Moving Average Stochastic Volatility Models with Application to Inflation Forecast

Joshua Chan (2013)
Journal of Econometrics, 176(2), 162-172
[ Journal Version | Working Paper | Code ]

This code estimates four stochastic volatility models with moving average errors. The four models are:

1. UC-MA: unobserved components model with SV and moving average errors
2. UCSV-MA: same as UC-MA but with an additional SV process for the trend
3. AR(1)-MA: AR(1) model with SV and moving average errors
4. AR(2)-MA: AR(2) model with SV and moving average errors

The MCMC algorithms are based on fast band matrix routines instead of the Kalman filter.

The methodology is illustrated with an application involving US CPI inflation.