Testing monetary exchange rate models with the Westerlund panel cointegration test

Andrea Szabó

doi:10.47282/economica/2014/7/2/4345

Abstract

Time series testing of long-run monetary models of exchange rate determination in most cases fails to support the conjectures of the theory. The empirical literature increasingly uses the panel technique when testing monetary exchange rate models because the power of the panel unit root and panel cointegration tests seems higher than the pure time series tests. In this paper we examine the validity of the monetary exchange rate models over the period 1996Q1-2011Q4 for US dollar exchange rates of 15 OECD countries using Westerlund’s 2007 panel cointegration tests. We found moderate empirical support for monetary exchange rate models.

Highlights

Monetary exchange rate models are one of the standard analytical tools of international openmacroeconomics
We examined three specifications of the reduced form of the monetary exchange rate models: a two, a three- and a five-variable model (Table 2)
The results of the twoand three-variable model unambiguously confirm that a long run equilibrium relationship exists between the nominal exchange rate and the monetary macro-fundamentals, and the unrestricted model offers moderate support for the empirical validity of the monetary exchange rate models

Summary

Introduction

Monetary exchange rate models are one of the standard analytical tools of international openmacroeconomics. The results usually do not show cointegration between the nominal exchange rate and the monetary macro-fundamentals [Frankel 1984; Meese 1986; Sarantis 1994; Rapach – Wohar 2002; MacDonald – Taylor 1992] These results do not indicate that the theoretical models are inapplicable. Among others, Groen 2000 and Rapach Wohar 2004 attributed the failure of the empirical testing of monetary exchange rate models to the short sample length In such circumstances the power of the unit root and the cointegration tests are too low to reject the null hypothesis of no cointegration between the variables.

Methods

Results

Conclusion