Asymptotic theory for the durbin-watson statistic under long-memory dependence

Shisei Nakamura, Masanobu Taniguchi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


In time series regression models with "short-memory" residual processes, the Durbin-Watson statistic (DW) has been used for the problem of testing for independence of the residuals. In this paper we elucidate the asymptotics of DW for "long-memory" residual processes. A standardized Durbin-Watson statistic (SDW) is proposed. Then we derive the asymptotic distributions of SDW under both the null and local alternative hypotheses. Based on this result we evaluate the local power of SDW. Numerical studies for DW and SDW are given.

Original languageEnglish
Pages (from-to)847-866
Number of pages20
JournalEconometric Theory
Issue number6
Publication statusPublished - 1999
Externally publishedYes

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Economics and Econometrics


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