The Library
Ordinary least squares estimation of a dynamic game model
Tools
Miessi Sanches, Fabio A., Silva, Daniel Junior and Srisuma, Sorawoot (2016) Ordinary least squares estimation of a dynamic game model. International Economic Review, 57 (2). pp. 623-634. doi:10.1111/iere.12170 ISSN 0020-6598.
Research output not available from this repository.
Request-a-Copy directly from author or use local Library Get it For Me service.
Official URL: http://dx.doi.org/10.1111/iere.12170
Abstract
Estimation of dynamic games is known to be a numerically challenging task. A common form of the payoff functions employed in practice takes the linear-in-parameter specification. We show a least squares estimator taking a familiar OLS/GLS expression is available in such a case. Our proposed estimator has a closed form. It can be computed without any numerical optimization and always minimizes the least squares objective function. We specify the optimally weighted GLS estimator that is efficient in the class of estimators under consideration. Our estimator appears to perform well in a simple Monte Carlo experiment.
Item Type: | Journal Article | ||||||||
---|---|---|---|---|---|---|---|---|---|
Divisions: | Faculty of Social Sciences > Economics | ||||||||
Journal or Publication Title: | International Economic Review | ||||||||
Publisher: | Wiley-Blackwell Publishing, Inc. | ||||||||
ISSN: | 0020-6598 | ||||||||
Official Date: | 28 April 2016 | ||||||||
Dates: |
|
||||||||
Volume: | 57 | ||||||||
Number: | 2 | ||||||||
Page Range: | pp. 623-634 | ||||||||
DOI: | 10.1111/iere.12170 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Adapted As: |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |