This thesis investigates the structural drivers of price dynamics in global agricultural commodity markets by estimating separate Structural Vector Autoregressive (SVAR) models for four major staples: corn, wheat, rice, and soybean. Each model includes a set of endogenous variables including production, consumption, inventory, real prices, and a common index of real economic activity to disentangle the effects of supply and demand shocks over the period 1960–2024. Our research addresses key gaps in the literature, including the scarce development of commodity-specific SVAR frameworks for major staple markets and the relatively unexplored effects of unexpected changes in consumption and inventory demand on agricultural commodity prices. Using impulse response functions (IRF), forecast error variance decomposition (FEVD), and historical decomposition, the thesis uncovers both common and crop-specific patterns in price behavior. Our findings highlight the central role of precautionary demand shocks—namely, increases in stockholding driven by precautionary reasons—particularly in the wheat and rice markets. Moreover, the price responses to production shocks (e.g., harvest shortfalls), consumption shocks (e.g., unexpected shifts in food, feed and industrial use,) and aggregate demand shocks (e.g., increases in current demand consistent with strong economic growth or income effects) are heterogeneous across commodities. In the soybean market, shocks have relatively homogeneous effects on prices, reflecting its dual role in food and industrial uses, whereas corn shows consistently strong reactions to consumption-driven demand. Overall, the results underscore the uneven transmission of global shocks across staple markets and offer relevant implications for the design of targeted food-security policies, inventory management strategies, and market-stabilization tools. Keywords: Structural VAR models, recursive identification, global agricultural commodity markets, rice, wheat, soybean, corn, supply shocks, precautionary demand shocks.
Questa tesi analizza il ruolo dei fondamentali strutturali – in termini di domanda e offerta – sottostanti alle dinamiche dei prezzi nei mercati agricoli globali attraverso la stima di modelli VAR strutturali (SVAR) distinti per quattro principali colture di base: mais, frumento, riso e soia. Ogni modello include un set di variabili endogene — produzione, consumo, scorte, prezzi reali e un indice comune di attività economica reale — con l’obiettivo di identificare gli effetti dei diversi shock di offerta e domanda nel periodo 1960–2024. La nostra ricerca affronta alcune carenze presenti nella letteratura, tra cui il limitato sviluppo di modelli SVAR specifici per singole commodity nei principali mercati agricoli e il ruolo, ancora poco indagato, delle variazioni inattese nella domanda di consumo e di accumulo delle scorte sui prezzi delle materie prime agricole all’interno dei modelli SVAR. Attraverso l’analisi delle funzioni di risposta agli impulsi (IRF), della scomposizione della varianza degli errori di previsione (FEVD) e della scomposizione storica, la tesi individua sia comportamenti comuni sia specifici per ciascuna coltura. I risultati evidenziano il ruolo centrale degli shock di domanda precauzionale, ossia gli aumenti nelle scorte dettati da motivazioni precauzionali, in particolare nei mercati del frumento e del riso. Inoltre, le risposte dei prezzi agli shock di produzione (ad es., cali del raccolto), di consumo (ad es., variazioni inattese nell’uso alimentare, zootecnico o industriale) e di domanda aggregata (ad es., aumenti della domanda associati a forte crescita economica o effetti di reddito) risultano eterogenee tra le diverse commodity. Nel mercato della soia gli shock producono effetti relativamente omogenei sui prezzi, riflettendo il duplice impiego di questa coltura in ambito alimentare e industriale, mentre il mais mostra reazioni costantemente elevate agli shock di domanda legati al consumo. Nel complesso, i risultati mettono in luce la trasmissione eterogenea degli shock globali tra i diversi mercati delle colture di base e offrono indicazioni rilevanti per la definizione di politiche mirate di sicurezza alimentare, strategie di gestione delle scorte e meccanismi di stabilizzazione dei mercati.
Identifying demand and supply shocks in global corn, wheat, rice, and soybean markets: a structural VAR model
BOTSHEKAN, MILAD;HASHEMI JAMKHANEH, QAZALEH SADAT
2024/2025
Abstract
This thesis investigates the structural drivers of price dynamics in global agricultural commodity markets by estimating separate Structural Vector Autoregressive (SVAR) models for four major staples: corn, wheat, rice, and soybean. Each model includes a set of endogenous variables including production, consumption, inventory, real prices, and a common index of real economic activity to disentangle the effects of supply and demand shocks over the period 1960–2024. Our research addresses key gaps in the literature, including the scarce development of commodity-specific SVAR frameworks for major staple markets and the relatively unexplored effects of unexpected changes in consumption and inventory demand on agricultural commodity prices. Using impulse response functions (IRF), forecast error variance decomposition (FEVD), and historical decomposition, the thesis uncovers both common and crop-specific patterns in price behavior. Our findings highlight the central role of precautionary demand shocks—namely, increases in stockholding driven by precautionary reasons—particularly in the wheat and rice markets. Moreover, the price responses to production shocks (e.g., harvest shortfalls), consumption shocks (e.g., unexpected shifts in food, feed and industrial use,) and aggregate demand shocks (e.g., increases in current demand consistent with strong economic growth or income effects) are heterogeneous across commodities. In the soybean market, shocks have relatively homogeneous effects on prices, reflecting its dual role in food and industrial uses, whereas corn shows consistently strong reactions to consumption-driven demand. Overall, the results underscore the uneven transmission of global shocks across staple markets and offer relevant implications for the design of targeted food-security policies, inventory management strategies, and market-stabilization tools. Keywords: Structural VAR models, recursive identification, global agricultural commodity markets, rice, wheat, soybean, corn, supply shocks, precautionary demand shocks.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/246787