According to economic survey of Pakistan (2006), in line with the rising growth rate of GDP, demand for energy has also grown rapidly. The magnitude by which economies are hurt as a result of price shock depends on the share of cost of oil in national income, the degree of dependence on imported oil and the ability of end-users to reduce their consumption and switch away from oil. In the energy mix for the year 2005-06, oil accounts for 32 percent of the total energy used in Pakistan. Although the intensity with which oil is used in total energy consumption has declined in the last few years but still it is the second largest source of energy used after natural gas, which accounts for 39 percent. As far as the energy intensity is concerned it has remained almost constant since 1990-91 (i.e., 1 %). Bacon (2005) suggests that decrease in energy intensity is considered as the most promising route for reducing vulnerability to oil shocks.
Pakistan spent about 44 percent of export earnings on oil imports in 2006-07. This percentage was only 27 percent in 2004-05. Therefore, the international oil price fluctuations have a direct bearing on the macro economy of the country, especially on the oil price GDP relationship. The share of net oil imports in GDP is an index of the relative importance of the oil price rise to the economy in terms of the potential adjustments needed to offset it. For Pakistan over the last few years, this ratio has risen from -3.13 in 1990-91 to -5.24 in 2005-06 (Malik 2007). With such a high ratio, unless country is running in surplus, or has extremely large foreign exchange reserves, high oil price is dealt by severe macroeconomic adjustments.
According to Malik (2008), a country’s vulnerability to oil shocks can be seen through a number of indicators. Firstly, the oil self sufficiency index, which is calculated as the difference between oil production and oil consumption divided by oil consumption. This ratio is negative for oil importers (with -1 being the extreme value). Pakistan had a value of -0.79 in 2005-2006, indicating its high susceptibility to oil shocks. Secondly, Vulnerability to rising oil prices also depends on the intensity with which oil is used. The intensity of oil use in energy consumption index measures the share of oil in an economy’s primary energy consumption. Pakistan had a value of 0.32 in 2005-2006, showing slight decrease from the past due to shift towards alternatives. Thirdly, Energy Intensity measures the energy intensity for an entire economy (measured as percentage change in energy consumption divided by percentage change in GDP).
A decrease in energy intensity is considered as the most promising route for reducing vulnerability to oil shocks (Bacon and Kojima 2006). For Pakistan, this has remained more or less constant at about 0.9 in 2005-2006, showing that there has not been much improvement in this area.
Finally, the net oil imports in GDP represent the magnitude of the direct effect of a price increase. Pakistan had a value of -5.24 in 2005-2006. Hamilton (2005) argues that a potential macroeconomic effect of oil price is on the inflation rate as long run inflation rate is governed by monetary policy, and so ultimately it depends on how the central bank responds to oil prices.
Oil price shocks have received considerable importance in the empirical literature. Macroeconomists have viewed changes in the oil prices as an important source of economic fluctuations as the oil shocks of mid and late 1970s was followed by low growth, high unemployment, and high inflation in most of the developed countries. However, the shocks of late 1990s and of 2000, although they were of the same size and magnitude comparable to 1970s, but in contrast, GDP growth and inflation have remained relatively stable in much of the industrialized world (Blanchard, et. al. 2007).
Hamilton (1983) empirically establishes a negative relationship between oil prices and macroeconomic variables. Hamilton in a series of studies on the subject (in 1983, 1996, 2000, 2008) established a vital role for oil price increase in most of US recessions. He stresses the importance of oil prices on the macroeconomic activities.
Later on many researchers further supporting and extending on Hamilton’s earlier work, while using different estimation procedures and data tested the relationships between an oil price increase and different macro-economic variables (e.g., Burbidge and Harrison 1984; Gisser and Goodwin 1986; Mork 1984; Hoover and Perez 1994; Federer 1996; Lee, et. al. 1995). Most of the studies have focused on the industrialized countries, restating that oil prices may be an important factor in affecting economic growth in the US and elsewhere. These studies present numerous theoretical perspectives on the oil price shock hypothesis, as well as empirical evidence on the estimated magnitude of such shocks impacting on growth through some of the direct and indirect channels. In addition, it has been shown that there is an asymmetric relationship between oil price shocks and economic recession. Some studies have established that the increase in oil price led to a decline in GDP while the decrease in oil price does not stimulate the economic activity.
