Abstract
We estimate a multivariate unobserved components stochastic volatility model to explain the dynamics of a panel of six exchange rates against the US dollar. The empirical model is based on the assumption that two countries’ monetary policy strategies may be well described by Taylor rules with a time‐varying inflation target, a time‐varying natural rate of unemployment, and interest rate smoothing. Compared to the existing literature, our model simultaneously provides estimates of the latent components included in a typical Taylor rule specification and the model‐based real exchange rate. Our estimates closely track major movements along with important time series properties of real and nominal exchange rates across all currencies considered, outperforming a benchmark model that does not account for changes in trend inflation and trend unemployment. More precisely, the proposed approach improves on competing models in tracking the actual evolution of the real exchange rate in terms of simple correlations while it appreciably improves on simpler competitors in terms of matching the persistence of the real exchange rate.
Highlights
To what extent do economic fundamentals explain exchange rate movements? Following the seminal work by Meese and Rogoff (1983), a wealth of studies have aimed to answer this question by comparing the out-of-sample predictive ability of economic exchange rate models to random walk forecasts, with mixed success (for an overview, see Rossi (2013))
We examine whether taking into account slow-moving trends—such as changes in the inflation target or the natural rate of unemployment—improves the in-sample explanatory power of exchange rate models
To assess whether the distinction between trend inflation and the inflation gap is supported by the data, we propose a novel model specification prior that enables testing whether it is necessary to estimate separate coefficients related to gap and trend components
Summary
To what extent do economic fundamentals explain exchange rate movements? Following the seminal work by Meese and Rogoff (1983), a wealth of studies have aimed to answer this question by comparing the out-of-sample predictive ability of economic exchange rate models to random walk forecasts, with mixed success (for an overview, see Rossi (2013)). A decline in inflation below target is associated with a depreciation, if the central bank cuts its policy interest rate more than one-for-one Such considerations imply that the researcher needs to estimate latent variables such as trend inflation and the inflation gap. We contribute to recent research on the uncovered interest parity (UIP) puzzle These studies aim to explain the low or even negative correlation between exchange rate changes and the interest rate differential by the fact that interest rates are driven by a variety of shocks. A benchmark model, which is estimated on the same information set but does not discriminate between trend and gap components, yields lower correlations comparable to existing studies (see Engel and West 2006; Mark 2009).
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