Estimation of the Czech real business cycle model with prediction
| Authors | |
|---|---|
| Year of publication | 2005 |
| Type | Article in Proceedings |
| Conference | Trendy hospodárskeho a sociálneho rozvoja v krajinách EU |
| MU Faculty or unit | |
| 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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