Threshold cointegration in international exchange rates: A Bayesian approach

Publication: Scientific journalJournal articlepeer-review


This paper considers Bayesian estimation of the threshold vector error correction (TVECM) model in moderate to large dimensions. Using the lagged cointegrating error as a threshold variable gives rise to additional difficulties that typically are solved by utilizing large sample approximations. By relying on Markov chain Monte Carlo methods, we are enabled to circumvent these issues and avoid computationally-prohibitive estimation strategies like the grid search. Due to the proliferation of parameters, we use novel global-local shrinkage priors in the spirit of Griffin and Brown (2010). We illustrate the merits of our approach in an application to five exchange rates vis-á-vis the US dollar by means of a forecasting comparison. Our findings indicate that adopting a non-linear modeling approach improves the predictive accuracy for most currencies relative to a set of simpler benchmark models and the random walk.
Original languageEnglish
Pages (from-to)458 - 473
JournalInternational Journal of Forecasting
Issue number2
Publication statusPublished - 2019

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 502025 Econometrics
  • 502047 Economic theory
  • 502018 Macroeconomics

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