A robust sign test for panel unit roots under cross sectional dependence

Dong Wan Shin, Soo Jung Park, Man Suk Oh

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


A robust sign test is proposed for testing unit roots in cross-sectionally dependent panel data. Large sample Gaussian null asymptotics of the test are established under (fixed N, large T) and, for serially uncorrelated error cases, under (large N, fixed T), where N is the number of panel units and T is the length of time span. The limiting null distribution is valid, even if the error processes are subject to any type of conditional heteroscedasticity. A Monte-Carlo experiment reveals that, compared with other existing tests, the proposed test has a very stable size property for wider classes of error distributions, type of conditional heteroscedasticities, type of cross-sectional correlations, and values of (N, T) while having reasonable power. Especially, for small T like T = 5, 10, 20, the proposed test shows much stabler size performance than other existing tests. The unemployment rates of the 51 states of the USA are analyzed by the proposed method, which reveals some evidence for unit roots in the presence of factor and spatial cross-section correlation.

Original languageEnglish
Pages (from-to)1312-1327
Number of pages16
JournalComputational Statistics and Data Analysis
Issue number4
StatePublished - 15 Feb 2009

Bibliographical note

Funding Information:
The authors are very grateful for the two anonymous referees for their comments. This work was supported by the Korea Research Foundation Grant funded by the Korean Government(MOEHRD) (KRF-2005-070-C00021).


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