proxy for uncertainty is the conditional variance of oil prices. This proxy reflects the dispersion in the forecast error generated by an econometric model applied to historical data and may not capture other forward-looking components of uncertainty that are not parameterized in the model. It may also be correlated with some other factor that is driving our result. Autoregressive conditional heteroscedasticity (ARCH-) based measures of uncertainty, however, have been very common, at least since their seminal application by Engle (1982) to inflation uncertainty. Second, our model does not decompose innovations in oil prices into components representing demand and supply as in Kilian (2009a). In this sense, our “oilprice shocks” may reflect the average composition of oil demand and oil supply shocks over the sample period.
There are a number of studies that have investigated the effects of oilprice shocks on various macroeconomic variables in the case of Nigeria. For example, Ayadi et al. (2000) examined the impact of the energy (or oil) sector on the functioning of the Nigerian economy, including the financial markets using a standard VAR and found the energy sector to exert significant influence on the economy. Also, Ayadi (2005) analyzed the relationship between oilprice changes and economic development via industrial production with a standard VAR and found that an increase in oil prices does not lead to an increase in industrial production in Nigeria. Recent studies have revisited the issue. For example, Chuku et al. (2011) assessed the relationship between oilprice shocks and current account dynamics in Nigeria using a standard VAR and found oilprice shocks to have a significant short-run effect on current account balances. Moreover, Iwayemi and Fowowe (2011) found oilprice shocks to have weak impact on most macroeconomic variables in Nigeria. The major limitation of these studies is that they failed to account for the observed volatility in oil prices, and therefore left out an important transmission channel. Our paper can be seen as an important improvement upon these studies. In particular, our paper is an extension of the studies on oilprice shocks and the real economy. The paper is closely related to those of Elder and Serletis (2010), and Aye et al. (2014) who studied the role of oilpriceuncertainty in the real economy for the US and South Africa, respectively. Unlike these studies, we consider an oil producing economy which also doubles as an importer, and by classification is a developing country with various structural and institutional problems. Specifically, we analyzed the effect of oilpriceuncertainty on the real output. Then we considered whether the real output responded asymmetrically to oilprice shocks.
This paper investigates the effect of oil income on real exchange rate defined in Iranianeconomy from 1981 to 2012. This study uses Unit Root Tests, Cointegration techniques, Engle-Granger test, Vector Error Correction Model (VECM). The main findings of this paper are: (i) long run relationship exists between the oil income and Real Exchange Rate (REXR). (ii) The real exchange rate is an important variable to the oil income and oilprice, and devaluation will improve the income growth rate of Iran in the long run. (iii) Unilateral causality is found among the variables of the model. As implication, in order to achieve the desired effects on oil income, Iran should depend on policy that focusing on the variable of real exchange rate. The results show that there is a long run co-integration relation between oil income and real exchange rate.
A number of studies have investigated the effects of oilprice shocks on various macroeconomic variables in the case of Nigeria. For example, Ayadi et al. (2000) examine the impact of the energy (or oil) sector on the Nigerian economy, including the financial markets, using standard vector autoregression (VAR) and find the energy sector exerts significant influence on the economy. In addition, Ayadi (2005) analyzes the relation between oilprice changes and economic development via industrial production with standard VAR and finds that an increase in oil prices does not lead to an increase in industrial production in Nigeria. Recent studies have revisited the issue. For example, Chuku et al. (2011) assess the relation between oilprice shocks and current account dynamics in Nigeria using a standard VAR and find oilprice shocks to have a significant short-run effect on current account balances. Moreover, Iwayemi and Fowowe (2011) find oilprice shocks to have a weak impact on most macroeconomic variables in Nigeria.
