Efficient Simulation and Integrated Likelihood Estimation in State Space Models
Joshua Chan and Ivan Jeliazkov (2009)
International Journal of Mathematical Modelling and Numerical Optimisation, 1, 101-120
[ Journal Version | Working Paper |
Code ]
How to cite. If you use this code or implement the precision sampler for linear Gaussian state space models, please cite: Chan and Jeliazkov (2009), Efficient Simulation and Integrated Likelihood Estimation in State Space Models, International Journal of Mathematical Modelling and Numerical Optimisation, 1, 101-120.
Related modules. High-dimensional state space models | Trend inflation models | Large Bayesian VARs overview | SV specification choice | Order-invariant BVAR-SV
This code implements the precision sampler to estimate a time-varying parameter vector autoregression with constant volatility and an unobserved components model with stochastic volatility
The TVP-VAR application considers a 4-variable VAR: output (GDP) growth, unemployment rate, interest rate, and inflation. The unobserved components model example fits US CPI inflation.