Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/246114 
Year of Publication: 
2020
Series/Report no.: 
Working Paper No. 17/2020
Publisher: 
Norges Bank, Oslo
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 benefits of using the card payments data by obtaining a timely and relatively accurate nowcast of the first quarter of 2020, a quarter characterized by heightened uncertainty due to the COVID-19 pandemic.
Subjects: 
Debit Card Transaction Data
Nowcasting
Forecast Evaluation
COVID-19
JEL: 
C22
C52
C53
E27
Persistent Identifier of the first edition: 
ISBN: 
978-82-8379-174-7
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Working Paper
Appears in Collections:

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.