Using time-varying volatility for identification in vector autoregressions: an application to endogenous uncertainty
From MaRDI portal
Publication:2236881
DOI10.1016/j.jeconom.2021.07.001OpenAlexW3188646204MaRDI QIDQ2236881
Todd E. Clark, Andrea Carriero, Massimiliano Marcellino
Publication date: 26 October 2021
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jeconom.2021.07.001
Statistics (62-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)
Related Items (2)
Uses Software
Cites Work
- Unnamed Item
- Structural vector autoregressions with smooth transition in variances
- Identification and estimation of non-Gaussian structural vector autoregressions
- Structural vector autoregressions with Markov switching
- Bayesian analysis of stochastic volatility models with fat-tails and correlated errors
- Real-time forecast evaluation of DSGE models with stochastic volatility
- Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors
- Real-Time Density Forecasts From Bayesian Vector Autoregressions With Stochastic Volatility
- The Impact of Uncertainty Shocks
- Uncertainty Shocks in a Model of Effective Demand
- Identification Using Stability Restrictions
- Really Uncertain Business Cycles
- MONETARY POLICY UNCERTAINTY AND ECONOMIC FLUCTUATIONS
- Uncertainty Traps*
- Identifying Shocks via Time-Varying Volatility
- Uncertainty Shocks as Second-Moment News Shocks
- Structural Vector Autoregressive Analysis
- Time Varying Structural Vector Autoregressions and Monetary Policy
- Getting It Right
- Estimation and Forecasting in Models with Multiple Breaks
- Identification, estimation and testing of conditionally heteroskedastic factor models
This page was built for publication: Using time-varying volatility for identification in vector autoregressions: an application to endogenous uncertainty
