Habit Formation and Price Indexation in DSGE Models with Nominal Rigidities
| Authors | |
|---|---|
| Year of publication | 2009 |
| Type | Article in Proceedings |
| Conference | Mathematical Methods in Economics 2009 |
| MU Faculty or unit | |
| Citation | |
| Field | Economy |
| Keywords | New Keynesian; DSGE; habit formation; price indexation; posterior odds; Bayesian estimation |
| Description | The goal of this paper is to evaluate some characteristics commonly used in New Keynesian DSGE models, such as habit formation in consumption, full price indexation and partial price indexation. This paper estimates six DSGE models in order to determine, which model provides better data fit. The models were estimated on data of US economy. All models were estimated using Bayesian techniques, particularly Metropolis-Hastings algorithm (using Dynare toolbox for Matlab). The data fit measure is posterior odds calculated from marginal likelihood, acquired from Bayesian estimation. Results suggest that including habit formation improves significantly the data fit of the models, whereas including price indexation does not. |
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