Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data

Stylianos Asimakopoulos, Joan Paredes and Thomas Warmedinger

Scandinavian Journal of Economics, 2020, vol. 122, issue 1, 369-390

Abstract: The sovereign debt crisis has increased the importance of monitoring budgetary execution. We employ real‐time data using a mixed data sampling (MiDaS) methodology to demonstrate how budgetary slippages can be detected early on. We show that in spite of using real‐time data, the year‐end forecast errors diminish significantly when incorporating intra‐annual information. Our results show the benefits of forecasting aggregates via subcomponents, in this case total government revenue and expenditure. Our methodology could significantly improve fiscal surveillance and could therefore be an important part of the European Commission's model toolkit.

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://doi.org/10.1111/sjoe.12338

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:bla:scandj:v:122:y:2020:i:1:p:369-390

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0347-0520

Access Statistics for this article

Scandinavian Journal of Economics is currently edited by Richard Friberg, Matti Liski and Kjetil Storesletten

More articles in Scandinavian Journal of Economics from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().