Swapping the Nested Fixed-Point Algorithm: a Class of Estimators for Discrete Markov Decision Models
This paper proposes a procedure for the estimation of discrete Markov decision models and studies its statistical and computational properties. Our method is similar to Rust's Nested Fixed-Point algorithm (NFXP), but the order of the two nested algorithms is swapped. First, we prove that this method produces the maximum likelihood estimator under the same conditions as NFXP. However, our procedure requires significantly fewer policy iterations than NFXP. Second, based on this algorithm, we define a class of sequential consistent estimators, K -stage Policy Iteration (PI) estimators, that encompasses MLE and Holz-Miller, and we obtain a recursive expression for their asymptotic covariance matrices. This presents the researcher with a 'menu' of sequential estimators reflecting a trade-off between efficiency and computational cost. Using actual and simulated data we compare the relative performance of these estimators. In all our experiments, the benefits in efficiency of using a two-stage PI estimator instead of a one-stage estimator (i.e., Hotz-Miller) are very significant. More interestingly, the benefits of MLE relative to two-stage PI are small.
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|
|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:scecf9:332. 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.