Another perspective on gasoline price responses to crude oil price changes

The effects of oil price volatility on the responses of gasoline prices to oil price shocks have received little attention in discussions on the relationship between the prices of crude oil and gasoline. In this paper we consider such effects by using a bivariate structural vector autoregression which is modified to accommodate GARCH-in-mean errors. Our measure of oil price volatility is the conditional variance of the oil price–change forecast error. We isolate the effects of volatility in the price of oil on the price of gasoline and employ simulation methods to calculate nonlinear impulse response functions (NIRFs) to trace any asymmetric effects of independent oil price shocks on the conditional means of gasoline prices. We test whether the relationship between the prices of crude oil and gasoline is symmetric using tests of the null hypothesis of symmetric impulse responses. Based on monthly U.S. data over the period from 1978:1 to 2014:11, our empirical results show that gasoline prices respond asymmetrically to positive and negative oil price shocks. We also find that oil price volatility has a positive effect on the price of gasoline and it contributes to the asymmetries in the transmission of oil price shocks.     

Dynamic link between oil prices and exchange rates: A non-linear approach

We explore the non-linear relationship between crude oil prices and exchange rates of major currencies from quantitative and structural perspectives, by utilizing bivariate normal mixture model. The correlation coefficients between oil prices and exchange rates demonstrate that their dependences typically start from 2004 then dynamically change over time. Then we investigate whether business cycle and oil price shocks as two possible exogenous factors affect the dependence structure of oil-FX linkage. We find significant structural heterogeneity during economic expansion while little evidence of heterogeneity in recession. This finding provides alternative interpretations for the enhanced dependence between oil prices and exchange rates and generates implications of financialization in commodity market. In terms of oil price shocks (Kilian, 2009), the normal mixture model captures significant heterogeneity, implying that unstable oil-FX dependence structure is frequently associated with oil aggregate demand shocks and oil-specific demand shocks. With an emphasis on the dynamic weights of two underlying states, we interestingly find that structural heterogeneities coincide with a variety of geopolitical and economic events. The application of normal mixture not only provide us knowledge of non-linear relationship between oil prices and exchange rates but also guidance for investors in risk management and portfolio diversification complementary to the traditional portfolio theory based on normal distribution.     

Macroeconomic impacts of oil price shocks in Asian economies

This paper analyzes the macroeconomic impact of structural oil shocks in four of the top oil-consuming Asian economies, using a VAR model. We identify three different structural oil shocks via sign restrictions: an oil supply shock, an oil demand shock driven by global economic activity and an oil-specific demand shock. The main results suggest that economic activity and prices respond very differently to oil price shocks depending on their types. In particular, an oil supply shock has a limited impact, while a demand shock driven by global economic activity has a significant positive effect in all four Asian countries examined. Our finding also includes that policy tools such as interest rates and exchange rates help mitigating the effects of supply shocks in Japan and Korea; however, they can be more actively used in response to demands shocks.     

Assessing the impact of US ethanol on fossil fuel markets: A structural VAR approach

Despite the growing importance of biofuels, the effect of biofuels on fossil fuel markets is not fully understood. We develop a joint structural Vector Auto Regression (VAR) model of the global crude oil, US gasoline, and US ethanol markets to examine whether the US ethanol market has had any impact on global oil markets. The structural VAR approach provides a unique method for decomposing price and quantity data into demand and supply shocks, allowing us to estimate the distinct dynamic effects of ethanol demand and supply shocks on the real prices of crude oil and US gasoline. Ethanol demand in the US is driven mainly by government support in the form of tax credits and blending mandates. Shocks to ethanol demand therefore reflect changes in policy more than any other factor. In contrast, ethanol supply shocks are driven by changes in feedstock prices. A principle finding is that a policy-driven ethanol demand expansion causes a statistically significant decline in real crude oil prices, while an ethanol supply expansion does not have a statistically significant impact on real oil prices. This suggests that even though US ethanol market is small, the influence of US biofuels policy on the crude oil market is pervasive. We also show that ethanol demand shocks are more important than ethanol supply shocks in explaining the fluctuation of real prices of crude oil and US gasoline.     

