Estimation of the Monetary Policy Model by the Kalman Filter and the Bootstrap Filter

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Year of publication 2004
Type Article in Proceedings
Conference Mathematical Methods in Economics 2004
MU Faculty or unit

Faculty of Economics and Administration

Field Economy
Keywords monetary policy; forward-looking model; discretion; Iterative Extended Kalman Filter Smoother; weighted Bootstrap algorithm
Description The monetary policy problem is explained in a simple theoretical framework based on [1]. Standard approach to non-linear recursive estimation is the utilization of the Iterative Extended Kalman filter. Monte Carlo methods (like the weighted Bootstrap method) provide an important alternative, especially for non-Gaussian systems. These approaches were used to estimate the states and parameters of a macroeconomic model of the Czech republic and their difference is explained.
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