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This paper aims to examine the validity of the question of whether oil dependence has a negative impact on the relationship between financial development and economic growth in Yemen.

The auto-regressive distributed lag approach for cointegration is used to examine the relationship between financial development and economic growth by capturing the impact of oil dependence on this relationship. The Granger causality test, based on a vector error correction model (VECM) framework, is used to investigate the causal relationships between financial development and economic growth.

The most interesting finding is the negative sign of interaction term between financial development and oil dependence, which implies that the positive effect of financial development on economic growth decreases with the increasing oil dependence. The result of the VECM Granger causality test revealed the existence of unidirectional causality running from financial development to economic growth.

The short sample period and the worry of losing degrees of freedom limited us when including control variables in the model. If the data are available in the future, other control variables can be added.

The government should reduce the level of oil dependence in Yemen by diversifying the country’s economy. Accelerating the pace and efficiency of the financial sector will bear fruitful returns in this regard. The government could achieve this strategy by playing a more proactive role in encouraging the expansion of credit to enable the financial sector to provide a more efficient intermediary role in mobilizing domestic savings and channeling them to productive investments across various economic sectors.

This is the first study to examine the impact of oil dependence on the finance-growth nexus in Yemen. A new indicator for oil dependence is also proposed.

This paper examines the extreme dependence and asymmetric risk spillovers between crude oil futures and ten US stock sector indices (consumer discretionary, consumer staples, energy, financials, health care, industrials, information technology, materials, telecommunication and utilities) before and during COVID-19 outbreak. This study is based on the rationale that stock sectors exhibit heterogeneity in their response to oil prices depending on whether they are classified as oil-intensive or non-oil-intensive sectors and the possible time variation in the dependence and risk spillover effects.

The authors employ static and dynamic symmetric and asymmetric copula models as well as Conditional Value at Risk (VaR) (CoVaR). Finally, they use robustness tests to validate their results.

Before the COVID-19 pandemic, crude oil returns showed an asymmetric tail dependence with all stock sector returns, except health care and industrials (materials), where an average (symmetric tail) dependence is identified. During the COVID-19 pandemic, crude oil returns exhibit a lower tail dependency with the returns of all stock sectors, except financials and consumer discretionary. Furthermore, there is evidence of downside and upside risk asymmetric spillovers from crude oil to stock sectors and vice versa. Finally, the risk spillovers from stock sectors to crude oil are higher than those from crude oil to stock sectors, and they significantly increase during the pandemic.

There is heterogeneity in the linkages and the asymmetric bidirectional systemic risk between crude oil and US economic sectors during bearish and bullish market conditions; this study is the first to investigate the average and extreme tail dependence and asymmetric spillovers between crude oil and US stock sectors.

The purpose of this paper is to analyze the optimal hedging strategy of the oil-stock dependence structure.

The methodology consists to model the data over the daily period spanning from January 02, 2002 to May 19, 2016 by a various copula functions to better modeling the dependence between crude oil market and stock markets, and to use dependence coefficients and conditional variance to calculate optimal portfolio weights and optimal hedge ratios, and to suggest the best hedging strategy for oil-stock portfolio.

The findings show that the Gumbel copula is the best model for modeling the conditional dependence structure of the oil and stock markets in most cases. They also indicate that the best hedging strategy for oil price by stock market varies considerably over time, but this variation depends on both the index introduced and the model used. However, the conditional copula method with skewed student more effective than the other models to minimize the risk of oil-stock portfolio.

This research implication can be valuable for portfolio managers and individual investors who seek to make earnings by diversifying their portfolios. The findings of this study provide evidence of the importance of stock assets for making an optimal portfolio consisting of oil in the case of investments in oil and stock markets. This paper attempts to fill the voids in the literature on volatility among oil prices and stock markets in two important areas. First, it uses copulas to investigate the conditional dependence structure of the oil crude and stock markets in the oil exporting and importing countries. Second, it uses the dependence coefficients and conditional variance to calculate dynamic hedge ratios and risk-minimizing optimal portfolio weights for oil–stock.

The study aims to understand the role of different streams of oil shocks (demand, supply and risk shocks) on the oil-importing and exporting countries' stock returns. The study also examines the impact of crude oil shocks across the economic regimes and market states. Besides, the role of the Global Financial Crisis (GFC) of 2008 in shaping the oil–stock relationship is also investigated.

