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The present study aims to compare the effect of international paid remittances on financial development in three Gulf Cooperation Council (GCC) countries from 1985 to 2020.

The study applied the bound cointegration technique and the autoregressive distributed lag (ARDL) method for long- and short-run estimations as well as diagnostic tests to increase robustness.

The ARDL long-run results showed that international paid remittances had a significant negative effect on financial development in Oman and Saudi Arabia but an insignificant negative effect in Bahrain. The error correction model for the short run of the ARDL slowdown model showed that international paid remittances had a significant positive effect on financial development in Oman, Bahrain, and Saudi Arabia.

Few studies have examined remittance outflows from GCC countries, which are enriched by oil wealth and located in one of the most stable geographical areas in the world. The findings from this study can help policymakers understand how to enable remittances and investments in order to establish regulations that will preserve remittance inflows and meet target services.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

Previous studies have mostly estimated there to be a symmetric effect in the Foreign direct investment (FDI) inflow regarding the economic growth of Central, East and Southeast European (CESEE) countries. However, for the CESEE countries, as well as for the majority of countries around the world, there has been no study that has estimated the symmetric and asymmetric effect of outward FDI on economic growth. The main objective of this study is to estimate whether the relation between outward FDI and economic growth in CESEE countries is symmetric or asymmetric.

This study includes a sample based on eight CESEE countries. The authors used the linear and non-linear autoregressive distributed lag (ARDL) model and annual data for the period from 1990 to 2020.

In the long run, in the linear ARDL model, a significant symmetrical effect due to OFDI on the economic growth of Romania and Slovenia was found, while in the non-linear ARDL model, a significant asymmetric effect of OFDI on the economic growth of Bulgaria, Poland, Romania, Russia, Slovenia and Slovakia was found. In six out of the eight countries, asymmetry was found while symmetry was found in the other two. Poorer symmetry results can be ascribed to the lack of linear model neglecting the asymmetric behaviour of the positive and negative change decomposition as part of the OFDI movement, which leads to the wrong conclusion.

This is the first study to evaluate the asymmetric effect of outward FDI on the economic growth of eight CESEE countries.

This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption during 1990–2018 in India.

For time series analysis, the standard unit root test has been employed to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction.

The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long-run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India.

The present study makes valuable and original contributions to the literature by applying a multivariate ecological footprint function, assessing the impact of economic globalization on ecological footprint while considering economic growth and energy consumption in India.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.

The environmental deterioration has become one of the most economically consequential and charged topics. Numerous scholars have examined the driving factors failing to consider the structural breaks. This study aims to explore sustainability using the per capita ecological footprints (EF) as an indicator of environmental adversities and controlling the resources rent [(natural resources (NR)], labor capital (LC), urbanization (UR) and per capita economic growth [gross domestic product (GDP)] of China.

Through the analysis of the long- and short-run effects with an autoregressive distributed lag model (ARDL), structural break based on BP test and Granger causality test based on vector error correction model (VECM), empirical evidence is provided for the policies formulation of sustainable development.

The long-run equilibrium between the EF and GDP, NR, UR and LC is proved. In the long run, an environmental Kuznets curve (EKC) relationship existed, but China is still in the rising stage of the curve; there is a positive relationship between the EF and NR, indicating a resource curse; the UR is also unsustainable. The LC is the most favorable factor for sustainable development. In the short term, only the lagged GDP has an inhibitory effect on the EF. Besides, all explanatory variables are Granger causes of the EF.

A novel attempt is made to examine the long-term equilibrium and short-term dynamics under the prerequisites that the structural break points with its time and frequencies were examined by BP test and ARDL and VECM framework and the validity of the EKC hypothesis is tested.

This study aims to assess the nexus among oil price (OP), renewable energy consumption (REC) and trade balance (TB) for India using annual time series data for the time period 1985–2019. In particular, the authors examine whether REC improves India's TB in the context of high oil import dependence.

The study uses autoregressive distributed lags (ARDL) bound testing approach that has the advantage of yielding estimates of long-run and short-run parameters simultaneously. Moreover, the small sample properties of this approach are superior to other multivariate cointegration techniques. Fully modified ordinary least square (FMOLS) and dynamic ordinary least squares (DOLS) are also applied to test the robustness of the results. The causality among the series is investigated through block exogeneity test based on vector error correction model.

