A Note on Nonlinear Cointegration, Misspecification, and Bimodality

Marcelo C. Medeiros, Eduardo Mendes, Les Oxley

Research output: Contribution to journalArticlepeer-review


We derive the asymptotic distribution of the ordinary least squares estimator in a regression with cointegrated variables under misspecification and/or nonlinearity in the regressors. We show that, under some circumstances, the order of convergence of the estimator changes and the asymptotic distribution is non-standard. The t-statistic might also diverge. A simple case arises when the intercept is erroneously omitted from the estimated model or in nonlinear-in-variables models with endogenous regressors. In the latter case, a solution is to use an instrumental variable estimator. The core results in this paper also generalise to more complicated nonlinear models involving integrated time series.

Original languageEnglish (US)
Pages (from-to)713-731
Number of pages19
JournalEconometric Reviews
Issue number7
StatePublished - Oct 2014
Externally publishedYes


  • Asymptotic theory
  • Bimodality
  • Cointegration
  • Misspecification
  • Nonlinearity

ASJC Scopus subject areas

  • Economics and Econometrics


Dive into the research topics of 'A Note on Nonlinear Cointegration, Misspecification, and Bimodality'. Together they form a unique fingerprint.

Cite this