How does the U.S. natural gas market react to demand and supply shocks in the crude oil market?

In this paper we use monthly data (over the period from January 1976 to December 2012) and a structural VAR model to disentangle demand and supply shocks in the global crude oil market and investigate their effects on the real price of natural gas in the United States. We identify the model by assuming that innovations to the real price of crude oil are predetermined with respect to the natural gas market and show that close to 45% of the variation in the real price of natural gas can be attributed to structural supply and demand shocks in the global crude oil market.     

What drives volatility in natural gas prices?

We examine the primary drivers of U.S. natural gas price volatility. To do so, we apply a structural heterogeneous autoregressive VAR (SHVAR) model, accommodating structural breaks in both the coefficient and volatility, to monthly time series data on natural gas supply, demand and price between January 1978 and July 2018. We detect several structural changes in coefficients and shock volatility in the natural gas market. Our findings indicate that the response of natural gas prices differs significantly depending on the regime and type of shock in the natural gas market. While demand shocks specific to the natural gas market are the primary drivers of natural gas price volatility, structural supply shocks also play a significant role in explaining movements in natural gas prices. Our results suggest that failure to consider structural breaks in the coefficient and volatility may result in biased estimates and distorted impulse responses of the impact of shocks on natural gas price volatility.     

Oil prices,fundamentals and expectations

This paper empirically investigates the relationship between oil prices, traditional fundamentals and expectations. Informational frictions may force a wedge between oil prices and supply and/or demand shocks, especially during periods of elevated risk aversion and uncertainty. In such a context, expectations can be a key driver of oil price movements and their impact can vary over time. Overall, we find that both traditional oil fundamentals and forward-looking expectations matter for oil prices. Our findings show that the real price of oil responds differently to expectations shocks of business leaders, consumers and aggregate markets. Our TVP-VAR approach provides evidence that business leaders' expectations play an important role in terms of oil price fluctuations and the impact is stronger in periods of elevated global oil demand. In terms of traditional oil market fundamentals, we find that oil prices have been significantly affected by the recent US shale oil boom. Moreover, global oil demand had a positive impact upon oil prices, especially from the mid-2000s. Several alternative model specifications prove the robustness of our analysis.     

The dynamic linkages between crude oil and natural gas markets

The time varying price spillovers between natural gas and crude oil markets for the period 1994 to 2014 are investigated. Contrary to earlier research, we show that in a large part of our sample the natural gas price leads the price of crude oil with price spillover effects lasting up to two weeks. This result is robust to a battery of tests including out-of-sample forecasting exercises. However, after 2006, we detect little price dependencies between these two energy commodities. These findings arise due to a conjunction of both demand and supply-side shocks arising from both natural and economic events, including Hurricane Katrina, the Tohoku earthquake and the Global Financial Crisis, as well as infrastructure and technological improvements. The increased use of new technologies such as hydraulic fracking for the extraction of gas and oil in particular affected supply in the latter part of the study. We conclude that the long term relation present in the early part of the sample has decoupled, such that price determination of these two energy sources is now independent.     

What drives commodity price booms and busts?

We provide evidence on the dynamic effects of aggregate commodity demand shocks, commodity supply shocks, and storage demand or other commodity-specific demand shocks on real commodity prices. We analyze a new data set of price and production levels for 12 agricultural goods, metals, and soft commodities from 1870 to 2013. We establish that commodity demand shocks strongly dominate commodity supply shocks in driving prices over a broad set of commodities and over a long period of time. While commodity demand shocks have gained importance over time, commodity supply shocks have become less relevant.     

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.     

World crude oil and natural gas: a demand and supply model

This paper examines world markets for crude oil and natural gas over the period 1918–1999; it analyzes the time-series properties of output and prices and estimates demand and supply elasticities during 1918–1973 and 1973–1999. Oil and gas prices were stable during the first period; they became volatile afterwards, reflecting deep changes in the market structure following the oil shock in 1973. Demand price elasticities were too low; however, demand income elasticities were high. Supply price elasticities were also too low. The elasticity estimates help to explain the market power of the oil producers and price volatility in response to shocks, and corroborate elasticity estimates in energy studies.     

An analysis of industrial demand for natural gas

Several analysts have proposed the theory that there is a frustrated demand for natural gas in the United States. According to this theory, the natural gas curtailments of the 1970s have convinced industrial users that natural gas is not reliably available. The users are willing to buy fuel oil at a premium and store it to assure a reliable energy supply. If this theory is correct, as the supply of natural gas becomes more reliable, natural gas should be able to recapture the market share it lost to fuel oil.To investigate this theory, a state-level data base on demand for fuel oil and natural gas by all manufacturing sectors for 1971 and 1974 to 1979 was developed. Then a model was developed to explain manufacturers' demand for fuel oil and natural gas during this period on the basis of fuel price and the availability of natural gas. Rather than a frustrated demand for natural gas, we find an excess demand for natural gas in several states. Fuel oil may be able to capture the market from natural gas in these states.     