The findings based on ARDL bounds testing approach indicate that OPs exert a negative impact on TB of India in both long run and short run, whereas REC has a favorable impact on the TB. In particular, 1% increase in OPs decreases TBs by 0.003% and a 1% increase in REC improves TB by 0.011%. The results of FMOLS and DOLS corroborate the findings from ARDL estimates. The results of block exogeneity test suggest unidirectional causation from OPs to TB; OPs to REC and REC to TB.

The study underscore the importance of renewable energy as a potential tool to curtail trade deficits in the context of Indian economy. Our results suggest that the policymakers must pay attention to the hindrances in augmentation of renewable energy usage and try to capitalize on the resulting gains for the TB.

Climate change is a major challenge for developing countries like India. Renewable energy sector is considered an important instrument toward attaining the twin objectives of environmental sustainability and employment generation. This study underscores another role of REC as a tool to achieve a sustainable trade position, which may help India save her valuable forex reserves for broader objectives of economic development.

To the best of the authors’ knowledge, this is the first study that probes the dynamic nexus among OPs, REC and TB in Indian context. From a policy standpoint, the study underscores the importance of renewable energy as a potential tool to curtail trade deficits in context of India. From a theoretical perspective, the study extends the literature on the determinants of TB by identifying the role of REC in shaping TB.

This paper seeks to examine the effect of monetary policy rate (MPR) on the lending rates of commercial banks in Ghana.

The paper employed the autoregressive distributed lag (ARDL) model as well as the non-linear autoregressive distributed lag (NARDL) model econometric techniques on a quarterly time series data from 2002 to 2018.

The ARDL results revealed that, MPR has a positive and significant effect on lending rate in the long and short run. Although there exists a direct relationship between MPR and lending rate, from the NARDL revealed an asymmetric effect of MPR on lending rate to the effect that, lending rate in Ghana responds more to positive shock (a rise in MPR) compared to a negative shock (a decrease in MPR) both in the long and short run.

The paper contributes to policy and literature in Ghana by providing empirical evidence on the asymmetric effect that MPR has on lending rates in Ghana. The paper recommends among others, the establishment of a rating system of banks according to their monetary policy compliance, where highly rated banks could have for instance a reduction on borrowed reserves from the central bank.

This study attempts to examine the relationship between the banking sector and stock market development in India.

To analyze the relationship between banks and stock market development, the ratio of stock market capitalization to GDP is proxied by stock market development. The determinants of the stock market development are used for analysis namely domestic credit to the private sector as a ratio of GDP is used as a proxy for the development of banks, saving rate, per capita real GDP, and inflation. The autoregressive distributed lag (ARDL)-Bounds testing approach is used for the analysis. The paper also used the unrestricted error correction model and CUSUM and CUSUM square test to check the stability of the model.

The ARDL bounds test found that there is a long-run relationship between stock market development and bank-centered financial development. The results also revealed that the stock market is positively influenced by the development of banks, savings, and per capita real GDP in the short-run as well as long-run.

This paper suggests that improvement of banking sector plays an important role to increase liquidity of the capital market development in India. This paper also suggests that the economic growth and savings rate have positive impact to induce the capital market growth in both short run and long run.

The study has investigated the empirical relationship between the banking sector and the stock market development in a different methodological approach by using an ARDL model which is appropriate for a small sample size. There are few studies related to bank-centered financial development and stock market development in the context of India.

Human capital is a portfolio of rich skills that the labour possesses. Human capital has attracted significant attention from scholars. Nevertheless, empirical findings on the utility of human capital have often been divided. To address the research gap in the literature, the authors attempt to understand how human capital plays a significant role in financial development and economic growth nexus.

The authors rely on secondary data published by the World Bank. The authors use econometric tools such as the autoregressive distributive lag (ARDL) model and related statistical tests to study the relationship between human capital, India's financial growth and gross domestic product (GDP) growth.

Study findings suggest that human capital and financial development contribute significantly to economic growth. Further, the authors found that human capital has a positive and significant moderating effect on the path of joining financial development and economic growth.

The study contributes to the human capital debate. Despite the rich body of literature, the study based on World Bank data confirms the previous findings that investment in human capital is always useful for the financial and economic growth of the nation.

This paper reveals some unique findings regarding effect of financial development and economic growth nexus which opens the window of new dimension to think about their nexus. It also provides a different pathway to foster the economic growth by using human capital and financial development as together, especially in India.