In addition, Mork (1989), Mork, et. al (1994), Huang, et. al. (2005), Sadorsky (1999) also emphasized the asymmetry of the impact of oil price shocks on economic activities. The basis for their argument was the oil price declines of the mid-1980s during which the world price of oil halved the linear relationship between oil prices and economic growth appeared to break down. On the similar grounds, Hooker (1996) challenged Hamilton’s findings on the ground, that sample stability is important. Oil prices are endogenous, and that linear and symmetric specifications misrepresent the form of the oil price interaction. He found that oil prices do Granger cause a variety of US macroeconomic indicator variables in data up to 1973 but not in the data afterwards. Oil prices were exogenous before 1973, but not afterwards.
Guo and Kliesen (2005) also found the negative and significant effect of oil futures prices on future gross domestic product, and this effect becomes more significant after oil price changes are also included in the regression to control for the symmetric effect. His findings were in confirmation with the Hamilton (1996, 2003), that is, increase in the price of oil matters less as compared to the future uncertainty about the direction of prices. As the oil price volatility is mainly driven by exogenous events such as significant terrorist attacks and military conflicts in the Middle East. His findings provide economic rationales for Hamilton’s (2003) non-linear oil shock measure, as it captures overall effects, both symmetric and asymmetric of oil shocks on output.
In the literatures of oil price-GDP relationships, earlier studies, which include Pierce and Enzler (1974), Rasche and Tatom (1977), Mork and Hall (1980), Darby (1982), and Bruno and Sachs (1982, 1985) have all documented and explained the inverse relationship between oil price increases and aggregate economic activity. Later, studies by Gisser and Goodwin (1986) and Hickman et al. (1987), empirically proved and confirmed the inverse relationship between the variables for the United States
Most of the earlier studies concerning oil price shocks and volatility and economic activities have been conducted in the context of developed economies. Research concerning the impact of oil price volatility in the context of developing countries is very limited. The reason for the lack of research on the developing countries is may be their less dependence on oil. It is only recently, that these countries are experiencing increased demand for energy. Therefore, very limited research has been conducted with reference to the developing countries. Rafiq, et. al. (2008) estimated the impact for Thialand; Kumar (2005) for India; Cunado, et. al. (2005) for six Asian countries including Thailand, Singapore, South Korea, Malaysia, Phillipines and Japan; Jbir, et. al. (2008) for Tunisia. These studies confirmed the negative impact of real oil prices on output and other macro variables (e.g., price index), using different methodologies, in linear and non-linear specifications, controlling for asymmetries in the oil price data.
In general, empirical studies suggest that oil importing economies are negatively affected by oil price rises. While the structure of various economies may affect the extent to which economic growth is retarded following a price shock, these findings also imply that oil price shocks contribute to the volatility in most of the countries (Gounder, et. al. 2007)
Mork (1989) focuses on the asymmetric effects. He hypothesized that, unlike oil price increases, price declines had little effect on the economy. His regressions confirmed his hypothesis, when the distinction between price increases and decreases was made, the effect of price increases on GNP growth doubled, whereas price declines had a small and statistically insignificant effect. Lee, Ni and Ratti (1995) look into oil price shocks and real U.S GNP growth from 1949 to 1992 in a framework similar to that of Hamilton (1983) and Mork (1989). Other than asymmetric relationships, they also investigate the impact of oil price volatility to the macro economy by means of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. The results obtained showed that, oil price volatility significantly affect the GNP and they also find asymmetric effects between positive and negative normalized shocks. Similar to Lee, Ni and Ratti (1995), Ferderer (1996) also believed that oil price volatility was the missing factor that could explain oil’s macroeconomic effects and added a variable to capture volatility to his regressions that previous studies lacked. Using industrial production growth as a proxy for economic growth, he found that monthly oil price changes could statistically explain 5.7-18.5percent of the fluctuations in industrial production, and oil price volatility could explain an additional 11.7-16.1 percent of the fluctuations. Hamilton (1996) has posited that the reason why standard regressions do not find that oil has a strong effect on economic growth is due to mis-specification. Hamilton (2000) demonstrated that non-linear specifications suggest that oil has stronger effects than linear specifications. Hamilton also noted that regression results may be hampered because the oil price can no longer be treated as exogenous, that is, it can now be driven by demand or supply.
