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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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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container_title Hitotsubashi journal of economics
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Kurozumi, Eiji
description 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.
doi_str_mv 10.15057/22026
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source EconLit s plnými texty; International Bibliography of the Social Sciences (IBSS); Business Source Ultimate【Trial: -2024/12/31】【Remote access available】; JSTOR Archival Journals and Primary Sources Collection
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
title A LOCALLY OPTIMAL TEST FOR NO UNIT ROOT IN CROSS-SECTIONALLY DEPENDENT PANEL DATA
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