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Real‐Time Fiscal Forecasting Using Mixed‐Frequency Data *
Author(s) -
Asimakopoulos Stylianos,
Paredes Joan,
Warmedinger Thomas
Publication year - 2020
Publication title -
the scandinavian journal of economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.725
H-Index - 64
eISSN - 1467-9442
pISSN - 0347-0520
DOI - 10.1111/sjoe.12338
Subject(s) - economics , revenue , real time data , debt , fiscal policy , econometrics , european commission , government (linguistics) , commission , macroeconomics , computer science , finance , economic policy , european union , linguistics , philosophy , world wide web
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.