CHALMOVIANSKÝ, Jakub. What drives the estimation results of DSGE models? Effect of the input data on parameter estimates. In Lucie Váchová, Václav Kratochvíl. Proceedings of 36th International Conference Mathematical Methods in Economics. Prague: MatfyzPress, Publishing House of the Faculty of Mathematics and Physics Charles University, 2018. p. 169-174. ISBN 978-80-7378-372-3.
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Basic information
Original name What drives the estimation results of DSGE models? Effect of the input data on parameter estimates
Authors CHALMOVIANSKÝ, Jakub (703 Slovakia, guarantor, belonging to the institution).
Edition Prague, Proceedings of 36th International Conference Mathematical Methods in Economics, p. 169-174, 6 pp. 2018.
Publisher MatfyzPress, Publishing House of the Faculty of Mathematics and Physics Charles University
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 50202 Applied Economics, Econometrics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Publication form storage medium (CD, DVD, flash disk)
WWW Conference proceedings
RIV identification code RIV/00216224:14560/18:00103666
Organization unit Faculty of Economics and Administration
ISBN 978-80-7378-372-3
UT WoS 000507455300030
Keywords in English Bayesian estimation; DSGE model; Matching moments; Model simulation; Parameter identification
Tags International impact, Reviewed
Changed by Changed by: Mgr. Daniela Marcollová, učo 111148. Changed: 27/4/2020 21:37.
Abstract
In this contribution, I compare three different Bayesian dynamic stochastic general equilibrium (DSGE) models in a simulation-estimation exercise. This exercise is aimed at revealing the capabilities of these models to re-estimate, during the estimation phase, values of parameters previously set in the simulation phase. The first model is the renowned work of Smets and Wouters. The second one is the rather small DSGE model of a closed economy with search and matching frictions on labour market proposed by Lubik. The third one is based on the paper written by Sheen and Wang, where they introduce a model of a small open economy with various labour market frictions. The aim of this contribution is to examine how the complexity of the model and the amount of information needed, represented by the number of observations in the observables, affect the results when the parameters are estimated. At first, I shortly introduce all presented models. Based on the given calibration, trajectories of main endogenous variables are simulated. These simulated trajectories with a various number of observations are then used as observables for estimation of the model parameters to reveal how rich information is needed for each model to properly identify its parameters.
Links
MUNI/A/0966/2017, interní kód MUName: Nekonvenční monetární politika a instituce trhu práce pohledem dynamických stochastických modelů všeobecné rovnováhy (Acronym: Nekonvenční monetární politika)
Investor: Masaryk University, Category A
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