A recent paper by Rodriguez and Sanchez (2005) updates Mork’s (1989), Hamilton’s (1996), and Lee et al’s (1995) respective work. Using standard vector auto regression methods, the analysis on oil price impact on real economic activities is carried out using both linear and nonlinear models. From the findings they find evidence of non-linear impact of oil prices on real GDP. In particular, oil price increases are found to have an impact on GDP growth of a larger magnitude than that of oil price declines, with the latter being statistically insignificant in most cases. Other analyses as such are conducted by Bohi (1991), Smyth (1993), and Cunado and Garcia (2004) and all reported asymmetric effects in their studies.
The study on oil price impact is also extended to global economies, which compares the effect between developed and developing economies, and also oil price impact on importing and exporting countries. The few studies are, IMF (2000), Abeysinghe (2001), and finally Abeysinghe and Forbes (2001). IMF (2000) in general, presents a study on the impact of oil price increase on global economy. In particular, the differential impact of an oil price increase of US$5 per barrel on developed and developing countries is assessed. The study figures that, the impact is found to be greater for developed countries than for developing countries as a group. In regional analyses, the results obtained vary widely, depending on the relative size of oil importing to exporting countries. Oil shocks are explained to lead to lower aggregate demand since the oil price increase redistributed income between the countries that are net oil importers and exporters. The study also figure that, the degree of influence of oil price changes on oil importing countries is found to be different from those of oil-exporting and small open economies. The contributing factors for these differences are explained by different oil intensity levels in domestic production, exports and imports, and degree of openness of an economy. In addition, the study also provides evidence that oil price changes tend to be positively correlated with the economic growth of the oil producing countries. The study also provides estimates of the first round impact of higher oil prices on GDP growth for some ASEAN countries, namely Indonesia (+0.5%), Malaysia (+0.2%), Philippines (-0.5%), and Thailand (-0.4%).
Abeysinghe and Forbes (2001) develop a structural VAR model to measure how a shock to one country can affect the GDP of other countries. It uses trade linkages to estimate the multiplier effects of a shock as it is transmitted through other countries’ output fluctuations. This model is then used to examine the impact of shocks to eleven Asian countries, the U.S., and the OECD countries. The results obtained showed that the ASEAN countries, with relatively smaller economies and are heavily dependent on oil, are much more vulnerable than the OECD economies when faced with world oil prices changes. They also discover that, the United States economy has more control over few variables, i.e. interest rates, which makes it practical to absorb the negative impact of oil price shocks.
Abeysinghe (2001) narrow down the study of IMF (2000) on the impact of oil price changes by focusing on only 12 economies, which includes Indonesia, Malaysia, Singapore, Philippines, and Thailand. By using data over the 1978-1998 periods, his study evaluates the direct and indirect effects of oil prices on GDP growth of these economies. Using a reduced form of bilateral export functions and structural VAR models to link up the GDP series through a trade matrix as proposed by Abeysinghe and Forbes (2001), the study demonstrates that high oil prices affect these economies both directly and indirectly (works through the network of an economy’s trading partners). The findings also implied that, a shock to one country is found to have a statistically significant impact on other countries even if they are relatively minor bilateral trading partners. Consequently, net oil-exporters such as Indonesia and Malaysia are shown to be unable to avoid the negative impacts of high oil prices.
Cunado and Gracia (2003) have reported different results than the predicted. The study on oil price impact is conducted on 15 European countries gives mixed results. They conclude that, the use of either world oil price index or a national real price index is part of the explanation to the difference. Moreover, they could not find any co-integrating long-run relationship between oil prices and economic activity except for the United Kingdom and Ireland. Therefore, they suggest that the impact of oil shocks on economic activity is limited to the short run. Cunado and Gracia (2004) extend their analysis by conducting a comparative study on the influences of oil price changes for some small and open economies for six Asian countries, including Malaysia, Singapore, Philippines, Thailand, and also on OECD countries. The results obtained suggest that oil prices have a statistically significant effect on both economic growth and inflation although the impact is limited to the short-run. When compares the two studies, they figured that the effect on the Asian countries is found to be marginal relative to the effect on OECD countries.
