Using Payment System Data to Forecast Economic Activity

Abstract

Payment systems trace economic transactions; they could therefore be considered important indicators of economic activity. This paper describes the monthly data available on Italy's retail settlement system and selects some of them for nowcasting and short-term forecasting. Using a mixed-frequency factor model based on a large-scale data set to predict Italian GDP and its main components, the contribution of payment system flows to improving forecasting accuracy is found to be non-negligible. Moreover, the timeliness of the data improves nowcasting accuracy throughout the quarter.

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