Arbeitspapier
Bayesian estimation and model selection in the generalised stochastic unit root model
We develop Bayesian techniques for estimation and model comparison in a novel Generalised Stochastic Unit Root (GSTUR) model. This allows us to investigate the presence of a deterministic time trend in economic series, while allowing the degree of persistence to change over time. In particular the model allows for shifts from stationarity I(0) to nonstationarity I(1) or vice versa. The empirical analysis demonstrates that the GSTUR model provides new insights on the properties of some macroeconomic time series such as stock market indices, inflation and exchange rates.
- Language
-
Englisch
- Bibliographic citation
-
Series: SFB 649 Discussion Paper ; No. 2010,006
- Classification
-
Wirtschaft
Bayesian Analysis: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- Subject
-
Stochastic Unit Root
MCMC
Bayesian
Unit Root Test
Schätztheorie
Bayes-Statistik
Zeitreihenanalyse
Theorie
Schätzung
Finanzmarkt
- Event
-
Geistige Schöpfung
- (who)
-
Yang, Fuyu
Leon-Gonzalez, Roberto
- Event
-
Veröffentlichung
- (who)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (where)
-
Berlin
- (when)
-
2010
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Yang, Fuyu
- Leon-Gonzalez, Roberto
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Time of origin
- 2010
Other Objects (12)
Bayesian Estimation and Model Selection in theGeneralised Stochastic Unit Root Model
Bayesian strategies: probabilistic programs as generalised graphical models
Bayesian inference and experimental design for large generalised linear models
Bayesian unit root test for panel data
Generalised instrumental variable models
Unit root tests in three-regime SETAR models
The power of the 'objective' Bayesian unit-root test
Model selection in generalised structured additive regression models
Model selection in generalised structured additive regression models
Testing for a unit root in noncausal autoregressive models
Impact of Model Specification Decisions on Unit Root Tests
A Model Selection Approach to detect Seasonal Unit Roots
Bayesian Estimation and Model Selection in theGeneralised Stochastic Unit Root Model
Bayesian strategies: probabilistic programs as generalised graphical models
Bayesian inference and experimental design for large generalised linear models
Bayesian unit root test for panel data
Generalised instrumental variable models
Unit root tests in three-regime SETAR models
The power of the 'objective' Bayesian unit-root test
Model selection in generalised structured additive regression models
Model selection in generalised structured additive regression models
Testing for a unit root in noncausal autoregressive models
Impact of Model Specification Decisions on Unit Root Tests
A Model Selection Approach to detect Seasonal Unit Roots
Bayesian Estimation and Model Selection in theGeneralised Stochastic Unit Root Model
Bayesian strategies: probabilistic programs as generalised graphical models
Bayesian inference and experimental design for large generalised linear models
Bayesian unit root test for panel data
Generalised instrumental variable models
Unit root tests in three-regime SETAR models
The power of the 'objective' Bayesian unit-root test
Model selection in generalised structured additive regression models
Model selection in generalised structured additive regression models
Testing for a unit root in noncausal autoregressive models
Impact of Model Specification Decisions on Unit Root Tests