Structural vector autoregression with time varying transition probabilities: identifying uncertainty shocks via changes in volatility
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Abstract
Suggested Citation
DOI: 10.23656/25045520/022018/0153
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Cited by:
- Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.
- Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
More about this item
Keywords
structural vector autoregression; Markov switching; time varying transition probabilities; identification via heteroscedasticity; uncertainty shocks; unemployment dynamics;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
- E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2019-01-28 (Econometrics)
- NEP-ETS-2019-01-28 (Econometric Time Series)
- NEP-MAC-2019-01-28 (Macroeconomics)
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