Dimitrakopoulos, S (2017) The semiparametric asymmetric stochastic volatility model with time-varying parameters: The case of US inflation. Economics Letters, 155. pp. 14-18. ISSN 0165-1765
Abstract
We propose a semiparametric extension of the time-varying parameter regression model with asymmetric stochastic volatility. For parameter estimation we use Bayesian methods. We illustrate our methods with an application to US inflation.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2017 Elsevier B.V. All rights reserved. This is an author produced version of a paper published in Economics Letters. Uploaded in accordance with the publisher's self-archiving policy |
| Keywords: | Asymmetric stochastic volatility; Dirichlet process; Markov chain; Monte Carlo; Time-varying parameters; Inflation |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Economics Division (LUBS) (Leeds) |
| Depositing User: | Symplectic Publications |
| Date Deposited: | 28 Jan 2019 10:35 |
| Last Modified: | 28 Jan 2019 10:35 |
| Status: | Published |
| Publisher: | Elsevier |
| Identification Number: | 10.1016/j.econlet.2017.02.039 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141638 |
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