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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.

The crude oil market plays a key role in addressing the issue of energy economics. This paper aims to detect the causality relationship between the crude oil market and economy based on the financial system.

This paper used the static and dynamic Hatemi-J Bootstrap Toda–Yamamoto and Diebold–Yilmaz connectedness index. The Hatemi-J Bootstrap Toda-Yamamoto approach allows researchers to use nonstationary data and that method is robust to nonnormal distribution and heteroscedasticity. The Diebold–Yilmaz connectedness index model provides researchers to detect the power of connectedness besides linkage direction. The analyzed period is the span from January 3, 2005 to October 3, 2022.

The results show bidirectional causality in the full sample but unidirectional causality before and after the 2008 financial crisis. During the 2008 financial crisis period and the COVID-19 period, there was a bidirectional and unidirectional causality, respectively. The connectedness approach indicates that the crude oil market affects financial stress through investors’ risk preferences.

The Diebold–Yilmaz spillover index model is based on vector autoregression methods with a stationarity precondition. However, some of the five dimensions that constitute the financial stress index (FSI) are nonstationary in level. Therefore, the authors takes the first difference of the nonstationary data.

The linkage between the crude oil market and the FSI provides useful information for investors and policymakers. For instance, this paper indicates that an investor wanted to forecast future value of the crude oil (financial stress) should consider the current and past values of financial stress (crude oil). Moreover, policymaker should consider the crude oil market (FSI) to make a policy proposal for financial system (crude oil market).

Recently, indicators of economic activity levels (economic policy uncertainty, implied volatility index) have begun to be considered to analyze the relationship between energy and the economy but very little is known in the literature about the leading and lagging roles of data in subsample periods and the linkage channel. The other originality of this research is using the new econometric approaches.

The primary objective of the paper is to examine the asymmetric Cointegration and asymmetric causality between financial development and poverty alleviation on annual data in Indian context over the period from 1980 to 2019.

First nonlinearity test by Brooks et al. (1999) is applied to ascertain the nonlinear behavior of the variables used. Once the nonlinear behavior of variables is confirmed, asymmetric and nonlinear unit root tests by Kapetanios and Shin (2008) are applied to check for the order of integration of selected variables. Next, nonlinear autoregressive distributed lag model (NARDL) is employed to analyze the asymmetric Cointegration. Finally, Hatemi-j- asymmetric causality tests is applied to work out the direction of asymmetric causality.

The empirical findings document the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The findings of Wald's test also confirm the presence of asymmetric Cointegration. The asymmetric cumulative dynamic multipliers used to examine the behavior of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator. This result exhibits the robustness of the model. Furthermore, the result emanating from recently introduced asymmetric causality test reveals a unidirectional asymmetric causality between negative shocks in financial development and poverty. The findings of the present study necessitate the need for investigating asymmetric and nonlinear effects in finance–poverty nexus, which existent literature has completely neglected, in order to have relevant policy conclusions.

The study used “Per capita consumption expenditure” as a measure for poverty due to lack of continuous time series data on headcount ratio. In future, researchers can extend this study by incorporating headcount ratio as a measure of poverty in their respective works. There is further scope of research on this issue by finding out the impact of formal and informal sources of credit on poverty separately. A panel data study for developing countries over a period of time could further confirm/negate the findings of the present study.

To the best of the authors’ knowledge none of the studies in Indian context has scrutinized asymmetric and nonlinear impact of financial development on poverty. To dredge up asymmetric structures at work, the authors have used the highly celebrated NARDL estimator. To enrich the existent body of knowledge along the lines of asymmetric (nonlinear) linkages, the authors have also used recently introduced asymmetric causality test by Hatemi-j-(2012) to find out the direction asymmetric causality.

This paper is an attempt to re-examine the validity of the Twin Deficit Hypothesis in the Indian economy, which is characterised by mounting inequality and liquidity constraints. The authors augment the econometric analysis with two important mediating variables, exchange rate and trade openness, to analyse their impact on current account deficit.

The authors have used a ground-breaking asymmetric cointegration technique proposed by Shin et al. (2014) to investigate the short-run and long-run asymmetric nexus between gross fiscal deficit and current account deficit. In addition, the study has used asymmetric dynamic multipliers to see the dynamics of nonlinear adjustment from disequilibrium in the short run to equilibrium in the long run. The study has also used generalised impulse response functions to check the robustness of our cointegration results.

Using annual time series data from 1970 to 2018, the empirical exercise validates the presence of asymmetries in the Twin Deficit Hypothesis for the Indian economy. This study's robust findings demonstrate that the two deficits are asymmetrically related in the long run. The authors also found that exchange rate asymmetrically affects current account deficit thus validating the asymmetric J-curve phenomenon. From the causality analysis, the authors infer that there is a weak unidirectional causality running from fiscal deficit to current account deficit.

Fiscal deficit may cause current account deficit via changes in other macroeconomic variables that were not taken care of in this study. Therefore, the estimation techniques used in the present study might suffer from the issue of omitted-variable bias. Further research should include other macroeconomic variables where the twin deficit nexus is also influenced by other relevant variables. This will help in disentangling the indirect transmissions by which fiscal deficit translates into current account deficit.

