Nowcasting regional consumer food inflation
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Consumer price indices (CPI) are disseminated by countries with a lag that typically varies from 1 to 4 months. Global CPI datasets, such as those maintained by the International Labour Organization (ILO), the United Nations’ Statistics Division (UNSD) or the International Monetary Fund (IMF), have a longer average lag because of the time needed to collect, compile and publish the data provided by countries. In order to monitor current trends in food inflation, forecasting (or nowcasting) price changes to the current period is therefore necessary. This paper presents the methodological framework used by FAO’s Statistics Division to now-cast consumer food inflation at regional level. Hybrid ARIMA-GARCH models are estimated for each region, with additional explanatory variables constructed from a large and high-frequency dataset. The out-of-sample analysis indicates a satisfactory performance of the models at predicting the overall variability in prices as well as the sign and direction of price changes.