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dc.contributor.authorAastveit, Knut Are
dc.contributor.authorFastbø, Tuva Marie
dc.contributor.authorGranziera, Eleonora
dc.contributor.authorPaulsen, Kenneth Sæterhagen
dc.contributor.authorTorstensen, Kjersti Næss
dc.description.abstractWe 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 benefits of using the card payments data by obtaining a timely and relatively accurate now cast of the first quarter of 2020, a quarter characterized by heightened uncertainty due to the COVID-19 pandemic.en_US
dc.publisherNorges Banken_US
dc.relation.ispartofseriesWorking Paper;17/2020
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.subjectdebit card transaction dataen_US
dc.subjectforecast evaluationen_US
dc.subjectJEL: C22en_US
dc.subjectJEL: C52en_US
dc.subjectJEL: C53en_US
dc.subjectJEL: E27en_US
dc.titleNowcasting Norwegian household consumption with debit card transaction dataen_US
dc.typeWorking paperen_US
dc.subject.nsiVDP::Samfunnsvitenskap: 200::Økonomi: 210::Samfunnsøkonomi: 212en_US

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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal