Real-time fiscal forecasting using mixed frequency data

Stylianos Asimakopoulos, Joan Paredes, Thomas Warmedinger

Research output: Contribution to journalArticle

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.
Original languageEnglish
Pages (from-to)369-390
Number of pages22
JournalThe Scandinavian Journal of Economics
Volume22
Issue number1
Early online date3 Dec 2018
DOIs
Publication statusPublished - 31 Jan 2020

Keywords

  • fiscal policy
  • mixed-frequency data
  • real-time data
  • short-term forecasting

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