Examining crude oil price – Exchange rate nexus for India during the period of extreme oil price volatility

This study probes crude oil price – exchange rate nexus for India using daily data for the time span July 2, 2007–November 28, 2008. Generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) models have been employed to examine the impact of oil price shocks on nominal exchange rate. The study reveals that an increase in the oil price return leads to the depreciation of Indian currency vis-à-vis US dollar. The study also establishes that positive and negative oil price shocks have similar effects, in terms of magnitude, on exchange rate volatility and oil price shocks have permanent effect on exchange rate volatility.     

How does oil price volatility affect non-energy commodity markets?

The influence of price volatility in the crude oil market is expanding to non-energy commodity markets. With the substitution of fossil fuels by biofuel and hedge strategies against inflation induced by high oil prices, the link between crude oil market and agriculture markets and metal markets has increased. This study measures the influence of the crude oil market on non-energy commodity markets before and after the 2008 financial crisis. By introducing the US dollar index as exogenous shocks, we investigate price and volatility spillover between commodity markets by constructing a bivariate EGARCH model with time-varying correlation construction. The results reveal that the crude oil market has significant volatility spillover effects on non-energy commodity markets, which demonstrates its core position among commodity markets. The overall level of correlation strengthened after the crisis, which indicates that the consistency of market price trends was enhanced affected by economic recession. In addition, the influence of the US dollar index on commodity markets has weakened since the crisis.     

Do all clean energy stocks respond homogeneously to oil price?

This paper investigates whether the relationship between oil price and clean energy stock is homogeneous across sub-sectors of the clean energy stock market and its implications for portfolio diversification and clean energy finance policy. We contribute to the literature by being the first empirical paper to document the oil price-clean energy stock relationship at a disaggregate level, thereby providing a more detailed picture of the clean energy stock market. Our findings show that the relationship between oil price and clean energy stock varies largely across clean energy stock sub-sectors. Specifically, biofuel and energy management stocks are the most connected to oil price, while wind, geothermal, fuel cell stocks are among the least connected to oil price. This implies that the hedging cost and effectiveness of a clean energy investment portfolio is dependent on the type of clean energy stock included, therefore, active portfolio management at a disaggregate level is of particular importance. Additionally, policy should take into account the specific characteristics of individual clean energy sub-sectors in order to effectively promote clean energy investment.     

How do oil price shocks affect the output volatility of the U.S. energy mining industry? The roles of structural oil price shocks

This paper focuses on how explicit structural shocks that characterize the endogenous character of international oil price change affect the output volatility of the U.S. crude oil and natural gas mining industries. To this end, we employ a modified structural vector autoregressive model (SVAR) to decompose real oil-price changes into four components: U.S. supply shocks, non-U.S. supply shocks, aggregate demand shocks, and oil-specific demand shocks mainly driven by precautionary demand. The results indicate that output volatility of the U.S. crude oil and natural gas mining industry has significantly negative responses to U.S. supply shocks, aggregate demand shocks, and oil-specific demand shocks, while lacks significant response to non-U.S. supply shocks. Variance decomposition and historical decomposition confirm that U.S. supply shocks occupy most explaining variations in output volatility among the four structural oil shocks. Moreover, the oil-specific demand shocks explain more variation than that of aggregate demand shocks for the crude oil mining industry, but the opposite is true for the natural gas mining industry.     

Is the recent low oil price attributable to the shale revolution?

The U.S. Energy Information Administration estimates that approximately 52% of total U.S. crude oil was produced from shale oil resources in 2015. We examine whether the recent low crude oil price is attributable to this shale revolution in the U.S., using a SVAR model with structural breaks. Our results reveal that U.S. supply shocks are important drivers of real oil price and, for example, explain approximately a quarter of the 73% decline between June 2014 and February 2016. Failure to consider statistically significant structural changes results in underestimating the role played by global supply shocks, while overestimating the role of the demand shocks.     

The third oil price surge – What’s different this time?

The period from 2003 to 2008 was marked by an oil price increase comparable to the two oil price crises in the 1970s. This paper looks in detail at the situation of the oil price crises 30 years ago and compares them along various aspects on the demand and supply side with the recent price increase to identify similarities and differences. While both oil price crises in 1973 and 1979/1980 were ultimately caused by supply actions of members of the Organisation of Petroleum Exporting Countries (OPEC), all three oil price crises were preceded by high demand growth. Other aspects that favoured a high oil price in all three cases were low investments in new oil fields, as a consequence low spare capacity, and a weak US dollar. In addition, the recent oil price surge has been characterised by a high global refinery utilisation and refineries that did not adapt fast enough to the rising demand for lighter oil products. Moreover, broader geopolitical uncertainties, combined with risks associated with the oil trade helped push the oil price into a triple-digit zone. Speculation played only a limited and temporary role in accelerating price movements during the recent price increase.     