Norasibah .A. et( … ) studied the impact of oil prices on GDP in Malaysia. In particular, three types of oil prices; world oil price (PW), world oil price in domestic currency (PWD), and domestic oil price (PD) are tested against the GDP within VAR framework. The results have documented positive relationship between GDP and oil prices, particularly the PWD and the PD oil prices. In the asymmetric test, significant result is documented in PD analysis only. The finding signifies the presence of asymmetric relationship between oil price changes and the economy. The overall findings lead us to conclude that, change in oil prices affects the GDP. Out of all three oil prices considered in the analysis, PD appears to be most prominent, because significant results are documented both in long and short-run relationships. Based on the asymmetric test results, the effect of oil price (PD) increase or decrease on GDP is different, in which, the event of oil price decrease give more significant effect to the economy.
Darby (1982) had one of the earliest econometric studies that attempted to estimate the economic effects of oil shocks. His study aimed to determine what had caused the 1973-1975 recessions in the US. He figured that, oil shock’s effect on the economy was statistically significant and estimated the 1973 oil shock caused a total cumulative decrease in GNP of 2.5%. In the following year, Hamilton (1983) published what many would consider to be the seminal study on oil shocks. He drew attention to the fact that all but one of the post-war recessions had been preceded by a sharp rise in the price of oil, and set out to demonstrate statistically that, contrary to conventional wisdom, it was oil price increase that caused the recessions.
Based on Hamilton’s work, Burbidge and Harrison (1984) examined the impact of oil price shocks on several macroeconomic variables in seven OECD countries. They converted their VAR estimation into vector moving average (VMA) representation to examine the impact of oil price shocks and used this to analyze the 1973-74 and 1979-80 oil price shocks. The results obtained showed that the 1973-1974 oil embargoes explain a substantial part of the behavior of industrial production (economic activity) in each of the countries examined. All findings appear to be consistent with the work of Hamilton (1983) except for the oil price shock in 1979-1980. In the analysis, they find little evidence that the changes in oil prices had an effect in industrial production. Gisser and Goodwin (1986) tried to capture the effects of monetary policy, fiscal policy, and oil price changes on economic growth, inflation, and unemployment. They figured that the effects of fiscal policy on GNP and unemployment are smaller than the effects of oil price changes, although larger than the effects on the price level.
Rodriguez and Sanchez (2005) updates Mork’s (1989), Hamilton’s (1996), and Lee et al’s (1995) respective work. Using standard vector auto regression methods, the analysis on oil price impact on real economic activities is carried out using both linear and nonlinear models. From the findings they find evidence of non-linear impact of oil prices on real GDP. In particular, oil price increases are found to have an impact on GDP growth of a larger magnitude than that of oil price declines, with the latter being statistically insignificant in most cases. Other analyses as such are conducted by Bohi (1991), Smyth (1993), and Cunado and Perez de Garcia (2004) and all reported asymmetric effects in their studies.
Recently, Shehu (2009) assess the impact of oil price shock and real exchange rate volatility on real economic growth in Nigeria on the basis of quarterly data from 1986Q1 to 2007Q4. His findings reveled that oil price shock and appreciation in the level of exchange rate exert positive impact on real economic growth in Nigeria. He recommends greater diversification of the economy through investment in key productive sectors of the economy to guard against the vicissitude of oil price shock and exchange rate volatility.
By using VAR models for Canada, Germany, Japan, the United Kingdom and the United States, Burbidge and Harrison (1984) show that oil price shocks have a significant negative impact on industrial production. However, they conclude that oil price changes have different impacts on the macro-economy before 1973 than after. Similar results are produced by Gisser and Goodwin (1986) for the US.
Hooker (1996) criticized Hamilton (1983), in finding evidence that oil prices do not seem to be more endogenous to the US macro-economy. He pointed out that oil prices (in linear as well as non-linear specifications) do not Granger-cause most macroeconomic indicators in quarterly data from 1973 up to 1994.
Eltony and Al-Awadi (2001) find evidence that linear oil price shocks are important in explaining fluctuations in macroeconomic variables in Kuwait. Their results show the importance of oil price shocks in government expenditures, which are the major determinant for the level of economic activity in Kuwait.
Raguindin and Reyes (2005) examined the effects of oil price shocks on the Philippine economy over the period of 1981 to 2003. Their impulse response functions for the linear transformation of oil prices show that an oil price shock leads to a prolonged reduction in the real GDP of the Philippines. Conversely, in the non-linear VAR model, oil price decreases play a greater role in each variable’s fluctuations than oil price increases.