However, despite the vastness of literature on the macroeconomic consequence of oilprice shocks as well on an optimal fiscal policy of oil- producing economies, only a few studies have actually evaluated the impact of oilprice shocks on the fiscal activity of such economy.In this regard particularly in recent time, studies by Aregbeyen and Fasanya  as well as Aregbeyen and Kolawole  for the example of Nigeria, Anshasy and Bradley  for the cases of selected oil exporting countries, Farzanegan  for Iran, Jbir and Zouari-Ghorbel  Tunisia, Farzanegan and Markwardt  Iranianeconomy, Reyes-Loya, M. and Blanco  and Tijerina-Guajardo and Pagán  for Mexico. Some of these studies concluded that oil prices influence fiscal policy and that can be a key propagation mechanism for transmitting oilprice shocks to the domestic economy ([25,26,27,28]). Ossowski et al.  in particular emphasised the trade-offs between increasing spending – in response to higher oil prices – and the institutional ability to effectively and efficiently absorb such an increase. They find that while the latest oil boom (2004–2008) allowed oil- producing countries to increase public spending, these countries had relatively low indices of government effectiveness.
As mentioned above, oilprice rise often leads to recessions. This happens because, during financial uncertainty, consumers opt for a cut back, avoiding especially non-essential spending, in order to have enough money for basics, such as food and petrol for travelling. Such cut-backs in spending lead to unemployment in those sectors of the economy that consumers opted for cut back (e.g. going on holidays and restaurants). Indeed, when oil prices are high, people understandably have less financial resources to consider a vacation travel, thus the demand for airline tickets drops, prompting airline management to consider closing down certain destinations. Consequently very likely the reduction of the number of airline staff may ensue. The potential rise in unemployment in such business sectors as airline, hotels and catering industry will further aggravate the spending capacity, which, in turn deepening further crises in other sectors too.
Following the leading approaches employed in literature, both symmetric and an asymmetric specification of real oilprice changes are employed for the developing economies as well. Berument and Ceylan (2005) analyzed the effects of symmetric oilprice shocks on industrial production of Middle East and North African countries over the period 1960-2003. They showed that oilprice shocks increased the industrial production of Iraq, Jordan, Kuwait, Algeria, Oman, Syria, Tunisia, Qatar, Iran, and Oman. Olomola and Adejuma (2006) studied the effects of oil shocks on output, real exchange rate, money supply, and inflation in Nigeria over the period 1970- 2003. Their empirical results indicated that the oilprice shocks did not affect output and inflation but had strong effect on money supply and exchange rate. Sari and Soytas (2006) analyzed the effects of oilprice shocks on industrial production, stock returns, and interest rates in Turkey for the period of 1987Q1 – 2004Q3. They conclude that oilprice shocks do not seem to affect the macroeconomic variables in Turkey. Farzanegan and Markwardt (2009) studied the effects of asymmetric oilprice shocks on an oil exporting Iranianeconomy from 1975Q2 to 2006Q4. Their empirical findings indicated that positive oilprice shocks increased the real effective exchange rate, real imports, real GDP per capita, inflation and real government expenditures. On the other hand, the negative oilprice shocks decreased the real effective exchange rate and real GDP per capita and increased the inflation and the real government expenditures. Kumar (2009) found that oilprice shocks negatively affected industrial production of the Indian economy over the period 1975Q1- 2004Q3. Chuku et al. (2010) investigated the effects of oil shocks on Nigerian economy between 1970Q1 and 2008Q4. They found that after the positive oilprice shock output and inflation increased and oil prices Granger cause inflation. Mendoza and Vera (2010) analyzed the influence of oilprice shocks on Venezuela during the period 1984Q1—2008Q3. They reported that oil shocks had positive and significant effects on output and the Venezuelan economy is more responsive to increases in oil prices than decreases.
lines indicate the timing of the outbreak of the six major historical events. The October War in October 1973 and Gulf War in August 1990 are marked by sharp increases of oilprice immediately following the wars. Oilprice jumped 25 percent and 48 percent after the October War and the Gulf War, respectively. The Iranian Revolution triggered a persistent rise in oilprice. Oilprice increased continuously for almost two years after the revolution. The Iran-Iraq War in September 1980 witnessed a temporary increase followed by a persistent decline in oilprice. The real oilprice reached 45 dollars per barrel shortly after the war but started a process of five year decline ultimately reaching 10 dollars per barrel. After the breakout of Afghan War in October 2001 real oilprice dropped for three consecutive months, but after four months, price began to rise significantly. Also, after the eruption of the Iraq War, the oilprice decreased consecutively for two months. A possible reason for the decrease is the expectation that the U.S. would have improved access to the Iraqi oil reserves after the war.
