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*I would like to thank Leonardo Bartolini, Peter Clark, Peter Isard, Lutz Kilian, Joaquim Levy, Karen Lewis, Ronald MacDonald, Richard Marston and Peter Wickham for their comments, Albert Ando, Charles Engel, Robert Flood and participants of the S.A.DI.BA.-Bank of Italy conference in Perugia (Italy) for helpful discussions, Mr. Alan Teck for permission to use the Financial Times Currency Forecaster data, and Susanna Mursula for technical assistance.
In the remainder of the study the expressions “currency risk premium,” “ex ante excess returns” and “expected excess returns” will be used interchangeably.
Which holds in absence of capital restrictions or sizable transaction costs.
Eurodeposit interest rates are used because CIP holds continuously in these markets. In line with the institutional features of Eurodeposit markets, interest rates are compounded continuously and are expressed in per-holding period, i.e.,
Note that estimation of the rational expectations risk premium requires, in general, knowledge of the model economy according to which agents form consistent expectations (see Section IV). The use of linear projections as in (6) is just a data-based shortcut to produce a measure of the rational risk premium. It does not require prior knowledge of a model economy (including functional forms and model parameters), and relies only on a guess of the relevant variables contained in agents’ information sets and the assumption of linearity.
In this case, by CIP, equal to
Forward rates are constructed from CIP using Eurodeposit interest rates. For a description of these and other data, see Appendix I.
Notice that the sample means for the 3 month lira/dollar risk premium is insignificantly different from zero. The figures reported in Table 1 are similar to the ones obtained by Cavaglia et al., (1993) with a different survey data set.
The presence of a negative lira/dollar risk premium, i.e., the perception that dollar assets are “riskier” than lira-denominated assets, may appear surprising. A closer look, however, reveals this anomaly to be coherent with the data. The presence of a very large and negative risk premium on the mark/dollar exchange rate (−5.6 percent for the same time period), pulls down the average lira/dollar risk premium, given that the lira/mark risk premium cannot be too high because these currencies belong (at least, for part of the sample) to a credible peg. This observation is also confirmed in a study by Favero et al. (1996), where it is contended that lira/mark excess returns may be driven not only by local factors, but also by international factors, i.e., by the presence of a highly negative mark/dollar risk premium.
Giorgianni (1996) links the presence of instability in dollar ex ante excess returns with policy switches and shifts in expectations functions.
Unit root test results on spot rates, expectations and interest rates are available from the author upon request. Standard Augmented Dickey-Fuller tests on these variables do not reject the unit root hypothesis at the usual 5 percent significance level.
A top-down lag selection procedure was adopted in the choice of the maximal lag for the first difference terms to be included in the ADF auxiliary regressions (the parametric correction for the presence of serial dependence in the residuals). Two sets of regressions were considered, one including only a constant term and another including a constant term and a linear trend. Both regressions produced similar results. Only the first set of results is included in Table 1.
A further a priori restriction is that
See Engel (1992) for an explanation of the advantages of using such approach.
The two stage estimation strategy adopted here is close in spirit to Hodrick’s (1989) and Cheung’s (1993) tests of the Lucas model. A discussion of the statistical aspects of this procedure is provided in the first study (see page 455 of Hodrick (1989)).
For Italy and the United States, this procedure identifies a VAR(3), while, for Italy and Germany a VAR(4). The results of the order selection procedure and of the tests for absence of autocorrelation, heteroskedasticity and nonnormality in the estimated errors of the chosen VAR’s are available from the author.
See Hamilton (1994) on the differences between parametric and nonparametric estimates of conditional second moments. Ideally, a simultaneous and multivariate parametric model of first and second moments (i.e., a VAR+Multivariate GARCH) could be specified and estimated by Maximum Likelihood. However, besides its intrinsic computational difficulties, this strategy is not appealing because GARCH effects at monthly frequency are notoriously very weak.
Different bandwidth parameters λ were experimented with and the corresponding second moments plotted to check the degree of smoothness. In the end, λ was fixed to 5 for all second moments. The results presented in the next sections were found robust to values of λ ranging between 2 and 11.
The regressors in the risk premium equations are lagged once to account for the typical delays in the release of official statistics.
The one-step ahead predicted values from these regressions were smoothed to emphasize the low frequency components of the data.
The FTCF, formerly known as the Currency Forecasters Digest, has been studied in Frankel and Chinn (1993) and Chinn and Frankel (1994a), (1994b). The samples considered in the first two studies were very short (from February 1988 to February 1991, 36 observations overall). In the third study the authors updated their results to June 1994. However, their data set carries three missing observations (Chinn and Frankel (1994b: 23). This paper employs a larger sample (from January 1987 to December 1994) and has no missing observations.
A list of the surveys on exchange rate expectations previously employed can be found in Takagi (1991, Table 1). For completeness, two surveys should be added to that list: the U.K. Money Market Services and the Business International Corporation (respectively, MacDonald (1990) and Cavaglia et al. (1993a) and (1993b).
Exceptions are the months of November and December, when the publication date is generally one week earlier because of Thanksgiving and Christmas.
See, for all, Fama (1984), Canova and Marrinan (1993) and Lewis (1994). Lewis (1994) justifies the adoption of this specification on the ground of parsimony, although she acknowledges the fact that other authors have found significant effects of other variables in explaining the forward bias.
The estimation sample is 1986.01-94.12.
These error bands are based on consistently estimated residuals’ standard errors. Detailed regression results are available from the author.
Notice that Figure A2 presents only the recursions for the 3-month case (for both currencies). This is a more stringent test, because the 12-month estimated equations (not included in the figures to save space) display higher instability.