Bootstrapping the Box-Pierce Q test: A robust test of uncorrelatedness

Joel L. Horowitz, I. N. Lobato, John C. Nankervis, N. E. Savin*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


This paper describes a test of the null hypothesis that the first K autocorrelations of a covariance stationary time series are zero in the presence of statistical dependence. The test is based on the Box-Pierce Q statistic with bootstrap-based P-values. The bootstrap is implemented using a double blocks-of-blocks procedure with prewhitening. The finite sample performance of the bootstrap Q test is investigated by simulation. In our experiments, the performance is satisfactory for samples of n = 500. At this sample size, the differences between the empirical and nominal rejection probabilities are essentially eliminated.

Original languageEnglish (US)
Pages (from-to)841-862
Number of pages22
JournalJournal of Econometrics
Issue number2
StatePublished - Aug 2006


  • Adjusted P-values
  • Blocks of blocks bootstrap
  • Box-Pierce Q
  • Double bootstrap
  • Serial correlation tests

ASJC Scopus subject areas

  • Economics and Econometrics


Dive into the research topics of 'Bootstrapping the Box-Pierce Q test: A robust test of uncorrelatedness'. Together they form a unique fingerprint.

Cite this