Alternative estimators of cointegrating parameters in models with nonstationary data: an application to US export demand
AbstractThis article presents Monte Carlo simulations which compare the empirical performance of two alternative single equation estimators of the equilibrium parameters in a dynamic relationship. The estimators considered are Stock and Watson's Dynamic Ordinary Least Squares (DOLS) estimator and Bewley's transformation of the general autoregressive distributed lag model. The results indicate that the Bewley transformation produces a lower mean-square error as well as superior serial correlation properties even with lower truncation lags for the lagged variables included in the estimation equation. An application is then provided which examines the nature of the equilibrium relationship between aggregate US exports, world trade and the US real exchange rate. This confirms that estimation of the equilibrium parameters of this relationship by the Bewley transformation produces results which are superior to estimation by DOLS.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 45 (2013)
Issue (Month): 5 (February)
Contact details of provider:
Web page: http://www.tandfonline.com/RAEC20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Holmes, Mark J. & Shen, Xin, 2013. "A note on the average propensity to consume, wealth and threshold adjustment," Economic Modelling, Elsevier, vol. 35(C), pages 309-313.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.