 Stationary bootstrapping for semiparametric panel unit root testsEunju Hwang and Dong Wan Shin Computational Statistics & Data Analysis, 2015, vol. 83, issue C, 14-25 Abstract: For panels of possible cross-sectional and serial dependency, stationary bootstrapping is applied to construct unit root tests that are valid regardless of the nuisance parameters of such dependency. The tests are semiparametric in that no model structure is imposed on the serial correlation and the cross-sectional correlation. The statistics are Wald tests and t-bar type tests based on the OLSE (ordinary least squares estimator). Residual-based and difference-based stationary bootstrapping are applied to obtain valid critical values of the tests. Both ordinary and recursive mean adjustments are considered. Large sample validity of the bootstrap tests is established for a large time series dimension. A Monte-Carlo simulation compares the proposed tests, yielding some promising tests, i.e., the t-bar type tests based on difference-based bootstrapping and recursive adjustment. Keywords: Cross-sectional dependence; Difference-based bootstrapping; Recursive mean adjustment; Residual-based bootstrapping (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:83:y:2015:i:c:p:14-25 DOI: 10.1016/j.csda.2014.09.004 Access Statistics for this article Computational Statistics & Data Analysis is currently edited by S.P. Azen More articles in Computational Statistics & Data Analysis from Elsevier |
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