Working Paper: CEPR ID: DP4958
Authors: Michel R. van Tol; Christian C. Wolff
Abstract: In this paper we develop a multivariate threshold vector error correction model of spot and forward exchange rates that allows for different forms of equilibrium reversion in each of the cointegrating residual series. By introducing the notion of an indicator matrix to differentiate between the various regimes in the set of nonlinear processes we provide a convenient framework for estimation by OLS. Empirically, out-of sample forecasting exercises demonstrate its superiority over a linear VECM, while being unable to out-predict a (driftless) random walk model. As such we provide empirical evidence against the findings of Clarida and Taylor (1997).
Keywords: Foreign exchange; Multivariate threshold cointegration; TAR models
JEL Codes: C51; C53; F31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| multivariate threshold vector error correction model (C32) | different forms of equilibrium reversion (D50) |
| multivariate threshold vector error correction model (C32) | dynamics of exchange rates (F31) |
| multivariate threshold vector error correction model (C32) | superior out-of-sample forecasts (C53) |
| multivariate threshold vector error correction model (C32) | better fit for the data (C52) |
| different forms of equilibrium reversion (D50) | dynamics of exchange rates (F31) |
| linear VECM (C22) | predictive accuracy (C52) |
| driftless random walk model (C22) | predictive accuracy (C52) |