Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework
University of Leeds - Leeds University Business School - Division of Economics
Dong-A University Business School
University of Melbourne
February 11, 2013
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.
Number of Pages in PDF File: 44
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, J64working papers series
Date posted: April 13, 2011 ; Last revised: March 27, 2013
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