Anshasy et.al. (2005) examined the effects of oil price shocks on Venezuela’s economic performance over 1950-2001. They investigated the relationship between oil prices, governmental revenues, government consumption spending, GDP and investment by employing a general to specific modelling (VAR and VECM). They found two long run relations consistent with economic growth and fiscal balance and that this relationship is important not only for the long run performance but also for short term fluctuations.
Berument and Ceylan (2005) examined how oil price shocks affect the output growth of selected Middle East and North African countries that are either exporters or net importers of oil commodities. In this respect, they used a structural vector autoregressive (SVAR) model, focusing explicitly on world oil prices and the real GDP over the period of 1960-2003. Their impulse response analysis suggests that the effects of the world oil price on GDP of Algeria, Iran, Iraq, Jordan, Kuwait, Oman, Qatar, Syria, Tunisia and UAE are positive and statistically significant. However, for Bahrain, Egypt, Lebanon, Morocco and Yemen they did not find a significant impact on oil price shocks.
Olomola and Adejumo (2006) examined the effects of oil price shocks on output, inflation, real exchange rate and money supply in Nigeria using quarterly data from 1970 to 2003. Using VAR methodology they find that oil price shocks do not have any substantial effect on output and inflation. Oil price shocks only significantly determine the real exchange rate and in the long run money supply. They conclude that this may squeeze the tradable sector, giving rise to the “Dutch Disease”.
According to ESMAP (2005) report , statistical evidence shows that there is a small but significant negative association between the level of per capita GDP and the ratio of net oil imports to GDP, so that systematically the lowest income oil importers suffer the most from the direct impact of higher oil prices on the balance of payments. Growth and development therefore tend to reduce the vulnerability to such shocks but this effect is small. The group of countries that are net exporters will experience a substantial improvement in the balance of payments as a result of higher oil prices – the lowest income group (less than US$900 per capita income) would enjoy a 5.21 percent improvement in GDP. For countries such as Angola a US$10 a barrel oil price increase is equivalent to a gain of 30 percent in GDP. Several other developing countries also experience very large gains. The challenge for these countries is to use the extra resources well. Incremental fiscal revenues arising from the higher oil prices need to be spent wisely or sterilized in an oil fund, held for future generations. Transparency over receipts and expenditure becomes more important at times of such large increments in revenue.
Papapetrou (2001) attempted to investigate the linkages among oil prices, real stock prices, interest rates, real economic activity and employment for Greece using a multivariate vector auto-regression (VAR) approach. The empirical results from the paper suggested that while oil prices were important in explaining stock price movements, stock market returns did not lead to changes in real activity and employment. They however, observed that changes in the oil price affected real economic activity and employment.
It was Bruno and Sachs (1982) who analyzed in detail the effects of oil prices of the 1970s on output and inflation. They took the case of UK manufacturing and developed a theoretical model and concluded that higher input prices have played a significant role in the slowdown since 1973 throughout the OECD, Huntington (2004) studied that when the crude oil price doubles, the German output would drop 1.7 % based on the initial output gap and decline 1.3 % based on the oil share, which is less than the 2.3 % decrease for the US. Kilian (2005) indicates that the decrease in output due to an oil shock is temporary and occurs in the second year, that the increase in inflation due to an oil shocks is not permanent and would reach the peak after three to four quarters, and that there is strong evidence of stagflation for Germany, Canada and Japan
Sulaiman D.M (2010) analyzed the impact of recent oil prices variability on Pakistan’s export earnings. Study shows the significant impact of oil price fluctuation and other macro economic variables like GDP growth rate, human capital and imports on Pakistan’s Exports Earnings, but oil prices impact negatively on Exports in Pakistan’s economy. Pakistan’s economy faces the long term relationship with oil price volatility and Export earnings as macroeconomic stability of Pakistan, which is highly dependent on imported oil. This Study had used annual data for the year 1975-2008 and Johnsean co integration technique for finding long run equilibrium.
