Forecasting spot and futures price volatility of agricultural commodities : the role of climate-related migration uncertainty

Abstract

There is a lack of research explicitly connecting climate-related migration uncertainties to the volatility of agricultural commodities. Existing studies emphasize supply shocks while neglecting the effects of migration and uncertainties linked to climate-related migration. In this paper, we evaluate the forecasting ability of the newly developed climate-related migration uncertainty index (CMUI) and its two components, the climate uncertainty index (CUI) and the migration uncertainty index (MUI), for the return volatility of agricultural commodity prices in both the futures and spot markets. Employing a GARCH-MIDAS model, based on mixed data frequencies covering the period from 1977Q4 (with the earliest daily observation on October 3, 1977) to 2024Q1 (with the latest daily observation on March 29, 2024), we conduct both statistical and economic evaluations, including the Modified Diebold-Mariano test, Model Confidence Set procedure, and risk-adjusted performance metrics. The results demonstrate that integrating CUI, MUI, and CMUI into the predictive model of the return volatility of agricultural commodities significantly improves forecast accuracy relative to the conventional GARCH-MIDAS-RV benchmark. These findings suggest that climate and migration related uncertainty indices are both statistically significant and economically relevant, offering enhanced forecasting power and investment performance.

HIGHLIGHTS • Forecast the volatility of agricultural commodities using Climate-Related Migration Uncertainty. • Apply a GARCH-MIDAS model and conduct both statistical and economic evaluations. • Uncertainty improves the forecasting power relative to GARCH-MIDAS-RV benchmark. • It leads to improvement in the investment performance.