Estimating Simultaneous Equations Models by a Simulation Technique
For simultaneous equations models, estimates from ordinary least squares (OLS) methods are biased and even inconsistent and those from two-stage least squares (2SLS) methods are, though consistent, still inadequate because of finite sample biases. A new simulation technique developed here produces better estimates by compensating for the simultaneous bias in those conventional estimation methods. In the simulation (SIM) estimation technique, such biases are directly compensated in situ through a synthetic use of simulations. SIM is demonstrated to outperform the existing techniques through a series of Monte Carlo experiments. Klein's macroeconomic model is used to further illustrate the practical application of SIM. The results are compared with those from OLS and 2SLS to elaborate the attractive performance of SIM. Citation Copyright 1995 by Kluwer Academic Publishers.
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.
Volume (Year): 8 (1995)
Issue (Month): 4 (November)
|Contact details of provider:|| Web page: http://www.springerlink.com/link.asp?id=100248|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:8:y:1995:i:4:p:255-65. 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: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.