Measuring and forecasting retail trade in real time using card transactional data

Juan García López, Matías Pacce, Tomasa Rodrigo, Pep Ruiz de Aguirre and Camilo A. Ulloa

International Journal of Forecasting, 2021, vol. 37, issue 3, 1235-1246

Abstract: We build big data retail trade indicators for Spain using high-dimensional card transaction data from one of the country’s biggest banks. The resulting indicators replicate the dynamics of the Spanish retail trade indices (RTI), regional RTIs (Spain’s autonomous regions), and RTI by retailer type (distribution classes) released by the Spanish National Statistics Institute. The new indicators not only have a higher frequency (daily data) and higher geographical and sectorial breakdown but are also shown to improve nowcasting and forecasting power for the official RTI, making them key variables to monitor consumption.

Keywords: Retail sales; Big data; Electronic payments; Consumption; Structural time series model (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207021000339
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:37:y:2021:i:3:p:1235-1246

DOI: 10.1016/j.ijforecast.2021.02.005

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().