Forecasting exchange rates out-of-sample with panel methods and real-time data

• I evaluate exchange rate forecasting models with PPP and Taylor rule fundamentals.
• I construct a quarterly real-time dataset for 10 OECD countries.
• Taylor rule fundamentals performs better at the one-quarter horizon.
• The PPP model forecasts better at the 16-quarter horizon.
• Panel estimation increases the predictability of the PPP model.

This paper evaluates out-of-sample exchange rate forecasting with Purchasing Power Parity (PPP) and Taylor rule fundamentals for 9 OECD countries vis-à-vis the U.S. dollar over the period from 1973:Q1 to 2009:Q1 at short and long horizons. In contrast with previous work, which reports “forecasts” using revised data, I construct a quarterly real-time dataset that incorporates only the information available to market participants when the forecasts were made. Using bootstrapped out-of-sample test statistics, the exchange rate model with Taylor rule fundamentals performs better at the one-quarter horizon and panel estimation is not able to improve its performance. The PPP model, however, forecasts better at the 16-quarter horizon and its performance increases in panel framework. The results are in accord with previous research on PPP and Taylor rule models.