Does electricity price matter for innovation in renewable energy technologies in China?

Though the development of renewable energy is rapid, innovation in renewable energy technologies is relatively weak due to the late commencement of renewable energy in China. In addition, renewable energy is mainly introduced into the supply mix of electricity generation, which increases the costs of electricity generation. Higher electricity price will make renewable energy more competitive and call forth renewable energy technological innovation. Based on FMOLS and DOLS models, as well as PMG model, this paper investigates the induced long and short run effects of electricity price, funding support, and economic growth on innovation in renewable energy technologies at the provincial level in China during the period 2006–2016. The Conclusions drawn were: (1) R&D expenditure and economic growth have positive impacts on innovation in renewable energy technologies in the long and short run; (2) Electricity price only has a long run effect on patenting in renewable energy technologies; (3) In the long run, a 1% increase in electricity price can lead to a 0.7825%–1.0952% increase in the patent counts of renewable energy technologies; (4) Electricity pricing system in China does not play any role in driving renewable energy technological innovation in the short run.     

Does oil price affect the value of firms? Evidence from Tunisian listed firms

A new debate on the potential impact of oil price changes on the value of firms was initiated in this paper. Using a stochastic frontier approach, an attempt was made to derive the optimal value Q* of firms and calculate the Q value observed. Then the shortfall (Q*–Q) which represents the inefficiency term was explained. Starting from 19 industrial Tunisian firms listed on the Tunis Stock Exchange between 2007 and 2011, the fact that variation of oil prices can largely explain distortions in the value of firms was empirically demonstrated.     

Modeling oil price–US stock nexus: A VARMA–BEKK–AGARCH approach

This study adds to the existing literature on oil price–US stock nexus in three ways. First, it employs the VARMA–AGARCH model developed by McAleer et al. (2009) within the context of BEKK framework using West Texas Intermediate (WTI) and Brent as proxies for oil market and S&P stocks as a proxy for US stock market. Secondly, it modifies the model to include endogenously determined structural break using the general structure for analyzing breaks with unit roots in Perron (2006). Third, it uses the adopted model to compute optimal portfolio weight and hedge ratios between oil price and US stocks using different sample data based on the break date. On average, our empirical evidence suggests a significant positive return spillover from US stock market to oil market and bi-directional shock spillovers between the two markets. In addition, there is significant own asymmetric shock effect in both markets while volatility spillover from oil market to stock market became pronounced after the break which coincides with the period of global economic slowdown. Similarly, the results of portfolio management differ across the sample data. More importantly, we find that ignoring structural break when it exists may exaggerate hedging effectiveness.     

The economic viability of gas-to-liquids technology and the crude oil–natural gas price relationship

This paper explores the viability of a gas-to-liquids (GTL) technology and examines how GTL penetration could shape the evolution of the crude oil–natural gas price ratio. Much research has established the cointegrated relationship between crude oil and natural gas prices in the U.S. The persistently low U.S. natural gas prices in recent years seem to mark a shift in this relationship, and have led some in industry to begin considering investments in GTL capacity in the US. In order to look forward over decades when the underlying economic drivers may be outside of historical experience, we use a computable general equilibrium model of the global economy to evaluate the economic viability of GTL and its impact on the evolution of the crude oil–natural gas price ratio. Our results are negative for the potential role of GTL. In order to produce any meaningful penetration of GTL, we find it necessary to evaluate scenarios that seem extreme. With any carbon cap GTL is not viable. Moreover, even without a carbon cap of any kind, extremely optimistic assumptions about (i) the cost and efficiency of GTL technology and about (ii) the available resource base of natural gas and the cost of extraction, before the technology penetrates and it impacts the evolution of the crude oil–natural gas price ratio.     

Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response

In a multi-energy collaboration system, cooling, heating, electricity, and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation, they can significantly improve their individual operating efficiency and overall economic benefits. Demand response, as a multi-energy supply and demand balance method, can further improve system flexibility and economy. Therefore, a multi-energy cooperative system optimization model has been proposed, which is driven by price-based demand response to determine the impact of power-demand response on the optimal operating mode of a multi-energy cooperative system. The main components of the multi-energy collaborative system have been analyzed. The multi-energy coupling characteristics have been identified based on the energy hub model. Using market elasticity as a basis, a price-based demand response model has been built. The model has been optimized to minimize daily operating cost of the multi-energy collaborative system. Using data from an actual situation, the model has been verified, and we have shown that the adoption of price-based demand response measures can significantly improve the economy of multi-energy collaborative systems.     

Slow oil shocks and the “weakening of the oil price–macroeconomy relationship”

Many papers have been documenting and analysing the asymmetry and the weakening of the oil price–macroeconomy relationship as off the early eighties. While there seems to be a consensus about the factors causing the asymmetry, namely adjustment costs which offset the benefits of low energy prices, the debate about the weakening of the relationship is not over yet. Moreover, the alternative oil price specifications which have been proposed by Mork (1989), Lee et al. (1995), and Hamilton (1996) to restore the stability of the relationship fail to Granger cause output or unemployment in post-1980 data. By using the concept of accelerations of the oil price, we show that the weakening of this relationship corresponds to the appearance of slow oil price increases, which have less impact on the economy. When filtering out these slow oil price variations from the sample, we manage to rehabilitate the causality running from the oil price to the macroeconomy and show that far from weakening, the oil price accelerations–GDP relationship has even been growing stronger since the early eighties.     

What is behind the increase in oil prices? Analyzing oil consumption and supply relationship with oil price

The continuing increases in oil prices have renewed the argument over the real culprits behind these movements. The growth in demand for oil in international markets, especially from the United States and China, is often identified as the main source of consumption pressure on prices, and thus the upward trend in oil prices. This paper uses unit root tests with two endogenous breaks to analyze the characteristics of oil prices, production, and consumption for several countries. By taking into account structural breaks, we find that many countries’ oil consumption and oil prices are stationary, while other countries are not. We also perform causality tests to determine the direction of any possible relationship between oil price and oil consumption and production. Our statistical analysis reveals that production variables cause oil prices, while oil prices tend to cause consumption. As a result, we claim that the blame for the recent fluctuations in oil prices is more appropriately associated with supply factors, not consumption influences.     

How does petroleum price and corn yield volatility affect ethanol markets with and without an ethanol use mandate?

The recent increase in ethanol use in the US strengthens and changes the nature of links between agricultural and energy markets. Here, we explore the interaction of market volatility and the scope for policy to affect this interaction, with a focus on how corn yields and petroleum prices affect ethanol prices. Mandates associated with new US energy legislation may intervene in these links in the medium-term future. We simulate stochastically a structural model that represents these markets, and that includes mandates, in order to assess how shocks to corn or oil markets can affect ethanol price and use. We estimate that the mandate makes ethanol producer prices more sensitive to corn yields and less sensitive to changes in petroleum prices overall. We note a discontinuity in these links that is caused by the mandate. Ethanol use can exceed the mandate if petroleum prices and corn yields are high enough, but the mandate limits downside adjustments in ethanol use to low petroleum prices or corn yields.     

Do energy prices stimulate food price volatility? Examining volatility transmission between US oil,ethanol and corn markets

This paper examines volatility transmission in oil, ethanol and corn prices in the United States between 1997 and 2011. We follow a multivariate GARCH approach to evaluate the level of interdependence and the dynamics of volatility across these markets. The estimation results indicate a higher interaction between ethanol and corn markets in recent years, particularly after 2006 when ethanol became the sole alternative oxygenate for gasoline. We only observe, however, significant volatility spillovers from corn to ethanol prices but not the converse. We also do not find major cross-volatility effects from oil to corn markets. The results do not provide evidence of volatility in energy markets stimulating price volatility in the US corn market.     

Paying the full price of steel – Perspectives on the cost of reducing carbon dioxide emissions from the steel industry

This study examines the impacts felt downstream of carbon pricing and investments made in CO₂ abatement within the steel industry. Using the supply of steel to a passenger car as a case study, the effects of a steel price increase on cost structures and price at each step of the supply chain were assessed. Since the prices of emission allowances under the European Union Emissions Trading System fall well below those required to unlock investments in low-CO₂ production processes in the integrated steelmaking industry this paper seeks to pave the way for a discussion on complementary policy options. The results of the analysis suggest that passing on the compliance costs of the steel industry would have only marginal impacts on costs and prices for the end-use sectors (e.g., on the production cost or selling price of the passenger car). Under the assumptions made herein, at a carbon price of 100 €/tCO₂, the retail price of a mid-sized European passenger car would have to be increased by approximately 100–125 €/car (<0.5%) to cover the projected increases in steel production costs.     

