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Nonparametric rank tests for non-stationary panels

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Author

Summary, in English

We develop a set of nonparametric rank tests for non-stationary panels based on multivariate variance ratios which use untruncated kernels. As such, the tests do not require the choice of tuning parameters associated with bandwidth or lag length and also do not require choices with respect to numbers of common factors. The tests allow for unrestricted cross-sectional dependence and dynamic heterogeneity among the units of the panel, provided simply that a joint functional central limit theorem holds for the panel of differenced series. We provide a discussion of the relationships between our setting and the settings for which first- and second generation panel unit root tests are designed. In Monte Carlo simulations we illustrate the small-sample performance of our tests when they are used as panel unit root tests under the more restrictive DGPs for which panel unit root tests are typically designed, and for more general DGPs we also compare the small-sample performance of our nonparametric tests to parametric rank tests. Finally, we provide an empirical illustration by testing for income convergence among countries. (C) 2014 Elsevier B.V. All rights reserved.

Publishing year

2015

Language

English

Pages

378-391

Publication/Series

Journal of Econometrics

Volume

185

Issue

2

Document type

Journal article

Publisher

Elsevier

Topic

  • Economics

Keywords

  • Cointegration
  • Cross-sectional dependence
  • Nonparametric rank tests
  • Time series panel
  • Unit roots

Status

Published

ISBN/ISSN/Other

  • ISSN: 0304-4076