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.     

North American natural gas and energy markets in transition: insights from global models

This modeling comparison exercise looks at the global consequences of increased shale gas production in the U.S. and increased gas demand from Asia. We find that differences in models' theoretical construct and assumptions can lead to divergences in their predictions about the consequences of U.S. shale gas boom. In general, models find that U.S. High Shale Gas scenario leads to increased U.S. production, lower global gas prices, and lower gas production in non-U.S. regions. Gas demand in Asia alone has little effects on U.S. production; but together with the shale gas boom, the U.S. can have a large export advantage. Overall, models find U.S. exports level range from 0.06 to 13.7 trillion cubic feet (TCF) in 2040. The comparison of supply, demand, and price changes in response to shocks reveals important differences among models. First is how the demand shocks were implemented and how the model responds to shocks: static and elastic within each time period vs. endogenous to the long-term gross domestic product (GDP) growth. Second is how the supply response is expressed through fuel/technology substitutions, particularly the flexibility of cross-fuel substitution in the power sector. Identifying these differences is important in understanding the model's insights and policy recommendations.     

The effects of oil price shocks on output and inflation in China

Crude oil price shocks derive from many sources, each of which may bring about different effects on macro-economy variables and require completely different designs in macro-economic policy; thus, distinguishing the sources of oil price fluctuations is crucial when evaluating these effects. This paper establishes an open-economy dynamic stochastic general equilibrium (DSGE) model with two economies: China and the rest of the world. To assess the effects of oil price shocks, the CES production function is extended by adding oil as an input. Based on the model, the effects of four types of oil price fluctuations are evaluated. The four types of oil price shocks are supply shocks driven by political events in OPEC countries, other oil supply shocks, aggregate shocks to the demand for industrial commodities, and demand shocks that are specific to the crude oil market. Simulation results indicate the following: Oil supply shocks driven by political events mainly produce short-term effects on China's output and inflation, while the other three shocks produce relatively long-term effects; in addition, demand shocks that are specific to the crude oil market contribute the most to the fluctuations in China's output and inflation.     

Dynamic connectedness of oil price shocks and exchange rates

Using a novel method of isolating the oil price shocks, we study how different sources of oil price shocks are connected to exchange rates of major oil-dependent countries using daily data from March 1996 to February 2019. We find that oil price shocks resulting from changes in demand and risk significantly contribute to variation in exchange rates, while supply shocks have virtually no impact. The connectedness of this relationship between oil price shocks and exchange rates has significantly increased after the global financial crisis. We also find that oil price shocks do not explain the variation in exchange rate volatility but we document significant volatility connectedness among exchange rates. Our findings have important implications for policy makers and financial market participants.     

The relationship between global oil price shocks and China's output: A time-varying analysis

We employ a class of time-varying Bayesian vector autoregressive (VAR) models on new standard dataset of China's GDP constructed by Chang et al. (2015) to examine the relationship between China's economic growth and global oil market fluctuations between 1992Q1 and 2015Q3. We find that: (1) the time varying parameter VAR with stochastic volatility provides a better fit as compared to it's constant counterparts; (2) the impacts of intertemporal global oil price shocks on China's output are often small and temporary in nature; (3) oil supply and specific oil demand shocks generally produce negative movements in China's GDP growth whilst oil demand shocks tend to have positive effects; (4) domestic output shocks have no significant impact on price or quantity movements within the global oil market. The results are generally robust to three commonly employed indicators of global economic activity: Kilian's global real economic activity index, the metal price index and the global industrial production index, and two alternative oil price metrics: the US refiners' acquisition cost for imported crude oil and the West Texas Intermediate price of crude oil.     

Validating energy-oriented CGE models

Although CGE models have received heavy usage — particularly in the analysis of broad-based policies relating to energy, climate and trade, they are often criticized as being insufficiently validated. Key parameters are often not econometrically estimated, and the performance of the model as a whole is rarely checked against historical outcomes. As a consequence, questions frequently arise as to how much faith one can put in CGE results. In this paper, we employ a novel approach to the validation of a widely utilized global CGE model — GTAP-E. By comparing the variance of model-generated petroleum price distributions – driven by historical demand and supply shocks to the model – with observed five-year moving average price distributions, we conclude that energy demand in GTAP-E is far too price-elastic over this medium run time frame. After incorporating the latest econometric estimates of energy demand and supply elasticities, we revisit the validation question and find the model to perform more satisfactorily. As a further check, we compare a deterministic global general equilibrium simulation, based on historical realizations over the five year period: 2001–2006, during which petroleum prices rose sharply, along with growing global energy demands. As anticipated by the stochastic simulations, the revised model parameters perform much better than the original GTAP-E parameters in this global, general equilibrium context.     

