GMM Estimation of Autoregressive Roots Near Unity with Panel Data

Hyungsik Moon ()

No 913, Econometric Society World Congress 2000 Contributed Papers from Econometric Society

Abstract: This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data. The two moment conditions studied are obtained by constructing bias corrections to the score functions under OLS and GLS detrending, respectively. It is shown that the moment condition under GLS detrending corresponds to taking the projected score on the Bhttacharyya basis, linking the approach to recent work on projected score methods for models with infinite numbers of nuisance parameters (Waterman and Lindsay, 1998). Assuming that the localizing parameter takes a non-positive value, we establish consistency of the GMM estimator and find its limiting distribution. A notable new finding is that the GMM estimator is super-consistent (i.e., has convergence rate faster than root n) when the true localizing parameter is zero (i.e., when there is a panel unit root) and the deterministic trends in the panel are linear.

Date: 2000-08-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://fmwww.bc.edu/RePEc/es2000/0913.pdf main text (application/pdf)

Related works:
Journal Article: GMM Estimation of Autoregressive Roots Near Unity with Panel Data (2004)
Working Paper: GMM Estimation of Autoregressive Roots Near Unity with Panel Data (2003)
Working Paper: GMM Estimation of Autoregressive Roots Near Unity with Panel Data (2000)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ecm:wc2000:0913

Access Statistics for this paper

More papers in Econometric Society World Congress 2000 Contributed Papers from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().