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This paper aims to explore the extreme effect of crude oil price fluctuations and its volatility on the economic growth of Middle East and North Africa (MENA) countries. It also investigates the asymmetric and dynamic relationship between oil price and economic growth. Further, a separate analysis for each MENA oil-export and oil-import countries is conducted. Furthermore, it studies to what extent the quality of institutions will change the effect of oil price fluctuations on economic growth.

As the effect of oil price fluctuations is not the same over different business cycles or oil price levels, the paper uses a panel quantile regression approach with other linear models such as fixed effects, random effects and panel generalized method of moments. The panel quantile methodology is an extension of traditional linear models and it has the advantage of exploring the relationship over the different quantiles of the whole distribution.

The paper can summarize results as following: changes in oil price and its volatility have an opposite effect for each oil-export and oil-import countries; for the former, changes in oil prices have a positive impact but the volatility a negative effect. While for the latter, changes in oil prices have a negative effect but volatility a positive effect. Further, the impact of oil price changes and their uncertainty are different across different quantiles. Furthermore, there is evidence about the asymmetric effect of the oil price changes on economic growth. Finally, accounting for institutional quality led to a reduction in the impact of oil price changes on economic growth.

The study concludes more detailed results on the impact of oil prices on gross domestic product growth. Thus, it can be used as a decision-support tool for policymakers.

The purpose of this paper is to explore and analyse the dynamic relationship between remittances inflows of Egyptians working abroad and asymmetric oil price shocks.

This study uses a vector autoregressive (VAR) model to explain the impulse response functions (IRFs) and the forecast error variance decomposition (FEVD). The rationale behind using these tools is its ability to examine the dynamic effects of our variables of interest.

The impulse response functions confirmed that remittance inflows have various responses to asymmetric oil price shocks. For instance, inflowing remittances increase in response to positive oil price shocks, while it decreases in response to negative oil price shocks. Also, the results indicate that the responses are significant in the short and medium-run and insignificant in the long run. The magnitude of these responses reaches its peak or trough in the third year. Further, the variance decomposition reveals that oil price decreases are more influential than oil price increases.

This means that remittances inflows in Egypt are pro-cyclical with oil price shocks. That explained by the fact that more than one-half of those remittances sent from GCC countries where real economic growth is very pro-cyclical with the oil prices. This empirical assessment will help policymakers to determine the behaviour of remittances and highlights the impact of different kinds of oil prices shocks on remittances. Unlike the little existing literature, this study is the first study applied the VAR model using a novel dataset spanning 1960-2016.

The purpose of this paper is to examine the issue of high current account deficit (CAD) from various perspectives focussing its behaviour, financing pattern and sustainability for India.

To begin with the trends, composition and dynamics of CAD for India are analysed. Next, the influence of capital flows on current account is investigated using Granger non-causality test proposed by Toda and Yamamoto (1995) between current account balance (CAB) to GDP ratio and financial account balance to GDP ratio. Also, the sustainability of India’s current account is examined using different econometrics techniques. In particular, Husted’s (1992), Johansen’s cointegration and vector error correction model (VECM) is applied along with conducting unit root and structural break tests wherever applicable. Further, long-run and short-run determinants of the CAB are estimated using Johansen’s VECM.

The study found that the widening of CAD is due to fall in household financial savings and corporate investments. Also, it was found that a large part of India’s CAD has been financed by FDI and portfolio investments which are partly replaced by short-term volatile flows. The unit root and cointegration tests indicate a sustainable current account for India. Further, econometric analysis reveals that India’s current account is driven by fiscal deficit, terms of trade growth, inflation, real deposit rate, trade openness, relative income growth and the age dependency factor.

Since India’s CAD has widened and is expected to widen primarily due to rise in gold and oil imports, policy makers should focus on achieving phenomenal export growth so that a sustainable current account is maintained. Also, with rising working-age and skilled population, India should focus more on high-value product exports rather than low-value manufactured items. Further, on the structural side it is important to correct fiscal deficit as it is one of the important factors contributing to large CAD.

The paper is an important empirical contribution towards explaining India’s CAD over time using latest and comprehensive data and econometric models.

Over the past decades, the global solar photovoltaic (PV) market has experienced an unprecedented development associated with a substantial decline in solar PV module prices. A body of literature has attempted to identify and evaluate the different sources of price variation. However, the impact of international trade on the price of solar PV modules has not yet been empirically examined. This paper contributes to filling this gap in the literature by providing a comprehensive empirical examination on the relationship between international trade and solar PV module prices.

The author uses a sample of 15 countries over the period 2006–2015 and proposes a linear dynamic panel data model based on a new specification, including a number of relevant factors influencing solar PV module prices.

The empirical analysis reveals that an increase in imports of solar PV cells and modules is associated with a decline in solar PV module prices. This finding suggests that international trade could lead to further price reductions, thus fostering the deployment of solar PV technology. The study reveals several other important findings. Market and technological development are key factors explaining the decline in solar PV module prices. Moreover, government policies such as public budget for R&D in PV and feed-in tariff for solar PV are effective in reducing the price of solar PV modules.

This paper examines the influence of international trade, government policies, market development and technological development on solar PV module prices. The results may be of interest to both academic research and policy analysis.

The purpose of this paper is to examine, in a global perspective, the oil, gold, US dollar and stock prices interdependencies and to identify instantaneously direct and indirect linkages among them.

