National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Real-time versus revised data in estimating the Taylor rule for the Czech Republic
Beňo, David ; Potužák, Pavel (advisor) ; Slaný, Martin (referee)
The main task of this paper is to analyze the differences between estimates of Taylor rule in real-time and with revised data. Estimates of the Taylor rule for the Czech Republic are compared. The source of data is OECD real-time database. The analysis shows that the estimates in real-time and ex-post vary significantly. The average deviation is equal to 0.9 percentage points. The main cause is the estimation of the output gap in real-time. Parameters of estimated reaction function also depend on the type of used data. The rule of inflation targeting or natural growth is more suitable for the use in real-time.
Forecasting Czech GDP Using Mixed-Frequency Data Models
Franta, Michal ; Havrlant, David ; Rusnák, Marek
In this paper we use a battery of various mixed-frequency data models to forecast Czech GDP. The models employed are mixed-frequency vector autoregressions, mixed-data sampling models, and the dynamic factor model. Using a dataset of historical vintages of unrevised macroeconomic and financial data, we evaluate the performance of these models over the 2005–2012 period and compare them with the Czech National Bank’s macroeconomic forecasts. The results suggest that for shorter forecasting horizons the accuracy of the dynamic factor model is comparable to the CNB forecasts. At longer horizons, mixed-frequency vector autoregressions are able to perform similarly or slightly better than the CNB forecasts. Furthermore, moving away from point forecasts, we also explore the potential of density forecasts from Bayesian mixed-frequency vector autoregressions.
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