Expectations, learning, and the changing relationship between oil prices and the macroeconomy

This paper estimates a structural general equilibrium model to investigate the changing relationship between the oil price and macroeconomic variables. The oil price, through the role of oil in production and consumption, affects aggregate demand and supply in the model. The assumption of rational expectations is relaxed in favor of learning. Oil prices, therefore, affect the economy through an additional channel, i.e. through their effect on the formation of agents' beliefs.The estimated learning dynamics indicates that economic agents' perceptions about the effects of oil prices on the economy have changed over time: oil prices were perceived to have large effects on output and inflation in the 1970s, but only milder effects after the mid-1980s. Since expectations play a large role in the determination of output and inflation, the effects of oil price increases on expectations can magnify the response of macroeconomic variables to oil price shocks. In the estimated model, in fact, the implied responses of output and inflation to oil price shocks were much more pronounced in the 1970s than in 2008. Therefore, through the time variation in the impact of oil prices on beliefs, the paper can successfully explain the observed weakening of the effects of oil price shocks on real activity and inflation.     

Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications

This paper analyses the changing impact of oil price shocks on a bouquet of metal and agro prices and their implications for investment decisions, during different oil price regimes, separated by structural breaks. Endogenously identifying the structural breaks, we use network analysis to decipher the nature and extent of such shock transfer across different sub periods. We suggest optimal portfolios based on conditional variance estimates to hedge oil shocks during each period. This is the first study to analyse the portfolio decisions during specific oil price regimes. The results are of significant interest to investors and policy makers.     

Are the macroeconomic effects of oil price shock symmetric?: A Factor-Augmented Vector Autoregressive approach

This paper aims to examine the asymmetric effect of oil price shocks on real economic activity in the U.S. within the context of a nonlinear Factor-Augmented Vector Autoregressive (FAVAR) model. By employing simulation methods, we trace the effects of positive and negative oil price shocks on the macroeconomic variables through the Impulse Response Function (IRF). It is found that the negative impacts of higher oil prices are larger than the positive effects of lower oil prices. And the asymmetric effects are more evident when the oil price shocks are larger. The results are robust to different lag specification and choice of factors.     

The asymmetric response of gasoline prices to oil price shocks and policy uncertainty

This study shows that the effect of oil price shocks on the real price of gasoline is interrelated with economic policy uncertainty. Economic policy shocks are linked with increased real price of gasoline and reduced consumption of gasoline. There is evidence that the fluctuation of both real gasoline prices and of gasoline consumption is associated with uncertainty of tax legislation expiration expectation as well as other components of economic policy uncertainty. Positive shocks to economic policy uncertainty have relatively larger effects on gasoline prices than do negative shocks to economic policy uncertainty. Economic policy uncertainty responds asymmetrically to increases and decreases in real oil price. Shocks to economic policy uncertainty account for 16.1% of variation in real gasoline prices and for 4.9% of variation in gasoline consumption in the long-run.     

Dynamic relationship of oil price shocks and country risks

This study investigates the dynamic relationship between oil price shocks and country risks using a Structural VAR framework for a sample of both net oil-exporting and net oil-importing countries over the period January 1994–December 2014. The results reveal that country risk is significantly affected by oil price shocks, but the impacts are different. Unanticipated positive oil price shocks trigger a reduction (addition) in country risk for net oil-exporting country (net oil-importing countries). As to the responses of oil prices to country risk shock, evidence show that country risk shocks have a delayed significantly positive impacts on oil price for oil-exporting country. With respect to the effects of subcomponents of country risk, we find evidence that economic and political risk have a significant impact on supply-side shocks in net oil-exporting countries like Canada, while economic and political risk have a significant effect on supply-side shocks and oil specific demand shocks in net oil-importing countries like the US. These results are particularly important to policy makers and government.     

OPEC and non-OPEC oil production and the global economy

Hamilton identifies 1973 to 1996 as “the age of OPEC” and 1997 to the present as “a new industrial age.” During 1974–1996 growth in non-OPEC oil production Granger causes growth in OPEC oil production. OPEC oil production decreases significantly with positive shocks to non-OPEC oil production in the earlier period, but does not do so in the “new industrial age”. In the “new industrial age” OPEC oil production rises significantly with an increase in oil prices, unlike during “the age of OPEC” period. OPEC oil production responds significantly to positive innovations in global GDP throughout. Over 1997:Q1–2012:Q4 the negative effect on real oil price of positive shocks to non-OPEC oil production is larger in absolute value than that of positive shocks to OPEC oil production. The cumulative effects of structural shocks to non-OPEC oil production and to real oil price on OPEC oil production are large. The cumulative effects of structural shocks to OPEC production and real oil price on non-OPEC production are small. Results are robust to changes in model specification. An econometric technique to predict growth in OPEC oil production provides support for the results from the SVAR analysis. Results are consistent with important changes in the global oil market.     

