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parameter drift with parameters' bounds

PostPosted: Sat Feb 04, 2017 4:17 am
by HouseC
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

Re: parameter drift with parameters' bounds

PostPosted: Sun Feb 05, 2017 4:04 am
by HouseC
Hi, any one could help?

Re: parameter drift with parameters' bounds

PostPosted: Sun Feb 05, 2017 4:30 pm
by jpfeifer
1. What is the reference for what you are trying to do?
2. In general, if you work with a log-linear approximation, there is not way to bound variables (like your capital share) due to linearity. One has to live with this and hope that the data do not assign much probability to it violating the theoretical bounds.

Re: parameter drift with parameters' bounds

PostPosted: Tue Mar 21, 2017 8:10 am
by jpfeifer
I read the relevant part of Seoane (2016). Unfortunately, the implementation is somewhat involved and only possible in Dynare with modifications to
Code: Select all
dsge_likelihood.m

The idea is the following: for each draw of the MCMC, you run the Kalman smoother on the model. If the smoothed "parameters" (which are actually variables now, because they are time-varying) violate the imposed bounds, you reject this draw.

Re: parameter drift with parameters' bounds

PostPosted: Tue Mar 21, 2017 12:18 pm
by HouseC
jpfeifer wrote:I read the relevant part of Seoane (2016). Unfortunately, the implementation is somewhat involved and only possible in Dynare with modifications to
Code: Select all
dsge_likelihood.m

The idea is the following: for each draw of the MCMC, you run the Kalman smoother on the model. If the smoothed "parameters" (which are actually variables now, because they are time-varying) violate the imposed bounds, you reject this draw.


Dear Johannes,

You mean that currently it's impossible to implement the algorithm in Seoane (2016) using dynare? Just want to confirm this issue.

Best,
Sihao

Re: parameter drift with parameters' bounds

PostPosted: Tue Mar 21, 2017 12:21 pm
by jpfeifer
It is not prepackaged, but can be implemented in a few lines of code.

Re: parameter drift with parameters' bounds

PostPosted: Wed Mar 22, 2017 2:21 am
by HouseC
jpfeifer wrote:It is not prepackaged, but can be implemented in a few lines of code.

Many thanks! your suggestion is really helpful!