Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework
Festschrift in Honor of Peter Schmidt, W.C. Horrace and R.C. Sickles, eds., Forthcoming
44 Pages Posted: 13 Apr 2011 Last revised: 23 Oct 2013
Date Written: October 21, 2013
Abstract
This paper develops a cointegrating nonlinear autoregressive distributed lag (NARDL) model in which short- and long-run nonlinearities are introduced via positive and negative partial sum decompositions of the explanatory variables. We demonstrate that the model is estimable by OLS and that reliable long-run inference can be achieved by bounds-testing regardless of the integration orders of the variables. Furthermore, we derive asymmetric dynamic multipliers that graphically depict the traverse between the short- and the long-run. The salient features of the model are illustrated using the example of the nonlinear unemployment-output relationship in the US, Canada and Japan.
Keywords: Asymmetric Cointegrating Relationships, Asymmetric Dynamic Multipliers, Nonlinear ARDL (NARDL) ECM-based Estimation and Tests, Nonlinear Unemployment-Output Relationship, Asymmetric Gasoline Price Adjustment
JEL Classification: C12, C13, J64
Suggested Citation: Suggested Citation
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