Economic impact of oil price shocks on the Turkish economy in the coming decades: A dynamic CGE analysis

As a small open economy, Turkey depends on both imported oil and natural gas, importing almost two-thirds of its primary energy demand. This paper analyzes the economic effects of oil price shocks for Turkey as a small, open oil- and gas-importing country. To analyze the potential long-term effects of oil price shocks on macroeconomic variables of interest, including GDP, consumer price inflation, indirect tax revenues, trade balance, and carbon emissions, we developed TurGEM-D, a dynamic multisectoral general equilibrium model for the Turkish economy. Using TurGEM-D, we analyzed the impact of oil price shocks under three distinct scenarios: reference, high and low oil prices. The simulation results show that these oil prices have very significant effects on macro indicators and carbon emissions in the Turkish economy.     

Recent drivers of the real oil price: Revisiting and extending Kilian's (2009) findings

We replicate and update the results of Kilian (2009) to include the period since the financial crisis. We separate the drivers of the price of crude oil shocks into three components: oil supply shocks, aggregate demand shocks and oil-market specific demand shocks. We provide evidence that the run-up of oil prices in 2008 was mostly driven by aggregate demand shocks and to a lesser extend by oil-market specific demand shocks, complementing similar analyses in Baumeister and Kilian (2016a) and Kilian (2017). Our results confirm that the cumulative effect of aggregate demand disruptions on the price of crude oil started before 2007. Furthermore, aggregate demand shocks and oil-market specific demand shocks rather than oil supply shocks have the most significant effects on U.S. output and prices. The findings are robust to an alternative measure of global real economic activity.     

Dynamic impacts of high oil prices on the bioethanol and feedstock markets

This study investigates the impacts of high international oil prices on the bioethanol and corn markets in the US. Between 2007 and 2008, the prices of major grain crops had increased sharply, reflecting the rise in international oil prices. These dual price shocks had caused substantial harm to the global economy. Employing a structural vector auto-regression model (SVAR), we analyze how increases in international oil prices could impact the prices of and demand for corn, which is used as a major bioethanol feedstock in the US. The results indicate that an increase in the oil price would increase bioethanol demand for corn and corn prices in the short run and that corn prices would stabilize in the long run as corn exports and feedstock demand for corn decline. Consequently, policies supporting biofuels should encourage the use of bioethanol co-products for feed and the development of marginal land to mitigate increases in the feedstock price.     

The effect of global oil price shocks on China's metal markets

This paper investigated the impacts of global oil price shocks on the whole metal market and two typical metal markets: copper and aluminum. We applied the autoregressive conditional jump intensity (ARJI) model, combining with the generalized conditional heteroscedasticity (GRACH) method, to describe the volatility process and jump behavior in the global oil market. We separated the oil price shocks into positive and negative parts, to analyze whether oil price volatility had symmetric impacts on China’s metal markets. We further used the likelihood ratio test to examine the symmetric effect of oil price shocks. In addition, we considered the jump behavior in oil prices as an input factor to investigate how China’s metal markets are affected when jumps occur in the global oil market, in contrast to the existing research paying little attention to this issue. Our results indicate that crude oil price shocks have significant impacts on China's metal markets and the impacts are symmetric. When compared with aluminum, copper is more easily affected by oil price shocks.     

Does the source of oil price shocks matter for South African stock returns? A structural VAR approach

In this paper, we investigate the dynamic relationship between different oil price shocks and the South African stock market using a sign restriction structural VAR approach for the period 1973:01 to 2011:07. The results show that for an oil-importing country like South Africa, stock returns only increase with oil prices when global economic activity improves. In response to oil supply shocks and speculative demand shocks, stock returns and the real price of oil move in opposite directions. The analysis of the variance decomposition shows that the oil supply shock contributes more to the variability in real stock prices. The main conclusion is that different oil price shocks affect stock returns differently and policy makers and investors should always consider the source of the shock before implementing a policy and making investment decisions.     

