Net Oil-importing Countries Research Articles

Assessing the impacts of oil price fluctuations on stock returns in emerging markets

This paper investigates the effects of oil price shocks on stock market returns in emerging countries. It differs from previous works in three main aspects: i) we distinguish three groups of countries, the largest net-oil importing countries, the moderately oil-dependent countries, and the largest net-oil exporting countries; ii) The potential influence of bullish and bearish market conditions on the causal relationship between oil and stock returns is controlled for in our analysis; iii) The empirical investigation is based on an analysis of long-term correlation and a conditional multifactor pricing model. Using data from twenty-five emerging countries, our results suggest that oil price risk is significantly priced in emerging markets, and that the oil impact is asymmetric with respect to market phases.

Oil Prices and Stock Markets: What Drives What in the Gulf Corporation Council Countries?

In the empirical literature, only few studies have focused on the relationship between oil prices and stock markets in net oil-importing countries. In net oil-exporting countries this relationship has not been widely researched. This paper implements the panel-data approach of Konya (2006), which is based on SUR systems and Wald tests with country-specific bootstrap critical values to study the sensitivity of stock markets to oil prices in GCC (Gulf Corporation Council) countries. Using two different (weekly and monthly) datasets covering respectively the periods from 7 June 2005 to 21 October 2008, and from January 1996 to December 2007, we show strong statistical evidence that the causal relationship is consistently bi-directional for Saudi Arabia. Stock market price changes in the other GCC member countries do not Granger cause oil price changes, whereas oil price shocks Granger cause stock price changes. Therefore, investors in GCC stock markets should look at the changes in oil prices, whereas investors in oil markets should look at changes in the Saudi stock market.

Erratum to “Assessing the suitability of Input-Output analysis for enhancing our understanding of potential effects of Peak-Oil” [Energy (2008) 34: 284–290

Given recent developments on energy markets and skyrocketing oil prices, we argue for an urgent need to study the potential effects of world oil production reaching a maximum (Peak Oil) in order to facilitate the development of adaptation policies. We consider input–output (IO) modelling as a powerful tool for this purpose. However, the standard Leontief type model implicitly assumes that all necessary inputs to satisfy a given demand can and will be supplied. This is problematic if the availability of certain key inputs becomes restricted and it is therefore only of limited usefulness for the study of the phenomenon of Peak Oil. Hence this paper firstly reviews two alternative modelling tools within the IO framework: supply-driven and mixed models. The former has been severely criticised for its problematic assumption of perfect factor substitution and perfect elasticity of demand as revealed by Oosterhaven [Oosterhaven J. On the plausibility of the supply-driven IO model. J Reg Sci 1988; 28:203–17. [1]]. The supply-constrained model on the other hand proved well suited to analyse the quantity dimension of Peak Oil and is therefore applied empirically in the second part of the paper, using data for the UK, Japanese and Chilean economy. Results show how differences in net-oil exporting and net-oil importing countries are clearly visible in terms of final demand. Industries, most affected in all countries, include transportation, electricity production and financial and trade services.

Assessing the suitability of input–output analysis for enhancing our understanding of potential economic effects of Peak Oil

Given recent developments on energy markets and skyrocketing oil prices, we argue for an urgent need to study the potential effects of world oil production reaching a maximum (Peak Oil) in order to facilitate the development of adaptation policies. We consider input–output (IO) modelling as a powerful tool for this purpose. However, the standard Leontief type model implicitly assumes that all necessary inputs to satisfy a given demand can and will be supplied. This is problematic if the availability of certain key inputs becomes restricted and it is therefore only of limited usefulness for the study of the phenomenon of Peak Oil. Hence this paper firstly reviews two alternative modelling tools within the IO framework: supply-driven and mixed models. The former has been severely criticised for its problematic assumption of perfect factor substitution and perfect elasticity of demand as revealed by Oosterhaven [Oosterhaven J. On the plausibility of the supply-driven IO model. J Reg Sci 1988; 28:203–17. [1]]. The supply-constrained model on the other hand proved well suited to analyse the quantity dimension of Peak Oil and is therefore applied empirically in the second part of the paper, using data for the UK, Japanese and Chilean economy. Results show how differences in net-oil exporting and net-oil importing countries are clearly visible in terms of final demand. Industries, most affected in all countries, include transportation, electricity production and financial and trade services.

Oil vulnerability index of oil-importing countries

This paper assesses the relative oil vulnerability of 26 net oil-importing countries for the year 2004 on the basis of various indicators—the ratio of value of oil imports to gross domestic product (GDP), oil consumption per unit of GDP, GDP per capita and oil share in total energy supply, ratio of domestic reserves to oil consumption, exposure to geopolitical oil market concentration risks as measured by net oil import dependence, diversification of supply sources, political risk in oil-supplying countries, and market liquidity. The approach using the principal component technique has been adopted to combine these individual indicators into a composite index of oil vulnerability. Such an index captures the relative sensitivity of various economies towards developments of the international oil market, with a higher index indicating higher vulnerability. The results show that there are considerable differences in the values of individual indicators of oil vulnerability and overall oil vulnerability index among the countries (both inter and intraregional).