Some studies distinguish priceuncertainty from mere price change, assuming that priceuncertainty has specific effects on the economy. Ferderer (1996) calculates monthly oilprice volatility as a standard deviation of daily price changes and argues that volatility has an explanatory power that can estimate fluctuations in U.S. economic output. Ahmed and Wadud (2011), on the other hand, employ an Exponential General Auto Regression Conditional Heteroscadasticity (EGARCH) model to estimate monthly oilprice volatility, apply the SVAR model to 1986 to 2009 monthly data, and thus analyze the effects of the oilprice shock on Malaysia’ s industry. They suggest that oilprice volatility negatively affects Malaysian industrial production. Notably, they point out that oilprice volatility lowers price levels over the long term, and the Malaysian authorities respond to this with an expansionary monetary policy to stimulate the economy. The Malaysian case is an example of how a government responds to the effects of an international oilprice shock. In general, developing countries like Nigeria, as opposed to industrialized countries, have only limited financial tools to implement financial policy, so it is worth looking at how the monetary authority of such a resource rich country responds to an international oilprice shock.
More specifically, we use (i) Jurado’s et al. (2015) macroeconomic uncertainty index (JMU), which expresses the common volatility of the unforecastable components of 132 macroeconomic indicators; (ii) The Economic Policy Uncertainty Index (EPU), which is constructed based on three components, i.e. newspaper articles of the ten largest newspapers of the US, the temporary provisions of the tax code expiration of the US and the factor of disagreement between the opinions of economic forecasters. Thus, EPU combines the different sources of uncertainty which are linked to the policy making and political conditions in an economy, without explicitly considering the country’s macroeconomic fundamentals ; (iii) The Equity Market Uncertainty Index (EMU), which is based on an automated text- search process from Access World News’s NewsBank service news articles that contain terms related to "uncertainty", "economy", "stock price" and "equity market"; (iv) The Implied Volatility Index of S&P500 (VIX), which is often characterized as the “fear index” and it is the leading measure of market expectations of the implied volatility of S&P500 index options over the upcoming 30-day period; and (v) the Conditional OilPrice Volatility (OCV), which is a measure of commodity uncertainty. We approximate commodity-related uncertainty with the oilprice volatility, given that oil is one of the most important traded commodities in the world and one of the most important production inputs. For this particular uncertainty indicator, we construct an additional oilprice volatility series (vi), namely the Realized OilPrice Volatility (denoted as ORV) for robustness purposes. The usage of these two volatility series is justified by the fact that realized volatility is a more precise and less noisy estimator, according to the literature (e.g. Andersen and Bollerslev, 1998), but it requires no-freely available data for its construction, which are not always available to researchers. On the other hand, the conditional volatility is a widely applied and accepted volatility estimator and requires daily data.
From the perspective of demand, rising oil prices and the subsequent increase in costs of production and general level of prices reduce production and employment opportunities. Oil shocks create uncertainty about the economic state of the country in the future. This leads to the postponement of consumption and investment decisions made by the people. From a more general perspective, rising oil prices decreases the world demand, because this causes the flow of income and resources from oil importing countries to oil exporting countries. Since the decrease of demand in the first group is much higher than the increase of demand in the second group, the total global purchasing power and aggregate demand decreases. On the other hand rising oil prices may have an adverse impact on the trade balance in oil- exporting countries. This is because of the fact that although the rise in oil prices leads to an increase in foreign exchange earnings from oil exports, but it has an overall adverse impact on the economy (Nematollahi and Tabatabaee, 2011- 2012; 154).