Exogenous shocks and the spillover effects between uncertainty and oil price

This paper evaluates the information spillover between equity-related uncertainty and the oil price before and after the 2008 global financial crisis, and the effects of exogenous shocks on the pattern of information spillover. In particular, we investigate mean and volatility spillovers between uncertainty and the oil price with and without exogenous shocks by using a bivariate EGARCH model. There are two main findings in our paper. First, the evidence ensures significant information transmission between equity-related uncertainty and the oil price, and shows remarkable differences in transmission patterns before and after the crisis. Second, the results show that exogenous shocks can intensify information transmission between oil prices and uncertainty in terms of both the mean and volatility spillover effects. Moreover, exogenous shocks exhibit direct spillover effects on oil prices.     

Oil sensitivity and its asymmetric impact on the stock market

We develop a two-step methodology to facilitate an examination of the impact of oil shocks on stock returns. Oil price volatility is monitored in this study through the use of a regime-switching model, with the presence of jumps subsequently being taken into consideration to examine the asymmetric effects of oil prices on stock returns. Our analysis provides quite conclusive results based upon the use of a regime-switching model with consideration of jumps; that is, when there are significant fluctuations in oil prices (West Texas Intermediate; WTI), the resultant unexpected asymmetric price changes lead to negative impacts on S&P 500 returns. However, the same result does not hold in a regime of lower oil price fluctuations. We therefore suggest that the achievement of a well diversified portfolio should involve the consideration of oil price shocks, which, as a consequence, should also help to improve the accuracy of hedging against oil price risks.     

Oil price shocks and agricultural commodity prices

While the impacts of oil price changes on agricultural commodity markets are of great interest to economists, previous studies do not differentiate oil-specific shocks from aggregate demand shocks. In this paper, we address this issue using a structural VAR analysis. Our findings indicate that the responses of agricultural commodity prices to oil price changes depend greatly on whether they are caused oil supply shocks, aggregate demand shocks or other oil-specific shocks mainly driven by precautionary demand. Oil shocks can explain a minor friction of agricultural commodity price variations before the food crisis in 2006–2008, whereas in post-crisis period their explanatory abilities become much higher. After crisis, the contributions of oil-specific factors to variations in agricultural commodity prices are greater than those of aggregate demand shocks. The results from an alternative SVAR confirm the robustness of our main findings.     

The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis

This paper investigates the effects of oil price shocks on Asian exchange rates. We employ quantile regression analysis and allow for structural breaks and asymmetry. Our results indicate that positive and negative oil price shocks have asymmetrical effects on exchange rate returns that vary in significance, size, and sign throughout the distribution of exchange rate returns. The impact of oil price shocks is also affected by market conditions (bearish and bullish currency markets). During bullish markets in domestic currencies, (at lower quantiles of currency movements in terms of U.S. dollar exchange rates), rising oil prices cause further appreciation for Indonesia, Korea, the Philippines, and Thailand currencies. During bearish markets in the domestic currencies (at higher quantiles of exchange rate movements in terms of U.S. dollar exchange rates), rising (falling) oil price causes further currency depreciation for Indonesia (Malaysia). Thus, currencies respond differently to oil price shocks under extreme bullish or bearish currency market conditions and the impact of rising or falling oil prices on foreign exchange markets can vary by country and market conditions.     

Does the volatility of commodity prices reflect macroeconomic uncertainty?

While there exists numerous studies on the macroeconomic effects of oil and commodity shocks, the literature is quite silent on the impact of macroeconomic uncertainty on oil and commodity prices and, especially, on their volatility. This paper tackles this issue through the estimation of a structural threshold vector autoregressive (TVAR) model on a sample of 19 commodity markets. We aim at (i) assessing whether the effect of macroeconomic uncertainty shocks on commodity price returns depends on the degree of uncertainty, and (ii) investigating the transfer from macroeconomic uncertainty to price uncertainty using a newly developed measure of commodity price uncertainty. Our findings show that both agricultural and industrial markets are highly sensitive to the variability and the level of macroeconomic uncertainty, while the impact on precious metals is more parsimonious given their well-identified safe-haven role in time of economic turmoil. In addition, we find evidence that the recent 2007–09 recession has generated an unprecedented episode of high uncertainty in numerous commodity prices. Interestingly, our analysis further reveals that volatility and uncertainty in prices can be disconnected. This is especially true for the oil market as most important shocks in the 1990s and the beginning of the 2000s that lead to price volatility do not generate price uncertainty, highlighting the relevance of our uncertainty measure in linking uncertainty to predictability rather than to volatility.