Research
Publications
Estimating the Competitive Storage Model with Trending Commodity Prices (with C. Gouel)
(Journal of Applied Econometrics, 32(4), 744-763)
This article presents a method to estimate jointly the parameters of a standard commodity storage model and the parameters characterizing the trend in commodity prices. This procedure allows the influence of a possible trend to be removed without restricting the model specification, and allows model and trend selection based on statistical criteria. The trend is modeled deterministically using linear or cubic spline functions of time. The results show that storage models with trend are always preferred to models without trend. They yield more plausible estimates of the structural parameters, with storage costs and demand elasticities that are more consistent with the literature. They imply occasional stockouts, whereas without trend the estimated models predict no stockouts over the sample period for most commodities. Moreover, accounting for a trend in the estimation implies price moments closer to those observed in commodity prices. Our results support the empirical relevance of the speculative storage model, and show that storage model estimations should not neglect the possibility of long-run price trends.
The Empirical Merit of Structural Explanations of Commodity Price Volatility: Review And Perspectives
(Journal of Economic Surveys, 33(2) 639-664)
This paper presents both the history of and state‐of‐the‐art in empirical modeling approaches to the world commodity price volatility. The analysis builds on the storage model and key milestones in its development. Specifically, it is intended to offer a reader unfamiliar with the relevant literature an insight into the modeling issues at stake from both a historical and speculative viewpoint. The review considers primarily the empirical techniques designed to assess the merits of the storage theory; it does not address purely statistical approaches that do not rely on storage theory and that have been studied in depth in other streams of the commodity price literature. The paper concludes with some suggestions for future research to try to resolve some of the existing empirical flaws, and hopefully to increase the explanatory power of the storage model.
"The empirical relevance of the competitive storage model” by Cafiero et al. (2011): Replication, Robustness and Extension
(Applied Economic and Perspectives Policy 45(3):1493-1514)
Most of the empirical work and policy analysis in commodity markets rely on the storage model with rational expectations. However, its empirical validity remains challenged. Cafiero et al. (2011) inject new life into the commodity price literature by addressing the major empirical concern which is the model’s inability to explain the observed patterns of autocorrelation in prices. This paper aims to reproduce the main estimation results of the structural parameters of the storage model obtained by Cafiero et al. (2011), and then to extend the analysis with a series of robustness checks of the original findings. The successful replication exercise supports the validity of the published results. Regarding the robustness analysis, I find that the results are particularly sensitive to the efficiency of the estimator used and the spurious averaging effect resulting from the construction of annual data series. Future structural estimations of the storage model should account for both factors for more reliable estimates to be obtained.
War in Ukraine: The Rational “Wait-and-See” Mode of Global Food Markets
(Applied Economic and Perspectives Policy 45(2):626-644)
Russia's invasion of Ukraine is a major shock at the heart of the breadbasket of Europe at a time when global stocks are running short. With inelastic supply and demand for such basic goods and lack of inventories to cushion the shock, the basic economics of storage arbitrage explains the commodity price spikes needed to ration the war-related supply shortage. In this paper, I show that sound policymaking in this context could rely on the rational expectations storage model to make sense of the chaotic price fluctuations. Empirical analysis of the unfolding commodity shock using a storage model lens suggests that, 3 months after the Russian invasion, the global food market switched into a “wait-and-see” mode, with price movements reflecting a loss in the size of the global share of caloric production from Ukraine.
Working papers
The Role of Storage in Commodity Markets: Indirect Inference Based on Grains Data (with C. Gouel)
We develop an indirect inference approach relying on a linear supply and demand model serving as auxiliary model to provide the first full empirical test of the rational expectations commodity storage model. We build a rich storage model which incorporates a supply response and four structural shocks, and show that exploiting information on both prices and quantities is key to relax previous restrictive identifying assumptions and assess the empirical consistency of the model's features. Finally, we carry out a structural estimation on the aggregate index of the world most important staple food products. Our estimations show that supply shocks are the main drivers of food market dynamics and that our storage model is consistent with most of the moments in the data, including the high price persistence so far subject of a long-standing puzzle.
Work in progress
Estimation of a Model of Price Discrimination in the Steel Market from Endogenously Sampled Data (with John Rust and George Hall)
The Delaying Effect of Storage on Investment: Evidence from the Crude Oil Sector (with Assia Elgouacem)
Our paper provides a theoretical framework able to represent with accuracy a consistent relationship between fixed capital investment, storage and the term structure of prices in a storable commodity market. It aims at understanding the interaction of storage capacity with irreversible investment decisions in mediating investment and commodity price dynamics. The results show that the presence of storage, while smoothing the spot price tends also to channel volatility into the future, thereby raising the options value of waiting and eventually delaying and making lumpier the investment in fixed capital. The time-varying expected price volatility related to the inventory levels is a new channel we identify to show why irreversible investment decisions in a storable commodity market capture more accurately both price and investment dynamics observed in the data as compared to an irreversible investment setting without storage capacity.
PhD Thesis
Revisiting the competitive storage model as a tool for the empirical analysis of commodity price volatility