Stationary bootstrapping for cointegrating regressions

Dong Wan Shin, Eunju Hwang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


The validity of stationary bootstrapping is investigated for cointegrating regressions in large samples as well as in finite samples. The bootstrap ordinary least squares estimator (OLSE) is shown to be valid in large samples having the same limiting distribution as the OLSE under a similar normalization. Large sample validity of a bootstrap test regarding cointegration parameters is also established. Finite sample size and power properties of the bootstrap test are investigated via a Monte Carlo experiment.

Original languageEnglish
Pages (from-to)474-480
Number of pages7
JournalStatistics and Probability Letters
Issue number2
StatePublished - Feb 2013

Bibliographical note

Funding Information:
The authors are very grateful to an anonymous referee for valuable comments which improved the paper considerably. This research was supported by the National Research Foundation of Korea ( NRF-2009-0084772 , and NRF-2009-0070618 ).


  • Cointegrating regression
  • Stationary bootstrapping


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