Economics at your fingertips  

A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data

Cláudia Duarte ()
Authors registered in the RePEc Author Service: António Rua and Paulo M. M. Rodrigues ()

Working Papers from Banco de Portugal, Economics and Research Department

Abstract: The recent worldwide development and widespread use of electronic payment systems opened the opportunity to explore new data sources for monitoring macroeconomic activity. In this paper, we analyse the usefulness of data collected from Automated Teller Machines (ATM) and Points-Of-Sale (POS) for nowcasting and forecasting quarterly private consumption. To take advantage of the high frequency availability of such data, we use Mixed Data Sampling (MIDAS) regressions. A comparison of several MIDAS variants proposed in the literature is conducted, both single- and multiple variable models are considered, as well as different information sets within the quarter. Given the high penetration of ATM/POS technology in Portugal, it becomes a natural case study to assess its information content for tracking private consumption behaviour. We find that ATM/POS data displays better forecast performance than typical indicators, reinforcing the potential usefulness of this novel type of data among policymakers and practitioner.

JEL-codes: C53 E27 (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-for, nep-mac and nep-pay
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)

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:

Access Statistics for this paper

More papers in Working Papers from Banco de Portugal, Economics and Research Department Contact information at EDIRC.
Bibliographic data for series maintained by DEE-NTD ().

Page updated 2021-06-12
Handle: RePEc:ptu:wpaper:w201601