Estimation of the Czech real business cycle model with prediction

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Authors

DAVID Stanislav

Year of publication 2005
Type Article in Proceedings
Conference Trendy hospodárskeho a sociálneho rozvoja v krajinách EU
MU Faculty or unit

Faculty of Economics and Administration

Citation
Field Economy
Keywords Business cycle; Linearized DSGE model; solution of DSGE model; Kalman Filter with log likelihood optimalization
Description In recent years has been developed new approach of the maximum likelihood estimation of the business cycle models incorporating rational expectations based on the method of the Blanchard and Kahn by Peter N. Ireland. Ireland has estimated the models with quarterly time-series data from the United States economy. It was a stimulus to verify result with the Czech Republic data. The paper begins by presenting small New Keynesian DSGE model. It goes on to show the estimated model with quarterly time-series data of the Czech economy. The model's parameters are estimated by maximum likelihood, as described by Hamilton. The Kalman filter is used to evaluate the negative log likelihood function. The last section presents the forecasts of the model. Not just the prediction of the model but also the prediction of the similar VAR models.
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