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Revisiting the Inflationary Effects of Oil Prices

Shiu-Sheng Chen

Year: 2009
Volume: Volume 30
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol30-No4-5
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Abstract:
This paper uses a structural vector autoregression model to investigate the inflationary effects of oil prices. Rather than simply infer the oil price changes as oil supply shocks, we identify three different shocks in the crude oil market: the oil supply shock, the global aggregate demand shock, and the oil-market specific demand shock. We then use impulse response functions to compute the conditional oil price pass-through ratios. It is found that the largest oil price pass-through is caused by oil supply shocks. However, evidence from historical decompositions suggests that the oil price movements have been driven by shocks from strong global aggregate demand and oil demand while only minor contributions come from oil supply shocks. Disentangling demand and supply shocks in the crude oil market helps to uncover the fact that a recent decline in unconditional oil price pass-through may come from the low conditional pass-through caused by global demand shocks.



Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets

Xiaodong Du and Lihong Lu McPhail

Year: 2012
Volume: Volume 33
Number: Number 2
DOI: 10.5547/01956574.33.2.8
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Abstract:
Motivated by strong comovement and increasing volatility of energy and agricultural prices, we examine dynamic evolutions of ethanol, gasoline, and corn prices over the period of March 2005-March 2011. A structural change is found around March 2008 in the pairwise dynamic correlations between the prices in a multivariate GARCH model. A structural VAR (SVAR) model is then estimated on two subsamples, one before and one after the identified change point. Using the novel method of identification through heteroscedasticity, we exploit the time-varying price volatilities to fully identify the SVAR model. In the more recent period, ethanol, gasoline, and corn prices are found to be more closely linked with a strengthened corn-ethanol relation, which can be largely explained by the new developments of the biofuel industry and related policy instruments. Variance decomposition shows that for each market a significant and relatively large share of the price variation could be explained by the price changes in the other two markets. The results are robust to the inclusion of seasonal dummies and various representative macroeconomic and financial indicators. Keywords: Biofuel, Identification through heteroscedasticity, Structural change, Structural VAR



Oil Price Shocks and the Stock Market: Evidence from Japan

Abhay Abhyankar, Bing Xu, and Jiayue Wang

Year: 2013
Volume: Volume 34
Number: Number 2
DOI: 10.5547/01956574.34.2.7
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Abstract:
We study, using a structural vector autoregressive (SVAR) model, the relationship between oil price shocks and the Japanese stock market. We find that oil price shocks that arise from changes in aggregate global demand are positively correlated to returns on the Japanese stock market. Thus, in contrast to the conventional wisdom, a rise in oil price is not always bad news for the Japanese stock market. On the other hand, the Japanese stock market reacts negatively to oil price increases related to oil-market specific demand shocks. Finally, different from prior research using U.S. stock market data, we find that supply and demand shocks in the global crude oil market affect returns to the Japanese stock market index through changes to expected real cash flows rather than to changes to expected returns.



The Impact of U.S. Supply Shocks on the Global Oil Price

Thomas S. Gundersen

Year: 2020
Volume: Volume 41
Number: Number 1
DOI: 10.5547/01956574.41.1.tgun
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Abstract:
I examine the role of the U.S. shale oil boom in driving global oil prices. Using a structural vector autoregressive (SVAR) model that identifies separate oil supply shocks for the U.S. and OPEC, I find that U.S. supply shocks can account for up to 13% of the oil price variation over the 2003-2015 period. This is considerably more than what has been found in other studies. Moreover, while U.S. oil production has increased substantially since 2010, U.S. oil supply shocks first started to contribute negatively to oil prices beginning in late 2013. This mismatch implies a temporary friction in the transmission of U.S. supply shocks to the rest of the world likely caused by logistical and technological challenges observed in the downstream supply chain.





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