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Discussion Papers No. 340, February 2003

Statistics Norway, Research Department

Hilde C. BjÐ"Ñ'rnland and HÐ"Ґvard Hungnes

The importance of interest rates

for forecasting the exchange rate


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.


HÐ"Ґvard Hungnes, Statistics Norway, Research Department. E-mail:

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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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