Large-N and Large-T Properties of Panel Data Estimators and the Hausman Test
This paper examines the asymptotic properties of the popular within, GLS estimators and the Hausman test for panel data models with both large numbers of cross-section (N) and time-series (T) observations. The model we consider includes the regressors with deterministic trends in mean as well as time invariant regressors. If a time-varying regressor is correlated with time invariant regressors, the time series of the time varying regressor is not ergodic. Our asymptotic results are obtained considering the dependence of such non-ergodic time-varying regressors. We find that the within estimator is as efficient as the GLS estimator. Despite this asymptotic equivalence, however, the Hausman statistic, which is essentially a distance measure between the two estimators, is well defined and asymptotically \chi^2-distributed under the random effects assumption.
Year of publication: |
2001-08
|
---|---|
Authors: | Ahn, Seung Chan ; Moon, Hyungsik Roger |
Institutions: | International Conferences on Panel Data |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Large-N and large-T properties of panel data estimators and the Hausman test
Ahn, Seung Chan, (2014)
-
Nonparametric Derivative Estimation for Related-Effect Panel Data
Lee, Myoung-jae, (2002)
-
Language-Group Differences in Very Early Retirement in Finland
Saarela, Jan, (2002)
- More ...