and CO₂ emissions share common strong variance in the medium and long run. Furthermore, the wavelet coherence results suggest that there is a significant co-movement between EG and CO₂ emissions, and EG is the leading variable for CO₂ emissions and EC. The results also unveil that both EG and EC cause CO₂ emissions both in short and long run. The results suggest that Algeria should take suitable measures towards the promotion of renewable energy sources.

The present empirical study filled the literature gap of applying the wavelet approach and frequency domain spectral causality test to examine this relevant issue for Algeria.

Accelerating the green economy’s transition is a practical means of lowering emissions and conserving energy, and its effects on the greenhouse effect merit careful consideration. Growing environmental deterioration has compelled decision-makers to prioritize sustainability alongside economic growth. Policymakers and the business community are interested in green investment (GRE), but its effects on social and environmental sustainability are still unknown. Based on this, this study aims at looking into the time-frequency interplay between GRE and carbon dioxide emissions and assessing the impacts of economic growth, financial globalization and fossil fuel energy (FUE) usage on this nexus in Vietnam across different time and frequency domains.

The authors employ continuous wavelets, cross wavelet transforms, wavelet coherence, Rua’s wavelet correlation and wavelet-based Granger causality tests to capture how the domestic variance and covariance of two-time series co-vary as well as the co-movement interdependence between two variables in the time-frequency domain.

The results shed new light on the fact that GRE will increase the levels of environmental quality in Vietnam in the short and medium run and there is a bidirectional causality between the two indicators across different time and frequencies. In addition, when the authors observe the effect of economic growth, financial globalization and fossil fuel energy consumption on this interplay, the findings suggest that, in different time and frequencies, any joined positive change in these indicators will move the CO₂ emissions-GRE nexus.

Policymakers and governments can greatly benefit from this topic by utilizing the function of economic institutions in capital control of GRE and CO₂ emissions and modifying the impact of GRE on the greenhouse effect by accelerating the green growth of economic industries.

The current work contributes to the current literature on GRE and CO₂ emissions in several dimensions: (1) considering the sustainable development in Vietnam, by employing a new single-country dataset of GRE index, this paper aims to contribute to the growing body of research on the factors that influence CO₂ emissions, as well as to provide a detailed explanation for the relationship between GRE and CO₂ emissions; (2) localized oscillatory components in the time-domain region have been used to evaluate the interplay between GRE and CO₂ emission in the frequency domain, overcoming the limitations of the fundamental time-series analysis; (3) the mediation role of economic growth, financial globalization and FUE in affecting the GRE-CO₂ relationship is empirically explored in the study.

1. To improve the causality analysis performance, a novel causality detector based on time-delayed convergent cross mapping (TD-CCM) is proposed in this work. 2. Identify the root cause of plant-wide oscillations in process control system.

A novel causality analysis framework is proposed based on denoising and periodicity-removing TD-CCM (time-delayed convergent cross mapping). We first point out that noise and periodicity have adverse effects on causality detection. Then, the empirical mode decomposition (EMD) and detrended fluctuation analysis (FDA) are combined to achieve denoising. The periodicities are effectively removed through singular spectrum analysis (SSA). Following, the TD-CCM can accurately capture the causalities and locate the root cause by analyzing the filtered signals.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. Simulation studies show that the proposed method is able to improve the causality analysis performance. 3. Industrial case study shows the proposed method can be used to analyze the root cause of plant-wide oscillations in process control system.

1. A novel causality detector based on denoising and periodicity-removing time-delayed convergent cross mapping (TD-CCM) is proposed. 2. The influences of noise and periodicity on causality analysis are investigated. 3. Simulations and industrial case shows that the proposed method can improve the causality analysis performance and can be used to identify the root cause of plant-wide oscillations in process control system.

This study investigates if the causal relationships between the exchange rates and selected inbound markets’ tourism demand are temporary or permanent, and compares market reactions in Türkiye.

Tourism demand is examined with a regional approach, focusing on the geographical markets, namely Europe, Commonwealth of Independent States (CIS) members and Asian countries, as the top inbound tourism markets, in addition to the total number of inbound tourists to Türkiye. Granger, frequency-domain causality, asymmetric Toda–Yamamoto, and asymmetric frequency-domain causality tests were employed to investigate and compare markets on exchange rate–tourism demand relationship for 2008M01-2020M02.

