parameter drift with parameters' bounds
Posted: Sat Feb 04, 2017 4:17 am
Dears,
I'm trying to estimate some parameters drifts but these parameters are bounded. For example, if I assume capital share in CD production function itself follows AR (1) process. Y_t=A_t*K_t^(alpha_t)*L_t^(1-alpha_t), and alpha_t=(1-rho)*alpha+rho*alpha_(t-1).
I can put the persistence and standard deviation into estimation and specify the bound for these estimated parameters. Yet how can I guarantee that alpha_t is between 0 and 1 for all the times.
I read related literature and people suggest to use the smoothed Kalman filter. Can any one elaborate more about it? And how to implement this smoother in dynare? Is there any sample code to follow?
Best,
House
I'm trying to estimate some parameters drifts but these parameters are bounded. For example, if I assume capital share in CD production function itself follows AR (1) process. Y_t=A_t*K_t^(alpha_t)*L_t^(1-alpha_t), and alpha_t=(1-rho)*alpha+rho*alpha_(t-1).
I can put the persistence and standard deviation into estimation and specify the bound for these estimated parameters. Yet how can I guarantee that alpha_t is between 0 and 1 for all the times.
I read related literature and people suggest to use the smoothed Kalman filter. Can any one elaborate more about it? And how to implement this smoother in dynare? Is there any sample code to follow?
Best,
House