DSGE model estimation on base of second order approximation

This article compares properties of different non-linear Kalman filters: well-known Unscented Kalman filter (UKF), Central Difference Kalman Filter (CDKF) and unknown Quadratic Kalman filter (QKF). Small financial DSGE model is repeatedly estimated by maximum quasi-likelihood methods with different filters for data generated by the model. Errors of parameters estimation are measure of filters quality. The result is that QKF has reasonable advantage in quality over CDKF and UKF with some loose in speed.