Abstract
Developments in bond markets over the past several years, in particular the decrease in international yield spreads, have raised questions about the relations between long-term interest rates, globalisation of financial activities, and the exchange rate regime. It is generally accepted that under fixed exchange rates, globalisation of financial activities implies a high degree of convergence of long-term interest rates and synchronisation of their movements over time. Interest rates are determined by conditions in the fixed exchange rate region as a whole, rather than in individual countries, and there is correspondingly reduced scope for independent monetary policy by a single country.1 Under floating exchange rates, interest rates differ across countries, in both real and nominal terms, because the existing pressures on financial markets are absorbed by movements in the countries’ exchange rates or expected exchange rate developments. A rise in one country’s interest rate relative to that of a partner is effectively offset by an expected future depreciation or a rise in the relative risk premium on its currency.
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Here we abstract from the exception to this rule that applies for the anchor country in a fixed but adjustable exchange rate regime like Bretton-Woods or the European Monetary System. An excellent description of this so-called ‘n-1 problem’ is provided by De Grauwe (1994).
Recent studies involving long-term rates are Kasman and Pigott (1988), Howe and Pigott (1991), Pigott (1993), Throop (1994), and Fell (1996).
The term currency swap refers to a long-term ‘cross-currency interest rate swap’ that entails an exchange of payment streams.
Deviations from a covered parity in interest rates appear to be somewhat larger among long-term assets than among short-term assets, but the differences are small for the major currencies (Popper, 1993; Fletcher and Taylor, 1996).
We used the so-called benchmark bonds, obtained from the BIS-databank, for all countries It is important that the properties of these bond contracts are identical (so that they differ only in currency of denomination), and the benchmark bonds come closest to this ideal. It is however likely that differences remain, for example because of variations in the degree of liquidity of the underlying markets and differences in the method by which the contracts are sold (Holmes and Wu, 1997).
The methodology which has been adopted to classify a major swing in the bond market is similar to that used by the NBER to date business cycles (Bry and Boschan, 1971). Peaks and troughs were identified using a 12-month moving window. A`bull’ market is defined as at least 6 consecutive months of declining bond yields and a`bear’ market is similarly defined.
In this respect, Browne and Tease (1992) find little tendency for long-term interest rates to vary systematically with the business cycle.
Based on an analysis of twelve OECD-countries, Fase and Vlaar (1997) reach a similar conclusion.
In composing the entire sample, we discarded the observations from the Business International survey for the period that coincided with the available data from the Consensus forecast. As both datasets appeared to be very similar for the overlapping period, discarding the Consensus data would not have changed our conclusions.
Note that for some individual countries, the results between standard and KPSS unit root tests differ, adding to the confusion.
Using this procedure implies a power gain vis-à-vis single equation estimation as in table 2 for at least two reasons. First, SUR utilizes the cross-sectional variations of interest rate differentials as additional information in estimation and testing, which is ignored in the single-equation framework. There exists considerable cross-sectional correlation between movements in interest rates (strongest between Switzerland and Germany (0.81), followed by France-Germany (0.74)). Second, under the null hypothesis of a unit root in all interest rate differentials, this unit root should be imposed on all countries simultaneously. As table 4 below indicates, the restriction that ßi = f3 ∀i cannot be rejected at conventional significance levels for our panel of countries. Accordingly, Monte Carlo simulations performed by Wu and Zhang (1996) revealed that the multivariate Dickey-Fuller test has substantially higher power than standard ADF tests.
In table 4, the results are presented for k=0, as no lagged differences were significant. We re-estimated the model with various values of k and obtained similar results.
The Monte Carlo distribution is robust to alternative specifications of the innovation covariance matrix, see Abuaf and Jorion (1990).
This correction is necessary because the forecast horizon implicit in the expected depreciation (12 months) exceeds the sampling interval (1 month), implying the so-called ‘overlapping observations’ problem. The error term is serially correlated (more specifically, it follows a MA(11) process), thereby rendering the OLS estimates of the covariance matrix inconsistent, despite consistent parameter estimates (Hansen and Hodrick, 1980; Frankel and Froot, 1987;Chinn and Frankel, 1994). The Newey-West standard errors are asymptotically consistent in the presence of serial correlation as well as heteroskedasticity (Hamilton, 1994).
Moreover, the attractive fiscal regime in Switzerland seems relevant in explaining the different results for that country.
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© 2001 Springer Science+Business Media Dordrecht
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Berk, J.M. (2001). Co-Movements in Long-Term Interest Rates and the Role of Exchange Rate Expectations: Evidence from Survey Data. In: The Preparation of Monetary Policy. Financial and Monetary Policy Studies, vol 35. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3405-8_3
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DOI: https://doi.org/10.1007/978-1-4757-3405-8_3
Publisher Name: Springer, Boston, MA
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