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DSGE Model Estimation on the Basis of Second-Order Approximation

Sergey Ivashchenko

Computational Economics, 2014, vol. 43, issue 1, 82 pages

Abstract: This article compares the properties of different non-linear Kalman filters: the well-known Unscented Kalman filter (UKF), the central difference Kalman filter (CDKF) and the new Quadratic Kalman filter (QKF). A small financial DSGE model is repeatedly estimated by several quasi-likelihood methods with different filters for data generated by the model. Errors in parameters estimation are a measure of the filters’ quality. The result shows that the QKF has a reasonable advantage in terms of quality over the CDKF and the UKF, albeit with some loss in speed. Copyright Springer Science+Business Media New York 2014

Keywords: DSGE; QKF; CDKF; UKF; Quadratic approximation; Kalman filtering; C13; C32; E32 (search for similar items in EconPapers)
Date: 2014
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Working Paper: DSGE Model Estimation on Base of Second Order Approximation (2011) Downloads
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DOI: 10.1007/s10614-013-9363-1

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