A LOCALLY OPTIMAL TEST FOR NO UNIT ROOT IN CROSS-SECTIONALLY DEPENDENT PANEL DATA

This paper develops a simple test for the null hypothesis of no unit root for panel data with cross-sectional dependence in the form of a common factor in the disturbance. We do not estimate the common factor but mop-up its effect by employing the same method as the one proposed in Pesaran (2007) in...

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Bibliographic Details
Published in:Hitotsubashi journal of economics 2011-12, Vol.52 (2), p.165-184
Main Authors: Hadri, Kaddour, Kurozumi, Eiji
Format: Article
Language:English
Subjects:
Economic models
Economic theory
Gaussian distributions
Hypothesis
Infinity
Lagrange multiplier
Model testing
Natural satellites
Null hypothesis
Panel data
Perceptron convergence procedure
Probabilities
Root test
Statistical discrepancies
Statistical models
Statistical theories
Studies
Time series
Unit root
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Summary:This paper develops a simple test for the null hypothesis of no unit root for panel data with cross-sectional dependence in the form of a common factor in the disturbance. We do not estimate the common factor but mop-up its effect by employing the same method as the one proposed in Pesaran (2007) in the unit root testing context. We show that our test is asymptotically locally optimal, although the optimality is not guaranteed under a wide range of the alternative.
ISSN:0018-280X
2436-097X
DOI:10.15057/22026