Stochastic Policy Design for Models with Rational Expectations and Time-Varying Parameters
In this paper, we present a method for using rational expectations in a stochastic linear-quadratic optimization framework in which the unknown parameters are updated through a learning scheme. We use the QZ decomposition as suggested by Sims (1996) to solve the rational-expectations part of the model. Parameter updating is done with a Kalman filter, and the optimal control is calculated using the variances and covariances of the uncertain time-varying parameter.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||01 Mar 1999|
|Date of revision:|
|Contact details of provider:|| Postal: CEF99, Boston College, Department of Economics, Chestnut Hill MA 02467 USA|
Web page: http://fmwww.bc.edu/CEF99/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:sce:scecf9:633. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.