The vulnerability of oil-importing countries to higher oil prices varies markedly depending on the degree to which they are net importers and the oil intensity of their economies. According to the results of a quantitative exercise carried out by the IEA in collaboration with the OECD Economics Department and with the assistance of the International Monetary Fund Research Department, a sustained $10 per barrel increase in oil prices from $25 to $35 would result in the OECD as a whole losing 0.4% of GDP in the first and second years of higher prices.IEA (2004)
According to report of IEA (2004) Oil prices remain an important macroeconomic variable: higher prices can still inflict substantial damage on the economies of oil-importing countries and on the global economy as a whole. The surge in prices in 1999-2000 contributed to the slowdown in global economic activity, international trade and investment in 2000- 2001. The disappointing pace of recovery since then is at least partly due to rising oil prices: according to the modelling results, global GDP growth may have been at least half a percentage point higher in the last two or three years had prices remained at mid-2001 levels. The results of the simulations presented in this paper suggest that further increases in oil prices sustained over the medium term would undermine significantly the prospects for continued global economic recovery. Oil importing developing countries would generally suffer the most as their economies are more oil-intensive and less able to weather the financial turmoil wrought by higher oil-import costs.
The transmission mechanisms, according to Jin (2008) through which oil prices affect real economic activity include both supply and demand channels. The supply side effects are related to the fact that crude oil is a basic input to production, and an increase in oil price leads to a rise in production costs that induces firms’ lower output. The demand side effect is derived from the fact that oil prices changes affect both consumption and investment decisions. Consumption is adversely affected because increase in oil price affects disposable income and the domestic price of tradable. Investment is adversely affected because such increase in oil price also affects firms’ input prices and thereby increasing their costs. In a comparative study of the impact of oil price shock and exchange rate volatility on economic growth, Jin (2008) discovered that the oil price increases exerts a negative impact on economic growth in Japan and China and a positive impact on economic growth of Russia. Specifically, a 10% permanent increase in international oil prices is associated with a 5.16% growth in Russian GDP and a 1.07% decrease in Japanese GDP. On the one hand, an appreciation of the real exchange rate leads to a positive GDP growth in Russia and a negative GDP growth in Japan and China.
Gounder and Barleet (2007) using both linear and nonlinear oil price transformation discovered a direct link between net oil price shock and economic growth in New Zealand. In addition, oil price shock was discovered to have substantial effect on inflation and exchange rate. While Greenspan (2004) noted that the impact of oil prices alone in modern market-based economies is difficult to infer in a way in which policy is automatically obvious. McKillop (2004) argued that higher oil prices reduce economic growth, generate stock exchange panics and produce inflation, which eventually lead to monetary and financial instability. It will also lead to higher interest rates and even a plunge into recession.
Literature on Exchange rates and Economy
Previous research on the impact of exchange stability on growth has tended to find weak evidence in favor of a positive impact of exchange rate stability on growth. For large country samples; Ghosh, Gulde and Wolf (2003) discovered weak evidence that exchange rate stability affects growth in a positive or negative way. Schnabl (2007) builds on De Grauwe and Schnabl (2005) using both GLS (Generalized Least Squares) and GMM (Generalized Method of Moment) panel estimations for 41 countries in the EMU (European Monetary Union) periphery. The results provide evidence in favor of a robust negative relationship between exchange rate volatility and growth. Also, the issue of which regime of exchange rate is susceptible to macroeconomic stability and growth has been extensively discussed in the literature. Proponents of flexible exchange rates emphasized the need for macroeconomic flexibility in the face of real asymmetric shocks while in contrast; proponents of fixed exchange rates have stressed the (microeconomic) benefits of low transaction costs for international trade, Frankel and Rose (2002).
Farzanegan and Markwardt (2007) investigates the dynamic response of the Iranian industry output, inflation, real effective change, real government expenditures and real import to asymmetric specifications of real light and heavy crude oil prices innovations, using unrestricted VAR models for the period 1988-2004. Impulse response functions and variance decomposition are obtained from each set of model specifications to evaluate how oil price shocks move through major channels of the Iranian economy and how much such shocks contribute to the fluctuations of the variables in the model. Contrary to previous empirical findings for oil net importing developed countries, oil price increases (decreases) have a significant positive (negative) impact on industrial output. Unexpectedly, this paper cannot identify any significant impact of oil price fluctuation on real government expenditures. The response of real imports and the real effective exchange rate to asymmetric oil price shocks are significant. Furthermore, the response of inflation to any kind of oil price sh