What is different between the recent price fall and that of 2008 is the extent to which price forecasts have moved. Markets which failed to predict the spectacular price fall are relatively confident that prices will remain below / around $70 a barrel through to 2017, however as shale gas production begins to slow and as demand recovers slightly over the coming years this could mean a faster-than-expected return to higher prices. The stance of OPEC and Saudi Arabia remains critical. If their current policy of maintaining production levels were to change – and output to be sharply curtailed – the price could soon rise. It is certainly true however that various plausible scenarios for coming weeks and months are feeding through to uncertainty and hence volatility in forward oil markets. Price volatility – measured by using futures contracts – has increased sharply over the last six months, and now stands at its highest levels for over five years (i.e. 2010). It would be interesting to better understand the separate, but linked, effects on production and exploration of low oil prices and high (forward) price volatility.
Second, there level of oil revenue changed from 1990s to 2000s. Non- linear effects of oil revenue in an economy are discussed in the literature since mid-1980s, when the decrease of the oilprice did not affect output positively (see Hamilton (1996) or Jimenez-Rodriguez and Sanchez (2005) among others). Adapting these theories for oil exporting countries (see Farznegan and Markwardt (2009)), this means that an increase in oil revenue does not have exactly the opposite effect of a decrease in oil revenue. As a result, there is a possibility that the role of oil in Iranianeconomy changes from 1990s to 2000s. The formation of the exchange reserve fund and exchange rate unification policy in early 2000s, are two other changes that might have changed the parameters of a macro-model in Iranianeconomy. As a result, in this study we estimate a TVP-VAR model of Iranianeconomy.
The assumption of constant conditional correlation facilitates the simplicity of the system estimation. The mean equation for real stock market return is assumed to be dependent on the lag of real oilprice change while the mean equation for real oilprice change is assumed to be independent of the lag of real stock market return. 3 The lags are chosen so that the system equations are free of serial correlation. Panels A and B contain the results of the conditional means and variances for stock market return and oilprice change, respectively. Referring to Panel A, stock market return is not affected by oilprice change. In Panel B, Oilprice change is affected by its one-period lag. The coefficients in the two conditional variance equations are non-negative. Both conditional variance equations give significant ARCH and GARCH terms (α and β). The sum of the coefficients of the ARCH and GARCH terms for real stock return is 0.998 whereas the sum of coefficients for real oilprice change is 0.939. These results show that the GARCH variance series as measures of volatility or uncertainty is stationary. The constant conditional correlation in Panel C is -0.062, which is low and not statistically significant. The system diagnostic test using residual portmanteau test for autocorrelation accepts the null of no autocorrelation as indicated by Q(8) statistic. Therefore, the system equations are free of serial correlation. The volatility series are generated so as to examine their impacts on stock market return and volatility in the standard Granger causality test.
Presently the research paper has drawn the conclusion based on the data analysis and findings, based on the outcome of the table no 1 the study found that the huge variations is there crude oil prices fluctuation and great draw back and insignificant impact on the economic development activity (2010 - 2018). In this concern, policymakers, financial analyst and economists have paid close thoughtfulness to alterations in internationally traded crude oil prices and apprehensive about the prospective impact of oilprice shocks on Indian economic development activity. The study has examined the how the effect of crude oilprice changes on the Indian economy fluctuates, the paper finds the fluctuation of economy indicators has dependent on the fundamental cause of the oilprice shock, that is, whether oilprice variations are motivated by shifts in oil demand or supply. Moreover, the paper find that the explicit cause of the oilprice shock distresses the size and nature of the responses of foremost Indian macroeconomic aggregates. In specific, when an increase in oil prices is instigated by an oil supply disorder in India with this an insistent to deterioration in its GDP and a rise in the CPI inflation. The outcome of the table no -4 has revealed that the Indian Government debt volatility is mostly elucidated by foreign oil intensity shocks as these shocks cause main lead to create the fluctuations in Indian Government revenue. And the study found that the overseas oil shocks are the highest responsible of Indian crude oilprice fluctuation. Further This research paper examined the impact of crude oilprice shockwaves on the eight macroeconomic variables i.e. GDP, IIP, WPI, real output, real exchange rate interest rate and inflation using Structural Vector Autoregressive (SVAR) model during period from 2010 to 2018.
