A roller coaster ride: an empirical investigation of the main drivers of the international wheat price

Abstract

Over the last decade, commodity prices have registered substantial booms and busts marked by extreme volatility. Wheat in particular, one of the main nonoil commodities, has registered a roller coaster in price levels which seems to be inconsistent with supply and demand fundamentals. To acutely investigate the drivers of wheat prices and quantify their impact, a vector error correction model (VECM) has been used. The exogenous variables have been distinguished into four groups: market-specific factors, broad macroeconomic determinants, speculative components, and weather variables. The quadriangulation of the determinants will enable us to better understand the movements in wheat price and identify the specific role of each component. The results show that a mix of factors are contributing to wheat price movements, including speculation, global demand, and real effective exchange rate.JEL classifications: C22, E31, Q11

Monetary policy shocks and the dynamics of agricultural commodity prices: evidence from structural and factor‐augmented VAR analyses

“…The estimated impulse response functions from FAVAR models are consistent, in terms of shape and magnitude, with those from similar studies that apply FAVAR in commodity price literature though our focus is different from theirs (Byrne et al., ; Lombardi et al., ). In the extended literature on commodity prices, our findings of the role of monetary policy are also consistent with the findings of Frankel () and Algieri () who emphasize the role of monetary policy in the long‐run development of commodity price.…”

“…() test the effects of monetary policy shocks on a broad index of commodity prices, and three indexes of metal, food and oil, and show that expansionary U.S. monetary policy shocks drive up the broad commodity price index and all of its components statistically significantly. To investigate the drivers of wheat prices, and quantify their impact, Algieri () estimates a VECM and demonstrates the long‐run cointegrated relationship between wheat price and four groups of variables, namely: market‐specific factors, broad macroeconomic determinants, speculative components, and weather. Scrimgeour () applying an event study method on 17 commodities (8 agricultural and 9 metals) shows that a surprise increase in interest rate reduces commodity prices immediately.…”

“…As the level of inventory plays an important role in the determination of commodity price (Frankel, ; Kilian and Murphy, ; Krugman ), controlling for the inventory level in the analysis helps us to understand the role of macroeconomic shocks accurately. Studies that consider inventory in the analyses, test and report either single‐equation regression results (Frankel, ), or long‐run cointegrating relationship (Algieri, ). Our analysis of short‐run dynamics is more relevant for (short‐run) policy formulation, and the use of structural VAR methodology for the estimation is more appropriate for the evaluation of policy effectiveness (Sims, , ).…”

Effects of drought on hay and feed grain prices

“…Other studies showed that grain prices positively react to anomalies in the El Niño-Southern Oscillation, which are linked to extreme weather events such as droughts (e.g. Algieri 2014, Ubilava 2017.…”

How financial investment distorts food prices: evidence from U.S. grain markets

“…Empirical evidence for a causal link between financial investment and commodity price dynamics has been mixed; see Irwin () and Cheng and Xiong (), for comprehensive literature reviews. Most empirical studies have focused on the impact of commodity indices on price levels and volatilities, such as Ott (), Sanders and Irwin (), and Algieri (, ). Few have looked at convergence, market basis, or term structure effects.…”