Heteroscedastic price forecasting for food security management in developing countries

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Abstract
Price forecasting systems are of considerable importance to food security management by governments’ and non‐governmental organizations. Sparse data availability in low‐income economies, however, generally necessitates reliance on reduced form forecasting methods. Relatively recent innovations in heteroscedasticity‐consistent time series techniques offer price forecasting tools that are feasible given available data and analysis technologies in low‐income economies. Moreover, extended GARCH models exhibit superior out‐of‐sample forecast accuracy using monthly food price data from Madagascar. These techniques also permit cost reduction in food security operations by more precise estimation of the risk of hitting a critical price level.

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