Comprehensive Method for Medium-Term Analysis and Forecast of Agricultural Commodity Prices (CMAF)

Zelingher, R. (2022). Comprehensive Method for Medium-Term Analysis and Forecast of Agricultural Commodity Prices (CMAF). In: IIASA-Israel Symposium on Sustainability Pathways empowered by Systems Analysis, 28-29 November, 2022, Tel Aviv, Israel.

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Food insecurity poses a pressing challenge globally, especially in low-income countries, where access to market information is crucial for mitigating food price spikes and ensuring year-round food security. Nevertheless, these countries often lack the resources and information to address these challenges effectively.

Here we present the development and application of the Comprehensive Methodology: Accessible Analyse and Forecast (CMAAF) of agricultural commodity prices. Using explainable machine learning (XML) and econometric techniques, CMAAF analyzes and forecasts monthly changes in prices of globally traded AC. The main goal of CMAAF is to facilitate access to accurate and interpretable medium-term forecasts of AC prices, overcoming barriers of budget, language or any other constraints. This paper applies CMAAF to four AC vital for global food security: maize, soybean, wheat, and cocoa. Our approach offers a complete understanding of how prices are forecasted. Our innovative approach offers a comprehensive insight into agricultural commodity prices, uncovering the factors driving their fluctuations. From global patterns to local nuances, we provide a detailed understanding of price dynamics across different months.

By accurately predicting and explaining price shifts during critical events, we empower decision-makers in building a fair and sustainable food system for all.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Research Programs: Advancing Systems Analysis (ASA)
Advancing Systems Analysis (ASA) > Exploratory Modeling of Human-natural Systems (EM)
Depositing User: Michaela Rossini
Date Deposited: 09 Jul 2024 08:24
Last Modified: 09 Jul 2024 08:26

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