Estimating Cointegrating Relations from a Cross Section
AbstractThis paper specifies a regression model describing cointegrating relations between variables at the individual level. The models considered allow for homogeneous cointegration and heterogeneous cointegration. In both cases correlation between the regressors and the regression error can occur through aggregate shocks that are common to all cross-section units so the condition about the regressors being independent of the regression error is not imposed. It is shown that the estimator obtained by a cross-section regression performed at any point in time is a consistent estimator of the cointegrating parameters in the homogeneous case and of the cointegrating parameter means in the heterogeneous case. In both cases the limiting distribution of the cross-section estimator is normal.
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 InfoPaper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number 2004-21.
Length: 15 pages
Date of creation: Nov 2004
Date of revision:
Contact details of provider:
Postal: Øster Farimagsgade 5, Building 26, DK-1353 Copenhagen K., Denmark
Phone: (45) 35 32 30 74
Fax: +45 35 32 30 00
Web page: http://www.econ.ku.dk/CAM/
More information through EDIRC
dynamic panel data models; non-stationary panel data; cointegrating relations; cross-section regression;
Find related papers by JEL classification:
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-12-02 (All new papers)
- NEP-ECM-2004-12-02 (Econometrics)
- NEP-ETS-2004-12-02 (Econometric Time Series)
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: (Thomas Hoffmann).
If references are entirely missing, you can add them using this form.