The authors revisit the impact of oil shocks on emerging equity markets by using the novel shock decomposition algorithm proposed by Ready (2018). The authors consider 24 emerging equity markets for the period spanning over July 15, 2002, to June 18, 2018, and bifurcate them based on oil dependence. The authors use rolling and dynamic conditional correlation analysis to understand the time-varying co-movements between oil prices and stock returns. The regime and state-specific dependence of stock returns on the structural oil shocks are captured by the Markov regime switching and quantile regression models.

The authors find that the demand shocks are positively associated with stock markets, whereas the supply shocks are negatively related, except in some of the oil-exporting countries. The risk-based shocks also appear to have a negative association with stocks. The authors do not find evidence of strong regime dependence and the direction of relationship across the high and low regimes is somewhat stable. Further, the authors observe an intense oil–stock relationship in the bearish market conditions. Besides, the authors also report evidences of changes in oil–stock relationship onset the GFC.

This is among the first studies to use the oil shock decomposition algorithm of Ready (2018) in the context of emerging equity markets. Additionally, oil shocks' role on the stock market movements across the regimes and market states is studied comprehensively. Thus, the nature of oil shock and the extent to which the emerging markets are exposed is observed in this study.

To explore the relationships among oil import dependence, energy (in)efficiency, and environmental damage for the USA. The goal is to illuminate possibilities for reducing oil import dependence.

The paper uses current information about costs of oil imports and energy alternatives for transportation vehicles, and environmental concerns, along with information about alternatives for energy provision for this purpose, to demonstrate feasible ways to reduce dependence, including government policy steps.

The USA is dependent on imported oil: two‐thirds of US oil used today is imported, and mostly used as gasoline for autos – close to 70 percent of all oil is used in transportation. This greatly affects the US BOP; oil imports cost almost US$300 billion in 2006. Current energy efficiency of auto engines is about 15 percent. Using hydrogen fuel cells would at least double this value, as well as reducing waste and completely eliminating carbon dioxide emissions. An efficient means of producing the hydrogen must be developed. A related problem is damage to the environment caused by greenhouse gas emissions. This problem also can be attacked by increasing engine efficiency, and ultimately by replacing gasoline in auto engines with alternative fuels such as hydrogen in fuel cells, as well as by reducing auto use, via mass transport. Policy alternatives include: encouraging energy efficiency via new technologies for vehicle engines; encouraging mass transportation; and higher production of fuels in the USA. Reducing demand via taxes, as in Europe, could reduce consumption, but at a cost to overall GDP unless alternative fuels become competitively priced.

The two main limitations on our recommendations are technology for making fuel cells more competitive, and willingness of government to take the needed policy steps. The practical implication is that dependence can be reduced with these steps.

The paper links the three corners of the energy triangle: dependence; efficiency, and environment.

This paper aims to clarify the relationship between oil product prices and factors describing the most crucial emerging trends in fuel consumption. The work is aimed to test the hypothesis that the proliferation of alternative fuel cars is a significant factor in determining the level of motor fuel prices. The influence of technical standards of oil products on the model parameters is also analysed.

The hypothesis testing is carried out on the basis of an econometric analysis of information regarding the North-West European commodity market and the data on the registration of alternative fuel passenger vehicles. Time series are analysed for the presence of a structural shift in the parameters of the model as a result of changes in the requirements of technical regulations for fuel.

The results suggest a different nature of the influence of the proliferation of alternative fuel passenger vehicles – it has little effect on diesel prices, whilst the indicators under study have a negative effect on the prices of motor gasoline. The construction of oil product price models has confirmed the impact of tightening the technical requirements for the parameters of dependence equations.

The obtained results can be used in forecasting price indicators in oil refining for strategic and investment purposes.

This paper fulfils an identified need to take into account the emerging global trends in fuel consumption to obtain reliable parameters for oil product price modelling.

This study aims to examine the links between oil price shocks and Gulf Cooperation Council (GCC) stock markets from February 2004 to December 2019. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors use the Ready (2018) oil price decomposition method and the quantile regression approach to conduct the analysis.

