Real-Time Fiscal Forecasting Using Mixed-Frequency Data* |
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Authors: | Stylianos Asimakopoulos Joan Paredes Thomas Warmedinger |
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Institution: | 1. University of Bath, Bath, BA2 7AY UK;2. European Central Bank, DE-60640 Frankfurt, Germany |
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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. |
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Keywords: | Fiscal policy mixed-frequency data real-time data short-term forecasting |
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