The results from our econometric exercise strongly suggest that the twin deficits are asymmetrically related. From a policy perspective, the asymmetric twin deficit nexus offers strong policy implications for the development of policies that are flexible enough to respond to shifts in internal and external sector dynamics. While framing the mechanism of fiscal prudence, policymakers in emerging countries like India must take into account the regime-changing behaviour of twin deficits.

The present paper is a significant contribution to the existing body of literature by being the first study in India which has analysed the Twin Deficits phenomenon in a nonlinear framework with the incorporation of asymmetric exchange rate dynamics in the model.

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 aims to revisit the empirical debate about the asymmetric relationship between oil prices, energy consumption, CO₂ emissions and economic growth in a panel of 184 countries from 1981 to 2020.

A relatively new research method, the PVAR system GMM, is applied.

The outcome of the PVAR system GMM model at the group level in the study suggests that oil prices exert a positive but statistically insignificant effect on economic growth. Energy consumption is inversely related to economic growth but statistically significant, and the correlation between CO₂ emissions and economic growth is negative but statistically insignificant. The Granger causality test indicates that oil prices, CO₂ emissions, oil rents, energy consumption and savings jointly Granger-cause economic growth. A unidirectional causality runs from energy consumption, savings and economic growth to oil prices. At countries’ income grouping levels, oil prices, oil rent, CO₂ emissions, energy consumption and savings jointly Granger-cause economic growth for the high-income and upper-middle-income countries groups only, while those variables did not jointly Granger-cause economic growth for the low-income and lower-middle-income countries groups. The modulus emanating from the eigenvalue stability condition with the roots of the companion matrix indicates that the model is stable. The results support the asymmetric impacts of oil prices on economic growth and aid policy formulation, particularly the cross-country disparities regarding the nexus between oil prices and growth.

From a methodological perspective, to the best of the author’s knowledge, the study is the first attempt to use the PVAR system GMM and such a large sample group of 184 economies in the post-COVID-19 era to examine the impacts of oil prices on countries’ growth while controlling for other crucial variables, which is noteworthy. Two, using the World Bank categorisation of countries according to income groups, the study adds another layer of contribution to the literature by decomposing the 184 sample economies into four income groups: high-income, low-income, upper-middle-income and lower-middle-income groups to investigate the potential for asymmetric effects of oil prices on growth, the first of its kind in the post-COVID-19 period.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

This study aims to explore the long- and short-run effects of daily confirmed cases of COVID-19 (C_t) on daily stock returns (R_t) for Kuwait. This is the first study that was applied to the case of Kuwait.

We employed the autoregressive distributed lag (ARDL) model of Pesaran et al. (2001) and the nonlinear autoregressive distributed lag (NARDL) model of Shin et al. (2001) for daily data over the period March 2020 to August 2021.

The findings first document the existence of a long-run relationship (cointegration). Second, the findings of the ARDL model show a significant positive long-run effect of daily confirmed cases of COVID-19 (C_t) on daily stock returns (R_t) but a significant negative short-run effect. As for the NARDL model, the findings showed that the increase and decrease of daily confirmed cases of COVID-19 (Ct−1+,Ct−1−) have symmetric long-run effects on daily stock returns but asymmetric short-run effects. Finally, the vector error correction model causality test shows significant long- and short-run unidirectional causality running from daily confirmed cases of COVID-19 (C_t) to daily stock returns (R_t).

To the best of the author’s knowledge, this is the first study that was applied to the case of Kuwait.

This study investigates the asymmetric influence of renewable energy consumption (REC) and trade openness (TO) in the pathway of decarbonizing of Indian economy.

By exploiting fifty years of annual time series data spanning from 1970 to 2019 with the augmentation of nonlinear autoregressive distributed lag technique with the consideration of GDP and industry value added (IVA) as control variables.

Our This research not only demonstrates the asymmetric association among the employed variables but also shows that negative shock to REC stimulates emissions, where as positive shock on the same policy variable promotes environmental quality improvement. Negative shock to TO is found to be associated with the corresponding increase of environmental quality, but the positive shock on the same intensifies environmental pollution. IVA is also found to be associated with intensifying environmental squalor. In addition, the research provides the empirical evidence of existence of “EKC” hypothesis in India as long-run coefficient associated with GDP looks smaller than short-run coefficient of GDP.

It was difficult to include may other causal variables due to nonavailability of data pertaining to those variables.

Moreover, some policy guidelines have also been recommended for India at the end that may aid India to achieve net zero emissions by 2070.

This is an original research paper carried out by the authors and has not yet been submitted elsewhere.

This study aims to intend to investigate the dynamic causality and asymmetric relationships between corruption and economic growth of Nigeria.

Toda–Yamamoto (TY) Dynamic Causality Test and Non-linear Autoregressive Distributed Lag Model (NARDL) were used for the estimations, for the period 1984–2018.

The result reveals the existence of bidirectional causality between control of corruption and economic growth, Similarly, in both the short run and long run, corruption can affect economic growth and economic growth can as well affects corruption.

Findings of the research are limited to Nigeria whose data were used, based on TY causality test and NARDL as the econometrics techniques applied, for a period 1984–2018.

For a meaningful progress to be recorded in Nigeria in terms of economic growth, the country must device some means for strengthen the control of corruption.

The study was able to prove empirically, the existence of not only causality between corruption and economic growth but also asymmetric effect of corruption on economic growth and that of economic growth on corruption in both the long run and short run, as against the previous studies that are lopsided on the effect of corruption on economic growth only.