On the intraday dynamics of oil price and exchange rate: What can we learn from China and India?

The main aim of this paper is to investigate the volatility determinants of crude oil and foreign exchange markets and jump spillover between them. We consider currencies of two major oil-importing countries (India and China) over the sample period of January 1, 2013 to October 31, 2019. We find evidence of positive return spillover from the oil to the foreign exchange market; however, there is a lack of return spillover in the other direction. Oil jumps appear to have a negative impact on exchange rate conditional volatility, and the latter responds asymmetrically to disentangled (positive and negative) oil price jumps. We also report disentangled exchange rate jumps' significant impact on conditional oil price volatility. These results, however, are asymmetric based on the nature of jumps and alternative oil price series. Finally, we do not find evidence of co-jump between the oil and foreign exchange markets. These results have important implications for investors and policymakers.     

Mass and energy-capital conservation equations to study price evolution of non-renewable energy resources,Part III – Energy supply curve

The price evolution of non-renewable resources versus the consumption rate is investigated with the aim of constructing the energy supply curve. The case studied is without accumulation nor depletion of the resources and the mass and energy-capital conservation equations are solved under the condition of the same mass flow rate of extraction and sale. The energy supply curve of extracted resource is dependent on the newly defined parameter, RINE, Rate of Interest of Non-extracted resources on the Extraction rate. The energy supply curve of sold resource is dependent on the newly defined parameter, RISE, Rate of Interest of Sold resources on the Extraction rate, in case the rate of interest of non-extracted resources, r_N, is nil. In general, the energy supply curve of sold resource is dependent also on two dimensionless parameters, Dimensionless Critical Initial Price of Sold resources_, i.e. DCIPS, and Dimensionless Critical Initial Price Extreme of Sold resources, i.e. DCIPES. The energy supply curve of sold resources is investigated under different relations between three parameters, i.e. extraction rate and interest rates of non-extracted and extracted/sold resources. New trends are observed in the economic market of non-renewable energy resources. The energy supply curve of the difference between sold and extracted resource is also obtained and is dependent on two dimensionless parameters, Critical Initial Price Difference_, i.e. CIPD, and Critical Extreme of the Initial Price Difference, i.e. CEIPD. Finally, the predictions obtained with the present approach are compared to the real evolution of the world price of oil and the European price of gas versus the world consumption during the last three decades, i.e. from 1980 until 2005 for oil and from 1984 until 2005 for gas, taking into account inflation, discount and prime rates of the economic market. The agreement is acceptable but, more important, the trend is correctly predicted. The price difference between sold and extracted resources is also investigated versus the dimensionless mass flow rate of extraction. The evolution is dependent on four parameters: RINE, RISE, DCIPS, and DCIPES.     

Wind power integration and power system flexibility–An empirical analysis of extreme events in Germany under the new negative price regime

In this article, the flexibility of the German power market with respect to the integration of an increasing share of electricity from renewable energy sources was analysed. Flexibility limiting system components, which cause negative prices, are explained and illustrated for the German market. The decision of the European Energy Exchange in Leipzig to allow negative price bids is then explained. The empirical data illustrate the flexibility of conventional generating capacities in Germany from October 2008 to December 2009. Of the 86 h of negative spot prices, 19 h were significantly negative, with prices of at least −100 €/MWh. These extreme hours were analysed in greater detail by the examination of different system components. Thereby, load, wind power infeed and conventional generation by fuel type were observed, as well as the market for negative tertiary reserve, as indicators for market tightness. Although the market situations were found to be severe, under the current conditions, it could have been much worse. In order to enable the market to clear at all times, policy recommendations are provided and long-run implications of an increasing RES-E share on the conventional generation capacity are discussed. The article concludes with an outlook on additional power system flexibility options.     

«Would you say that the price you pay for electricity is fair?» Consumers' satisfaction and utility reforms in the EU15

The research question addressed by this paper is a simple one: are European consumers happy with the price they pay for electricity supply services after two decades of reforms? We focus on self-assessed consumers' satisfaction as reported in three waves of the Eurobarometer surveys, 2000-2002-2004, conditioning on a set of indicators of public ownership and liberalisation across the EU-15. After controlling for individual and country characteristics, we find that consumers are happier with the prices they pay when in their country there are both public ownership and liberalisation. We discuss this finding.