The results indicate that exchange rates affect European tourism demand both in the short and long run. The meaning of this Frequency Domain Causality (FDC) analysis finding shows that the exchange rate has both permanent and temporary effects on European tourists. The relationships are statistically insignificant for CIS members and Asian countries. The exchange rates also permanently affect total inbound tourism demand, but the independent variable has no short-run (temporary) effects on total demand. Asymmetric causality tests confirmed a permanent causality relationship from the positive and negative components of exchange rates to the positive and negative components of European and total tourism demand.

The Granger causality test provides information on the presence of a causal relation, while the FDC test, an extended version of Granger causality, enlightens the short- (temporary) and long-run (permanent) relationships and allows for analyzing the duration of the impact. In addition, asymmetric causality relationships are also investigated in the study. Besides, this study is the first in the literature to examine the relationship between tourism demand and the exchange rate regionally (continentally) for Türkiye.

This study aims to investigate whether changes in consumer interest rate, exchange rate and housing supply have permanent effects on housing inflation in Turkey.

For this purpose, data from 2010M01 to 2020M06 and changes in consumer interest rate, exchange rate, housing supply and housing inflation were used. Relationships between variables are analyzed first by the Granger causality tests and then the conditional frequency domain causality tests. The conditional frequency domain causality test specifically reveals the permanent causality between variables, whether there is a permanent effect.

According to the Granger causality test results, there are causality relationships from changes in the consumer interest rate and exchange rate to housing inflation. However, there is no causality relationship between housing supply and housing inflation. According to the conditional frequency domain causality test results, there is causality for the permanent and mid-term from changes in the consumer interest rate to housing inflation and causality for the mid-term and temporary from changes in the exchange rate to housing inflation. Additionally, it was found that there are causality relationships between changes in the consumer interest rate and changes in the exchange rate.

The first limit of the study is that only 2010M01-2020M06 months can be considered. Because the date that variables started common is 2010M01. Besides, there is a limit in the study in variables used. Many variables, both micro and macro, can be added to affect housing inflation.

Housing inflation is a remarkable issue in Turkey. There is an increase in the number of studies on the subject in recent years. For this reason, the study is trying to contribute by approaching the subject from a different angle. The most important contribution of the study is that it has not been investigated whether the determinants of housing inflation have permanent or temporary effects, which were not done in previous studies. In addition, the method used reveals how many months the effects of changes in exchange rates, consumer interest rates and housing supply on housing inflation last. Based on the findings obtained from the methods, important economic and political implications have been put forward in depth.

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 is to attempt to analyze Granger causality in the frequency domain framework between producers' prices measured by wholesale price index (WPI) and consumers' prices measured by consumer price index (CPI) in the context of India.

Analysis was carried out in the framework of time series and for analysis Johansen and Juselius's maximum likelihood approach for cointegration was applied after confirming that variables are integrated of order one, i.e. I(1) through the Lee and Strazicich unit root test. Finally, Granger causality was tested in the frequency domain by utilizing a recently developed approach of Lemmens et al. over the period January 1957‐February 2009.

The paper finds that CPI Granger cause WPI at a lower, intermediate as well as higher levels of frequency, reflecting very long‐run, intermediate as well as short‐run cycles. By contrast WPI Granger cause CPI at 5 percent level of significance was found at intermediate frequencies, reflecting significant intermediate cycles.

The study reveals that CPI is a leading indicator of producers' prices and inflation (i.e. WPI). This gives an indication that Indian policy analysts ought to control for factors affecting CPI in order to have control on WPI since WPI is used for making various macroeconomic indicators in real terms.

The main contribution of the paper is to show the evidence of bidirectional causality between WPI and CPI. Furthermore, use of a recent approach developed by Lemmens et al. for Granger causality in the frequency domain in this study is also relatively new. To the best of the author's knowledge there is no such study in this area either for developed or developing economy to date.

This paper uses Sims‐Granger causality to examine the causal relationships between (1) the money stock and income, and (2) the reserve money base and the money stock for India. These relationships are empirically investigated so as to determine the role of money in economic activity and the role and channels of monetary policy in a developing economy. Both the conventional regression method used by Sims and the more recent time‐series method developed by Box and Jenkins are utilised in the tests. The results indicate (a) that money does not play a causal role in economic activity while conventional money‐demand functions with income as the right‐hand side variable are vindicated, and (b) there is weak support for the Central Bank's alleged control over the money stock through control over the reserve money base. The differing nature of the results with respect to the two methods adopted point towards the sensitivity of the Sims‐Granger causality test to the type of filtering procedure chosen.