Based on a two-country, multi-period general equilibrium model of the spot and futures markets for crude oil, we show that there is no theoretical support for the common view that oil futures prices are accurate predictors of the spot price in the mean-squared prediction error (MSPE) sense; yet under certain conditions there is support for the view that oil futures prices are unbiased predictors. Our empirical analysis documents that futures-based forecasts typically are less accurate than the no-change forecast and biased, although the bias is small. Much of the MSPE is driven by the variability of the futures price about the expected spot price, as captured by the basis. Empirically, the fluctuations in the oil futures basis are larger and more persistent than fluctuations in the basis of foreign exchange futures. Within the context of our theoretical model, this anomaly can be explained by the marginal convenience yield of oil inventories. We show that increased uncertainty about future oil supply shortfalls under plausible assumptions causes the basis to decline and precautionary demand for crude oil to increase, resulting in an immediate increase in the real spot price that is not necessarily associated with an accumulation of oil inventories. Our main result is that the negative of the basis may be viewed as an index of fluctuations in the price of crude oil driven by precautionary demand for oil. An empirical analysis of this index provides independent evidence of how shifts in market expectations about future oil supply shortfalls affect the spot price of crude oil. Such expectation shifts have been difficult to quantify, yet have been shown to play an important role in explaining oil price fluctuations. Our empirical results are consistent with related evidence in the literature obtained by alternative methodologies.
We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need to know about the choice of sample period and about the tradeoffs between alternative oil price series and model specifications? Are real or nominal oil prices predictable based on macroeconomic aggregates? Does this predictability translate into gains in out-of-sample forecast accuracy compared with conventional no-change forecasts? How useful are oil futures markets in forecasting the price of oil? How useful are survey forecasts? How does one evaluate the sensitivity of a baseline oil price forecast to alternative assumptions about future demand and supply conditions? How does one quantify risks associated with oil price forecasts? Can joint forecasts of the price of oil and of U.S. real GDP growth be improved upon by allowing for asymmetries? Acknowledgements: We thank Christiane Baumeister for providing access to the world and OECD industrial production data and Ryan Kellogg for providing the Michigan survey data on gasoline price expectations. We thank Domenico Giannone for providing the code generating the Bayesian VAR forecasts. We have benefited from discussions with
Guided by a macroeconomic model in which non-energy commodity prices are endogenously determined, we apply a new factor-based identification strategy to decompose the historical sources of changes in commodity prices and global economic activity. The model yields a factor structure for commodity prices and identification conditions that provide the factors with an economic interpretation: one factor captures the combined contribution of shocks that affect commodity markets only through general-equilibrium forces. Applied to a cross-section of commodity prices since 1968, the theoretical restrictions are consistent with the data and yield structural interpretations of the common factors in commodity prices. Commodity-related shocks have contributed modestly to global economic fluctuations. RésuméÀ partir d'un modèle macroéconomique dans lequel les prix des produits de base non énergétiques sont déterminés de façon endogène, les auteurs appliquent une nouvelle stratégie d'identification factorielle pour décomposer les éléments à l'origine des variations des prix des produits de base et de l'activité économique mondiale observées par le passé. Le modèle génère une structure factorielle des prix des produits de base, ainsi que des conditions d'identification permettant de donner aux facteurs examinés une interprétation économique : un facteur unique rend compte de l'incidence combinée de chocs dont l'influence sur les marchés des produits de base s'exerce uniquement par l'entremise des effets d'équilibre général. Appliquées à un échantillon représentatif des prix des produits de base depuis 1968, les contraintes théoriques sont conformes aux données et cadrent avec une interprétation structurelle des facteurs communs influant sur les prix de ces produits. Les auteurs constatent que les chocs liés aux produits de base ont pesé modestement sur les fluctuations de l'économie mondiale. Classification JEL : E3, F4 Classification de la Banque : Modèles économiques ; Questions internationalescommodity storage, while section 5 uses the indirect common factor in a recursive out-of-sample forecasting exercise. Section 6 concludes. 2The Sources of Commodity Price Co-movement: Theory In this section, we present a model that characterizes the sources of commodity price co-movement. In particular, we show that the model yields a tractable factor structure for a cross-section of commodity prices, which permits an economic interpretation of the factors. 2.1Model of commodity prices The baseline model consists of households, a continuum of heterogeneous primary commodities, a sector that aggregates these commodities into a single intermediate commodity input, and a final goods sector that combines commodities, labor and technology into a final good. The HouseholdA representative consumer maximizes expected discounted utility over consumption ( ), labor supply ( ) and the amount of another input supplied to each commodity sector ( ( )) as follows:
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