What drives the estimation results of DSGE models? Effect of the input data on parameter estimates

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F18%3A00103666" target="_blank" >RIV/00216224:14560/18:00103666 - isvavai.cz</a>
Result on the web
<a href="https://mme2018.fm.vse.cz/" target="_blank" >https://mme2018.fm.vse.cz/</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
What drives the estimation results of DSGE models? Effect of the input data on parameter estimates
Original language description
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.
Czech name
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Czech description
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Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of 36th International Conference Mathematical Methods in Economics
ISBN
9788073783723
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
169-174
Publisher name
MatfyzPress, Publishing House of the Faculty of Mathematics and Physics Charles University
Place of publication
Prague
Event location
Jindřichův Hradec, Czech Republic
Event date
Jan 1, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000507455300030

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