Application of the Bootstrap Filter Method on a Small Economy Model
| Authors | |
|---|---|
| Year of publication | 2005 |
| Type | Article in Proceedings |
| Conference | Proceedings of the 23rd International Conference Mathematical Methods in Economics 2005 |
| MU Faculty or unit | |
| Citation | |
| Field | Economy |
| Keywords | weighted Bootstrap algorithm; monetary policy model; conditional probality density functions; impulse responses rational expectations |
| Description | The paper shows the monetary policy problem in a simple framework and it illustrates the behaviour of the model on the Czech economy data. Model parameters are estimated by the weighted Bootstrap algorithm which represents an important alternative approach to model estimation. Its power lies in its generality because it is usable for non-local systems. It is especially important in the case that classical methods like extended Kalman filter diverge or are not applicable; or when only the lack of data is available (which is the case of the Czech Republic). Conditional probability density functions of the parameters and states are analyzed. |
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