Exchange Rate
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Discussion Papers No. 340, February 2003
Statistics Norway, Research Department
Hilde C. BjÐ"Ñ'rnland and HÐ"Òvard Hungnes
The importance of interest rates
for forecasting the exchange rate
Abstract:
This study compares the forecasting performance of a structural exchange rate model that combines
the purchasing power parity condition with the interest rate differential in the long run, with some
alternative models. The analysis is applied to the Norwegian exchange rate. The long run equilibrium
relationship is embedded in a parsimonious representation for the exchange rate. The structural
exchange rate representation is stable over the sample and outperforms a random walk in an out-ofsample
forecasting exercise at one to four horizons. Ignoring the interest rate differential in the long
run, however, the structural model no longer outperforms a random walk.
Keywords: Equilibrium real exchange rate, cointegration VAR, out-of-sample forecasting
JEL classification: C22, C32, C53, F31
Acknowledgement: The authors wish to thank Ð".... Cappelen, P. R. Johansen and T. Skjerpen for
very useful comments and discussions. The usual disclaimers apply.
Address: Hilde C. BjÐ"Ñ'rnland, University of Oslo and Statistics Norway.
E-mail: h.c.bjornland@econ.uio.no.
HÐ"Òvard Hungnes, Statistics Norway, Research Department. E-mail: havard.hungnes@ssb.no
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1. Introduction
The well cited finding by Meese and Rogoff (1983), that a comprehensive range of exchange rate
models were unable to outperform a random walk, has motivated numerous studies to examine the role
of economic fundamentals in explaining exchange rate behaviour. Later on, however, MacDonald and
Taylor (1994), Chrystal and MacDonald (1995), Kim and Mo (1995) and Reinton and Ongena (1999)
among others, have found that a series of monetary models can beat a random walk in forecasting
performance, at least at the long horizons, using a metric like the root mean square errors (RMSE) for
evaluation. However, although the monetary models have proved somewhat successful in explaining
exchange rate behaviour, they have also encountered many problems. In particular, many of the
cointegrating relationships have taken on incorrect signs when compared to theoretical models
(McNown and Wallace (1994)).
One of the basic building blocks of the monetary models is the purchasing power parity (PPP).
However, empirical evidence from the post Bretton Woods fixed exchange rate system, have found
little to support the PPP condition (see e.g. Rogoff (1996) for a survey)1 and forecasts based on the
PPP condition alone, have provided mixed results (see for instance Fritsche and Wallace (1997)
among others).
The PPP condition has its roots in the goods market. Another central parity condition for the exchange
rate that plays a crucial role in capital market models is uncovered interest parity (UIP). However,
empirical evidence has also generally led to a strong rejection of the UIP condition in the Post Bretton
Woods period (see e.g. Engel (1996) for a survey). On the other hand, Johansen and Juselius (1992)
have suggested that one possible reason why so many researches have failed to find evidence in
support of these parity conditions is the fact that researchers have ignored the links between goods and
capital markets when modelling the exchange rate. By modelling the whole system jointly, one is
better able to capture the interactions between the nominal exchange rate, the price differential and the
interest rate differentials, as well as allowing for different short and long run dynamics.
This paper examines whether a dynamic exchange rate model that combines the purchasing power
parity condition with the uncovered interest parity condition in the long run, can outperform a random
walk model in an out-of-sample forecasting exercise. The model is applied to Norway. Previous
1 The rejections have been less clear-cut using panel data, see e.g. Frankel and Rose (1996) among many others. However,
see O'Connell (1998) and Chortareas and Driver (2001) for critical assessments of these
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