Beyond Panel Unit Root Tests: Using Multiple Testing to Determine the Non-Stationarity Properties of Individual Series in a Panel

Hyungsik Moon () and Benoit Perron ()

Cahiers de recherche from Centre interuniversitaire de recherche en économie quantitative, CIREQ

Abstract: Most panel unit root tests are designed to test the joint null hypothesis of a unit root for each individual series in a panel. After a rejection, it will often be of interest to identify which series can be deemed to be stationary and which series can be deemed nonstationary. Researchers will sometimes carry out this classification on the basis of n individual (univariate) unit root tests based on some ad hoc significance level. In this paper, we demonstrate how to use the false discovery rate (FDR) in evaluating I(1)=I(0) classifications based on individual unit root tests when the size of the cross section (n) and time series (T) dimensions are large. We report results from a simulation experiment and illustrate the methods on two data sets.

Keywords: False discovery rate; Multiple testing; unit root tests; panel data (search for similar items in EconPapers)
JEL-codes: C32 C33 C44 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2010
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Beyond panel unit root tests: Using multiple testing to determine the nonstationarity properties of individual series in a panel (2012)
Working Paper: Beyond Panel Unit Root Tests: Using Multiple Testing to Determine the Non Stationarity Properties of Individual Series in a Panel (2011)
Working Paper: Beyond Panel Unit Root Tests: Using Multiple Testing to Determine the Non Stationarity Properties of Individual Series in a Panel (2010)
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