Initial results show a positive oil price change increases stock returns, while greater volatility decreases returns. The oil shock decomposition results reveal a significant positive impact of supply-side shocks on stocks. This contrasts with the literature that argues demand-side shocks are more important. While factors such as liquidity and the lack of hedging instruments can increase the vulnerability of GCC equities to oil price shocks, the result reflects the unique economic structure of the GCC bloc, notably, marked by dependency on oil revenues. In analysing quantile-based results, oil supply shocks mainly exhibit lower-tail dependence, while the authors do uncover some evidence of demand-side shocks affecting mid and upper-tail dependence.

Acknowledging the presence of endogeneity in the relation between oil and economic activity, to the best of the authors’ knowledge, this study is the first to combine the oil price decompositions of Ready (2018) with a quantile regression framework in the GCC context. The results reveal notable difference to those previously reported in the literature.

The main purpose of this paper is to understand the impact on the United Arab Emirates (UAE) economy of the objective of reducing its dependence on oil, trying to achieve the Gulf Cooperation Council (GCC) fiscal convergence criterion and the inevitable depletion of oil resources.

An 18 equation compact macro‐econometric model is constructed and is evaluated and calibrated employing dynamic simulation techniques. Optimal control techniques are used to analyze the economic impact of the three objectives listed above.

Each of the optimal control experiments that has been carried out has served to reinforce the fact that the UAE is still critically dependent on oil. An increase in the share of the non‐oil sector, adhering to the GCC fiscal criterion and any reduction in oil output production will affect government finances adversely.

The macro‐econometric model developed is for the UAE and further research is needed to see if the conclusions can be generalized to the other oil exporting countries.

The estimated macro‐econometric model and the optimal control experiments indicate to the policy makers the need to continue the diversification of the economy and for government to actively explore and enhance non‐hydrocarbon sources of revenue.

This paper develops a compact macro‐econometric model of the UAE and uses optimal control techniques which go well beyond the standard simulation techniques and the routine counter‐factual experiments to understand the working of the economy.

The achievement of self-reliance (zi li geng sheng: “regeneration through one's own efforts”) is an important Chinese goal. Mao Zedong's approach to achieving this goal after 1960 was to advocate and practice economic self-sufficiency both within China and nationally. One purpose of this article is to outline and discuss Mao's approach and its consequences. Following China's market reforms commencing in 1978, Mao's economic self-reliance policies were systematically abandoned. The second aim of this article is to consider how China's market reforms and its development have impacted on subnational economic self-reliance within China and to assess the extent to which its open-door policy has reduced its national self-reliance.

Secondary sources and data are used to develop this article.

As a result of its market reform and economic development, all parts of China's economy have become more interdependent and continue to do so. In addition, China has become more dependent for its economic welfare on international trade, but its dependence is much less than that of many other countries, for example, Germany. Nevertheless, the Chinese still endeavour to be masters of their own destiny. From this perspective, Mao's principle of self-reliance has not been abandoned.

Despite its growing economic interdependence, China continues to value its capacity for autonomous goal setting and decision-making. This is illustrated by the strategies it has adopted to address its dependency on oil imports. Nevertheless, China's increased economic interdependence adds to China's challenges and difficulties in controlling its economic affairs.

The purpose of this paper is to compare the security of oil supply of the 27 European Union (EU27) member countries throughout the measurement of the vulnerability that their economies have exhibited to oil during the period from 1995 to 2007. Additionally, the EU27 future oil vulnerability is to be estimated for two indicative scenarios: a low oil price projection and a high price one. The two projections are going up to 2030.

Six indicators that quantify the core concepts that affect the security of supply of a country have been integrated in a synthetic index that measures the vulnerability of the case study countries for the time period under consideration. For the development of the synthetic index the principal component analysis (PCA) has been applied.

The results of this paper are illustrative of the existing vulnerabilities in the oil supply that may signal for a common EU policy addressing the energy availability risk issue.

The main limitation of the analysis is the usage of six indicators in order to capture the core essence of vulnerability and security of supply. The integration of additional indicators in the synthetic index may strive towards a more precise analysis.

The contribution of the paper lies in the usage of a statistical technique, PCA, for the development of a synthetic index that specifies the vulnerability in oil for EU27.