Nowcasting Brazilian GDP with Electronic Payments Data

Raquel Gonçalves

No 564, Working Papers Series from Central Bank of Brazil, Research Department

Abstract: Electronic payments data are usually available on a more timely basis than other coincident economic indicators and can be disaggregated into the level of economic divisions, by number of transactions and value, being potentially useful to anticipate the pace of economic activity. This paper seeks to measure how data from electronic payment instruments contribute to improving the nowcasting accuracy of GDP and its sectoral components. To do so, the nowcasting accuracy of complete models, with economic indicators and payments data, is compared with the accuracy of base models, without payments data, in two horizons: right after the closure of the quarter to be predicted, when payments data are already available; and about 15 days before the GDP release, when data from other coincident economic indicators are also known. The results show payments data contribute significantly to improving GDP nowcast accuracy in both horizons, but mainly just after the closure of the quarter.

Date: 2022-08
New Economics Papers: this item is included in nep-fdg and nep-pay
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