Nowcasting Norwegian household consumption with debit card transaction data

Knut Are Aastveit, Tuva Marie Fastbø, Eleonora Granziera, Kenneth Sæterhagen Paulsen and Kjersti Næss Torstensen

No 2020/17, Working Paper from Norges Bank

Abstract: We use a novel data set covering all domestic debit card transactions in physical terminals by Norwegian households, to nowcast quarterly Norwegian household consumption. These card payments data are free of sampling errors and are available weekly without delays, providing a valuable early indicator of household spending. To account for mixed-frequency data, we estimate various mixed-data sampling (MIDAS) regressions using predictors sampled at monthly and weekly frequency. We evaluate both point and density forecasting performance over the sample 2011Q4-2020Q1. Our results show that MIDAS regressions with debit card transactions data improve both point and density forecast accuracy over competitive standard benchmark models that use alternative high-frequency predictors. Finally, we illustrate the beneï¬ ts of using the card payments data by obtaining a timely and relatively accurate now cast of the ï¬ rst quarter of 2020, a quarter characterized by heightened uncertainty due to the COVID-19 pandemic.

Keywords: debit card transaction data; nowcasting; forecast evaluation; COVID-19 (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 E27 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2020-11-08
New Economics Papers: this item is included in nep-big, nep-for, nep-isf, nep-mac, nep-ore and nep-pay
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:bno:worpap:2020_17

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