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Estimation and filtering of nonlinear MS-DSGE models

Sergey Ivashchenko

HSE Working papers from National Research University Higher School of Economics

Abstract: This article suggests and compares the properties of some nonlinear Markov-switching filters. Two of them are sigma point filters: the Markov switching central difference Kalman filter (MSCDKF) and MSCDKFA. Two of them are Gaussian assumed filters: Markov switching quadratic Kalman filter (MSQKF) and MSQKFA. A small scale financial MS-DSGE model is used for tests. MSQKF greatly outperforms other filters in terms of computational costs. It also is the first or the second best according to most tests of filtering quality (including the quality of quasi-maximum likelihood estimation with use of a filter, RMSE and LPS of unobserved variables).

Keywords: regime switching; second-order approximation; non-linear MS-DSGE estimation; MSQKF; MSCDKF (search for similar items in EconPapers)
JEL-codes: C13 C32 E32 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2016
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-ets, nep-mac and nep-ore
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Published in WP BRP Series: Economics / EC, May 2016, pages 1-23

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