dynamic longitudinal (panel) data;
generalized method of moments;
instrumental variables;
unit roots;
moving average errors;
D O I:
10.1016/j.jspi.2005.11.004
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
We investigate the influence of residual serial correlation and of the time dimension on statistical inference for a unit root in dynamic longitudinal data, known as panel data in econometrics. To this end, we introduce two test statistics based on method of moments estimators. The first is based on the generalized method of moments estimators, while the second is based on the instrumental variables estimator. Analytical results for the Instrumental Variables (IV) based test in a simplified setting show that (i) large time dimension panel unit root tests will suffer from serious size distortions in finite samples, even for samples that would normally be considered large in practice, and (ii) negative serial correlation in the error terms of the panel reduces the power of the unit root tests, possibly up to a point where the test becomes biased. However, near the unit root the test is shown to have power against a wide range of alternatives. These findings are confirmed in a more general set-up through a series of Monte Carlo experiments. (c) 2005 Elsevier B.V. All rights reserved.
机构:
Univ York, Dept Econ & Related Studies, York YO10 5DD, N Yorkshire, EnglandUniv York, Dept Econ & Related Studies, York YO10 5DD, N Yorkshire, England
机构:
Syracuse Univ, Dept Econ, Syracuse, NY 13244 USA
Syracuse Univ, Ctr Policy Res, Syracuse, NY 13244 USASyracuse Univ, Dept Econ, Syracuse, NY 13244 USA
Baltagi, Badi H.
Liu, Long
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机构:
Univ Texas San Antonio, Dept Econ, Coll Business, San Antonio, TX 78249 USASyracuse Univ, Dept Econ, Syracuse, NY 13244 USA