Huber, Florian, Kastner, Gregor, Feldkircher, Martin. 2017. A New Approach Toward Detecting Structural Breaks in Vector Autoregressive Models.
BibTeX
Abstract
Incorporating structural changes into time series models is crucial during turbulent economic periods. In this paper, we propose a flexible means of estimating vector autoregressions with time-varying parameters (TVP-VARs) by introducing a threshold process that is driven by the absolute size of parameter changes. This enables us to detect whether a given regression coefficient is constant or time-varying. When applied to a medium-scale macroeconomic US dataset our model yields precise density and turning point predictions, especially during economic downturns, and provides new insights on the changing effects of increases in short-term interest rates over time.
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Status of publication | Published |
---|---|
Affiliation | WU |
Type of publication | Working/discussion paper, preprint |
Language | English |
Title | A New Approach Toward Detecting Structural Breaks in Vector Autoregressive Models |
Year | 2017 |
URL | https://arxiv.org/abs/1607.04532 |
JEL | C11, C32, C52, E42 |
Associations
- People
- Huber, Florian (Former researcher)
- Kastner, Gregor (Details)
- External
- Feldkircher, Martin (Oesterreichische Nationalbank, Austria)
- Organization
- Institute for Statistics and Mathematics IN (Details)
- Research areas (Ă–STAT Classification 'Statistik Austria')
- 1105 Computer software (Details)
- 1162 Statistics (Details)
- 5323 Econometrics (Details)
- 5701 Applied statistics (Details)
- 5707 Time series analysis (Details)