Structural Breaks in the Real Exchange Rate and Real Interest Rate Relationship

In this paper we empirically examine the relationship between the real exchange rate and real interest rate differentials using recent econometric methods robust to potential structural breaks. Generally, our study provides evidence of this relationship in the long-run context. More specifically, we first focus on the UK-US relationship, and interestingly find limited evidence of this long-run relationship using traditional methods. But when an approach robust to endogenously determined structural breaks is employed, we find evidence that the real interest rate differential is an important determinant of the real exchange rate. Secondly, in order to investigate the relevance of structural shifts in a more global context, we carry out multiple country analysis. While providing evidence of this long-run relationship, European data suggest that the presence of structural breaks is not very common across countries and is indeed country-specific.

Interest Rate Co-movements, Global Factors and the Long End of the Term Spread

The disconnect between rising short and low long interest rates has been a distinctive feature of the 2000s. Both research and policy circles have argued that international forces, such as global monetary policy (e.g. Rogoff, 2006); international business cycles (e.g. Borio and Filardo, 2007); or a global savings glut (e.g Bernanke, 2005) may be responsible. In this paper, we employ recent advances in panel data econometrics to document the disconnect and link it explicitly to the existence of a global latent factor that dominates the long end of the term spread for the recent period; the saving glut story emerges as the most likely contender for the global factor.

Exchange Rate Predictability in a Changing World

An expanding literature articulates the view that Taylor rules are helpful in predicting exchange rates. In a changing world however, Taylor rule parameters may be subject to structural instabilities, for example during the Global Financial Crisis. This paper forecasts exchange rates using such Taylor rules with Time Varying Parameters (TVP) estimated by Bayesian methods. In core out-of-sample results, we improve upon a random walk benchmark for at least half, and for as many as eight out of ten, of the currencies considered. This contrasts with a constant parameter Taylor rule model that yields a more limited improvement upon the benchmark. In further results, Purchasing Power Parity and Uncovered Interest Rate Parity TVP models beat a random walk benchmark, implying our methods have some generality in exchange rate prediction.

On the Sources of Uncertainty in Exchange Rate Predictability

We analyse the role of time-variation in coefficients and other sources of uncertainty in exchange rate forecasting regressions. Our techniques incorporate the notion that the relevant set of predictors and their corresponding weights, change over time. We find that predictive models which allow for sudden rather than smooth, changes in coefficients significantly beat the random walk benchmark in out-of-sample forecasting exercise. Using innovative variance decomposition scheme, we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients' variability, as the main factors hindering models' forecasting performance. The uncertainty regarding the choice of the predictor is small.