Time and frequency connectedness among oil shocks,electricity and clean energy markets

This paper examines the time and frequency connectedness among electricity, carbon and clean energy markets, and oil price demand and supply shocks. In doing so, we use the spillover method proposed by Diebold and Yilmaz (2012) and its extension in the frequency domain by Baruník and Křehlík (2018). We find increased connectedness during the global financial crisis as well as in the shale oil revolution period. The total connectedness is also higher in the short-run compared to the long-run. Due to their low connectedness, electricity futures can act as a risk diversifier and safe-haven asset against oil shocks. Net pairwise directional connectedness among oil shocks and the clean energy index is higher during the shale oil revolution. These results have important implications for investors with different investment time horizons.     

The impact of oil price shocks in the Canadian economy: A structural investigation on an oil-exporting economy

Oil price shocks and monetary policy response by oil producing economies have been the subject of important theoretical investigation in the modern literature. This topic seems to be well grounded since fluctuations in the US dollar, which is affected by US monetary policy, plays an important role in exacerbating run ups and precipitous falls in world oil prices. We investigate the economic consequences of oil price shocks using an open-economy DSGE model that incorporates demand for and supply of oil while allowing for interaction between domestic and foreign monetary policy. Using Canadian and U.S. data, we quantify the relative importance of oil price shocks and monetary policy response on macroeconomic variables. We show that domestic monetary policy is a key channel that accounts for over 40% of discounted variation in domestic output across a 4-year horizon after an oil shock. In contrast, US monetary policy is of lesser importance in propagating oil price shocks on an oil-exporting economy through the international channel.     

The impacts of structural oil shocks on macroeconomic uncertainty: Evidence from a large panel of 45 countries

Using local projection methods, this paper employs monthly panel data from 1989 to 2017 to examine both linear and nonlinear impulse responses of macroeconomic uncertainty to structural shocks to global oil production, aggregate demand, oil-market-specific demand and speculative demand in a large group of 45 economies. We find that both oil supply and demand shocks are important drivers of uncertainty. There is strong evidence that the impacts of oil price shocks on macroeconomic uncertainty are regime-dependent and contingent on the states of investor sentiments and perceived volatility in financial markets. The responses of economic uncertainty to oil shocks, especially demand-side shocks, appear to experience a dramatic change in the post-Global Financial Crisis period.     

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.     

Correlation between Chinese and international energy prices based on a HP filter and time difference analysis

To establish a reasonable system and mechanism for Chinese energy prices, we use the Granger causality test, Hodrick–Prescott (HP) filter and time difference analysis to research the pricing relationship between Chinese and international energy prices. We find that Chinese and international crude oil prices changed synchronously while Chinese refined oil prices follow the changes of international oil prices with the time difference being about 1 month to 2 months. Further, Australian coal prices Granger causes Chinese coal prices, and there is a high correlation between them. The U.S. electricity price is influenced by the WTI crude oil price, the U.S. gasoline price and the HenryHub gas price. Due to the unreasonable price-setting mechanism and regulation from the central government, China′s terminal market prices for both electricity and natural gas do not reflect the real supply–demand situation. This paper provides quantitative results on the correlation between Chinese and international energy prices to better predict the impact of international energy price fluctuations on China′s domestic energy supply and guide the design of more efficient energy pricing policies. Moreover, it provides references for developing countries to improve their energy market systems and trading, and to coordinate domestic and international energy markets.     

Natural gas consumption and economic growth: Are we ready to natural gas price liberalization in Iran?

This paper examines the relationship between natural gas consumption and economic growth in Iran within a multivariate production model. We also investigate the effects of natural gas price on its consumption and economic growth using a demand side model. The paper employs bounds test approach to level relationship over the period of 1972–007. We find evidence of bidirectional positive relationship between natural gas consumption and economic growth in short-run and long-run, based on the production model. The findings also suggest that real GDP growth and natural gas have positive and negative impacts on gross fixed capital formation, respectively. Employment, however, was found to have negative but insignificant impact on gross fixed capital formation. Moreover, the estimation results of demand side model suggest that natural gas price has negative and significant impact on natural gas consumption only in the long-run, though there is insignificant impact on economic growth. These results imply that the Iranian government's decision for natural gas price liberalization has the adverse effects on economic growth and policy makers should be cautious in doing this policy.