By Stefano Schiavo^[1]

The globalization of agriculture has intensified significantly over the past four decades, marked by a six-fold increase in trade in agricultural goods. As a result, approximately 25% of global agricultural production is currently exported (D’Odorico et al. 2014) and food imports feed between 2 and 3 billion people (MacDonald et al. 2015).

While trade offers benefits such as risk diversification and the ability to decouple population growth from local resource availability, it simultaneously increases countries' exposure to shocks originating elsewhere and fosters dependence on other nations.

These competing effects can be investigated using network-based simulations that study diffusion of global or local shocks affecting agricultural production (Grassia et al. 2022). Since three main staples --corn, rice and wheat-- account for more than 50% of global caloric intake, these commodities represent a natural starting point for the analysis.

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By Daniele Curzi^[1], Dela-Dem Doe Fiankor^[2], Roberto Solazzo^[3], and Daniele Valenti^[4]

Global agricultural markets have experienced recurrent spikes in wheat prices over the past two decades, driven by extreme weather events, rising input costs, tightening stocks, and, more recently, the COVID-19 pandemic and the Russia–Ukraine conflict. These developments have renewed interest in how firms that rely on wheat as a key intermediate input adjust their pricing strategies in response to large and persistent commodity price fluctuations. This paper examines how Italian firms exporting pasta and wheat-based derivatives adjust export prices when confronted with shocks to the global wheat market.

We combine a time-series analysis of global wheat price dynamics with firm-level trade data. Using the universe of Italian firm-product-destination export records over 2004–2022, we study how export prices respond to structural shocks identified in the international wheat market. To do so, we first estimate a Bayesian Structural Vector Autoregressive (BSVAR) model for the global wheat market, following Valenti et al. (2025), using quarterly data from 1970–2022. The model identifies five fundamental drivers of wheat price movements: supply shocks, global economic activity shocks, energy demand shocks, precautionary (inventory) demand shocks, and wheat-specific demand shocks. These structural shocks are then aggregated to the annual frequency and linked to firms’ export pricing decisions.

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By Julia Fischer^[1]

Armed conflict remains a daily reality in many parts of the world. While the trend of conflict outbreaks is increasing (Pettersson et al., 2021), there is reason to expect that peace eventually materializes after war. Within the past 25 years, approximately half of African countries experienced war, followed by periods of peace, the so-called post-conflict periods. However, due to the acute instability, a country’s economy contracts during war because of factors such as capital flight, disinvestment in human capital and physical property destruction. This not only shapes a country’s post-conflict development as a whole, but these consequences of war are likely very local. While some locations within a country experience an influx of displaced people and their savings are spent on necessities there, other locations experience higher destruction of physical property and infrastructure, increased capital flight and a large outflow of human capital.

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