WP 8: Short term forecasts and early warning

General Information

Work package 8 will develop econometric tools for short-term forecasts and early warning systems for the most relevant agricultural commodities, with an explicit assessment of model uncertainty.

Further, it will develop tools for policy design aiming at the short-term stabilization of agricultural commodity markets.

 

Latest Publication

Deliverable 8.4: Early warning systems for commodity markets

An agricultural commodity price and price volatility forecasting modelling system has been developed and applied for four agricultural commodities to perform forecasts on a horizon spanning from three months to one year. The forecasting system can be used as an early warning system based on seasonal and decadal simulated weather and climate forecasts in combination with financial and macro-economic projections.

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Deliverable 8.1: Fundamentals, Speculation or Macroeconomic Conditions? On the Determinants of Commodity Price Dynamics, with an Application to Arabica Coffee

We analyse the role played by market fundamentals, speculation and macroeconomic conditions as empirical determinants of commodity price changes. We combine model averaging techniques to explain historical patterns with an in-depth analysis of out-of-sample predictability of commodity prices using fundamentals as well as macroeconomic and financial variables. Our results indicate that variables related to global macroeconomic and financial developments contain valuable information to explain the historical pattern of coffee price developments, as well as to improve out-of-sample predictions of coffee prices

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Deliverable 8.3: Forecasting Commodity Prices Under Specification Uncertainty: A Comprehensive Approach

We present a comprehensive modelling framework aimed at obtaining short-term forecasts (one to twelve months ahead) of commodity prices and apply it to short and medium run predictions of Arabica coffee, wheat, soybeans and corn. We entertain a large number of univariate and multivariate time series models, including specifications that exploit information about market fundamentals, macroeconomic and financial developments and climatic variables. A comprehensive set of forecast averaging tools is implemented to explicitly address model uncertainty. Our results indicate that variables measuring market fundamentals and macroeconomic developments (and to a lesser extent, financial developments) contain systematic predictive information for out-of-sample forecasting of commodity prices.

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Deliverable 8.2: Preliminary report on Task 8.2: prices forecasting model

We present a comprehensive modelling framework aimed at obtaining shortterm forecasts of commodity prices.

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