Oil Price Volatility And The Role Of Speculation

How much does speculation contribute to oil price volatility? We revisit this contentious question by estimating a sign-restricted structural vector autoregression (SVAR). First, using a simple storage model, we show that revisions to expectations regarding oil market fundamentals and the effect of mispricing in oil derivative markets can be observationally equivalent in a SVAR model of the world oil market à la Kilian and Murphy (2013), since both imply a positive co-movement of oil prices and inventories. Second, we impose additional restrictions on the set of admissible models embodying the assumption that the impact from noise trading shocks in oil derivative markets is temporary. Our additional restrictions effectively put a bound on the contribution of speculation to short-term oil price volatility (lying between 3 and 22 percent). This estimated short-run impact is smaller than that of flow demand shocks but possibly larger than that of flow supply shocks.

This book provides fresh insights into concepts, methods and new research findings on the causes of excessive food price volatility. It also discusses the implications for food security and policy responses to mitigate excessive volatility. The approaches applied by the contributors range from on-the-ground surveys, to panel econometrics and innovative high-frequency time series analysis as well as computational economics methods. It offers policy analysts and decision-makers guidance on dealing with extreme volatility.

The recent global financial crisis exposed the serious limitations of existing economic and financial models. Not only did macro models fail to predict the crisis, they seemed incapable of explaining what was happening to the economy. Policymakers felt abandoned by the conventional tools of the now obsolete Washington consensus and the World Trade Organization’s oversimplified faith in free markets.The traditional models for agricultural commodities have so far failed to take into account the uncertain character of the global agricultural economy and its ferocious consequences in food price volatility, the worst in 300 years, yielding hunger riots throughout the world. This book explores the elements which could help to close this fundamental modeling gap. To what extent should traditional models be questioned regarding agricultural commodities? Are prices on these markets foreseeable? Can their evolution be either predicted or convincingly simulated, and if so, by which methods and models? Presenting contributions from acknowledged experts from several countries and backgrounds – professors at major international universities or researchers within specialized international organizations – the book concentrates on four issues: the role of expectations and capacity of prediction; policy issues related to development strategies and food security; the role of hoarding and speculation and finally, global modeling methods. The book offers a renewed wisdom on some of the core issues in the world economy today and puts forward important innovations in analyzing these core issues, among which the modular modeling design, the Momagri model being a seminal example of it. Reading this book should inspire fruitful revisions in policy-making to improve the welfare of populations worldwide.

The theories of investment under uncertainty and real options predict that uncertainty about, for example, oil prices will tend to depress current investment. We reinvestigate the relationship between the price of oil and investment, focusing on the role of uncertainty about oil prices. We find that volatility in oil prices has had a negative and statistically significant effect on several measures of investment, durables consumption and aggregate output. We also find that accounting for the effects of oil price volatility tends to exacerbate the negative dynamic response of economic activity to a negative oil price shock, while dampening the response to a positive oil price shock.

Building on recent work on the role of speculation and inventories in oil markets, we embed a competitive oil storage model within a DSGE model of the U.S. economy. This enables us to formally analyze the impact of a (speculative) storage demand shock and to assess how the effects of various demand and supply shocks change in the presence of oil storage facility. We find that business-cycle driven oil demand shocks are the most important drivers of U.S. oil price fluctuations during 1982-2007. Disregarding the storage facility in the model causes a considerable upward bias in the estimated role of oil supply shocks in driving oil price fluctuations. Our results also confirm that a change in the composition of shocks helps explain the resilience of the macroeconomic environment to the oil price surge after 2003. Finally, speculative storage is shown to have a mitigating or amplifying role depending on the nature of the shock.

"The conference was organized by the three editors of this book and took place on August 15-16, 2012 in Seattle."--Preface.