A methodology based on simultaneous equations system was used to identify direct and indirect linkages for the period 1995-2015. The authors try initially to find theoretical answers to main question of the study by discussing causal bilateral relationships while focusing on multilateral interactions.

The results show significant interactions between all markets. The authors found a negative relation between oil and stock prices but oil price is significantly and positively affected by gold and USD. Oil price is also affected by oil futures prices and by Chinese oil gross imports. Gold rate is concerned by changes in oil, USD and stock markets. The US dollar is negatively affected by stock market and significantly by oil and gold price. Indirect effects always exist which confirm the presence of global interdependencies and involve the financialization process of commodity markets.

Motivation of this research paper is the substantial implications of price movements on real economy and financial markets. Understanding that co-movement has great value for investors, policy makers and portfolio managers. This paper differs from previous studies in several aspects. First, most of the research papers focus on bilateral linkages solely, while the authors’ investigation was implemented on all the four markets simultaneously. Second, the study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

Might the impact of the global economic policy uncertainty (GEPU) and the long-term bond yields on oil prices be asymmetric? This paper aims to consider the effects of the GEPU and the US long-term government bond yields on oil prices using quantile-based analysis and nonlinear vector autoregression (VAR) model. The author hypothesized whether the negative and positive changes in the GEPU and the long-term bond yields of the USA have different effects on oil prices.

To address this question, the author uses quantile cointegration model and the impulse response functions (IRFs) of the censored variable approach of Kilian and Vigfusson (2011).

The quantile cointegration test showed the existence of non-linear cointegration relationship, whereas Granger-causality analysis revealed that positive/negative variations in GEPU will have opposite effects on oil prices. This result was supported by the quantile regression model’s coefficients and nonlinear VAR model’s IRFs; more specifically, it was stressed that increasing/decreasing GEPU will deaccelerate/accelerate global economic activity and thus lead to a fall/rise in oil prices. On the other hand, the empirical models indicated that the impact of US 10-year government bond yields on oil prices is asymmetrical, while it was found that deterioration in the borrowing conditions in the USA may have an impact on oil prices by slowing down the global economic activity.

As a robustness check of the quantile-based analysis results, the slope-based Mork test is used.

Energy is a driving force of economic development in the modern world, while as a commodity group it holds the greatest share of the world seaborne trade. Oil, natural gas and coal are the three most important sources of energy for the European Union which, as a bloc, represents 17% of the total energy consumption. The aim of the present paper is to explore the economics and trade issues of these three major energy commodities and investigate the role of the maritime transport in the energy trade within the context of the EU-25. A number of factors are considered in order to discuss contemporary opportunities and challenges that arise in this context for the shipping business. The examination reveals the critical dependence of EU-25 energy supply on seaborne trade and the considerable reliance of the maritime transport on such commodities for the generation of shipping business within the realms of the EU-25. Among the parameters regarded as conducive to the demand of shipping services in the context of the EU energy trade are the energy demand factor, the import dependency factor, the cost effective production element, and seaborne trade related parameters while consideration is also given to environmental issues.

The study aims to examine the geoeconomic significance of the Gulf Cooperation Council (GCC) countries to China’s global geopolitical ends. In this vein, the paper also seeks to explore the interplay between China’s grand geoeconomic strategy and China’s geopolitical ends from a realist perspective.

The study uses the realism theory to explore the interplay between China’s geoeconomic presence in the GCC countries and its geopolitical global ends.

The study concludes that China under President Xi Jinping has geopolitical ends, and they are the regional and global leadership. To achieve them, President Xi has formulated a grand geoeconomic strategy consisting of four strategies: going out strategy, periphery strategy, Belt and Road Initiative (BRI) and Asian Infrastructure Investment Bank. These strategies will maximize China’s economic power and presence around the world. From a realist perspective, this presence and its evolving consequences such as the balance of dependence will enable China to achieve its geopolitical ends. In this vein, China’s geoeconomic strategy in the GCC countries has largely maximized China’s economic presence in the Gulf. This presence highly serving China’s geopolitical global ends for two reasons: the economic weight of the GCC countries and their strategic location within BRI.

The study can prove the realistic dimension of geoeconomics in the neoliberal era on the application to China’s geoeconomic strategy.

This study aims to establish the dynamic relationship between international crude oil prices and Indian stock prices represented by the Bombay Stock Exchange (BSE) energy index.

Using Johansen’s cointegration test, vector error correction (VEC) model, impulse response function and variance decomposition test the study tries to ascertain the short-term and long-term dynamic association between the oil price shock and the movement of stock price and Granger causality test is applied to find out the nature of causality.

Considering vector autoregression estimation, the present study analyzes the relationship between the variables and tries to make a valid conclusion. The result of the co-integration test exhibits the presence of a long-term association between these two macro-economic variables during the period under study. Also, in the short-run VEC Granger causality result reveals that the movement of international crude oil price significantly influences the Indian stock price.

To get a more robust result the study can be further extended by taking a longer time period with data of shorter time-frequency such as daily or weekly and further by using more sophisticated econometric and statistical tools. Further, the study can be extended to firm-level investigation considering the forward trading concentration with the Indian oil basket.

In today’s globalized era, forecasting of share price movement helps investors in predicting the market and invest accordingly. Through this liquidity of the markets enhance and markets become more active in the global arena.

This study represents fresh findings in the changing time period the linkage between crude oil prices and stock prices which are of value to the academicians, researchers, policymakers, investors, market regulators, etc.

This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China.

The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables.

The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market.

To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.