An Alternative to Stationarization
AbstractFor good reasons, it is standard practice to remove trends before linearizing a growth model. This paper explores an alternative strategy that consists in computing local approximations around successive points in the state space. Obviously this is terribly inefficiant it trend removal is feasible, but it makes possible to do local approximation in models that don't allow for trend removal. Among such models one can find models that don't display balanced growth and some models with learning
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
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.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 377.
Date of creation: 04 Jul 2006
Date of revision:
approximation method; growth models;
Find related papers by JEL classification:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
You can help add them by filling out this form.
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.