The recoverable reserves of global offshore oil are about 135 billion tons, while those of natural gas are about 1.4 million cubic meters which respectively account for 51% and 42% of those on land. While among them, about 30% are deepwater resources . Since the drill of the first deepwater exploration well in 1975, rich reserves and bright development prospect of deepwater oil and gas resources have attracted more than 60 countries to explore and develop in the deep sea. Investment on deepwater oil and gas development has shown exponential growth and will exceed investment on shallow water in the next few years. Deepwater oil and gas development technology has continuously achieved breakthroughs, and depth of drilling operation has reached 3000 meters. The proportion of deepwater oil and gas production keeps on increasing which will jump from 7% of global oil and gas production to 13% in 2035. In addition to traditional “Deepwater Golden Triangle” district in Gulf of Mexico, Brazil and Western Africa, Australia, Southeast Asia and many other new focal areas also show bright potentials. At present, production of deepwater oil and gas in Gulf of Mexico and Brazil has exceeded that of shallow water areas. Petroleum production in Gulf of Mexico even accounts for DOI: 10.1051/
Some studies emphasize the mechanism of return and volatility transmission between oil and stock markets and their sector indices. Malik and Ewing (2009) use weekly data during 1992 to 2008 to examine volatility transmission between oil prices and equity sector returns. They employ bivariate GARCH models to estimate the mean and conditional variance simultaneously and find the existence of significant transmission of the United States sector index returns and volatility of oil prices. Arouri et al. (2011) employ a generalized vector autoregressive-generalized autoregressive conditional heteroskedastic (VAR-GARCH) approach to examine volatility transmission between oil and stock markets in Europe and the United States at sector level using weekly data. Their results show that there is a widespread direct spillover of volatility between oil and stock sector returns. Furthermore, the volatility cross effects run only from oil to stock sectors in Europe while bilateral spillover effects are observed in the United States. Masih et al. (2011) find a negative impact of oilprice volatility on real stock return in South Korea. Jouini (2013) employs the VAR-GARCH procedure to investigate the link between world oilprice and stock sectors in Saudi Arabia using weekly data during 2007 to 2011. The results show the existence of return and volatility transmission between oilprice and stock sectors.
The intuition for the decline in real wages is that with ex post Leontief technology, labor cannot be reallocated to relatively efficient machines, which in turn reduces labor demand.On the labor side, we should observe lower consumption and lower leisure as the high energy prices generate wealth effect on the consumption behavior of the households. Lastly, the real wage has to decline to clear the labor market. Lastly, some authors have argue that stagflation of the 1970s were largely due to factors other than oil. Barsky and Kilian (2002) claim that stagflation may have been partly caused by exogenous changes in monetary policy, which coincided in time with the rise in oil prices. Bernanke, Gertler and Watson (1997) argue that much of the decline in output and employment was due to the rise in interest rates, resulting from the Feds endogenous response to the higher inflation induced by oil shocks.
On the other hand, Alley, et al.  observe that one of the impacts of oilprice shocks on economic growth and performance of an oil exporting country like Nigeria is the “Dutch Disease Syndrome”. This is a phenomenon whereby a sudden boom in oilprice cannot sweep through a developing economy that is yet to be diversified and large enough to absorb the inflow without causing inflation and at the same time placing upward pressure on the exchange rate . To this effect, Mieiro and Ramos  argue that there is always a resource pull effect and spending effect that result when large inflow from oil export hits a less diversified economy. Thus, this presents a more complex scenario for Nigeria. But taking into account that the oilprice in both of the oil importing and oil exporting countries affect the aggregate supply and demand, therefore, it is important to evaluate its effect on economic growth.
In the view that oilprice shocks have detrimental effects on Kenya’s macroeconomic performance, the government should adopt prudent fiscal and monetary policies in relation to oil prices. This could be through elimination of some taxes on crude oil imports and introduction of oilprice subsidies. Crude oilprice subsidies are necessary, since increased taxation only work to reinforce the negative impact of crude oilprice shocks on the economy. Taxes on crude oil imports should thus be reduced and if possible completely removed. This is because removal of taxes will go a long way to reduce the cost of production of producers. In addition, oilprice subsidies and reduced taxation as is the case in Ghana, are likely to induce private investment and foster growth. Increased investments would provide an opportunity for increased government revenue through taxation.