Long-term interest rate predictability: Exploring the usefulness of survey forecasts of growth and inflation

Abstract

This study focuses on the consensus forecasts from the Survey of Professional Forecasters (SPF) for 1993-2017. These include the SPF forecasts of US 10-year Treasury rate (TBR), Moody's Aaa corporate bond rate (Aaa), CPI inflation, and real GDP growth. We show that both SPF and random walk forecasts of TBR and Aaa generally fail to be orthogonal to changes in SPF inflation (but not growth) forecasts. Such findings point to the potential usefulness of SPF inflation forecasts in improving the accuracy of SPF and random walk forecasts of TBR and Aaa. Further results indicate that changes in SPF inflation forecasts accurately predict directional change in both TBR and Aaa at longer forecast horizons for 2008-2017 (but not for 1993-2007). These latter results raise the question of whether long-term interest rates have become easier to predict, which deserves subsequent research.

Evaluating survey-based forecasts of interest rates and macroeconomic variables

“…Our empirical findings are generally consistent with existing empirical literature regarding short-term rates predictability (Chun 2012) but differ from existing evidence on long-term interest rates (Filiz et al , 2019) as we show that survey-based forecasts are also efficient in predicting long-term interest rates in the long run. Third, regarding the other key macroeconomic variables under examination, we provide evidence that survey-based forecasts are among the most accurate predictors of key macroeconomic variables, in line with the existing literature (Baghestani, 2019).…”

“…Long-term interest rate, in theory, follow a near random walk and thus, its best forecast is a naive estimated based on the most recent rate known at the time of the forecast (Pesando, 1979). Consistent with the theory, existing empirical evidence on the accuracy of survey forecasts of long-term interest rates have shown that such forecasts fail to beat the random walk benchmark (Baghestani, 2006, 2009a, 2018, 2019; Baghestani et al , 2015; Cho, 1996; Greer, 1999, 2003; Kolb and Stekler, 1996; Mitchell and Pearce, 2007; Stark, 2010). As for survey forecasts of short-term interest rates, existing findings are mixed (Altavilla and Giannone, 2017; Baghestani, 2010; Baghestani et al , 2015; Chun, 2012) as empirical evidence generally suggests that survey participants perform the best for short-horizon forecasts of short to medium term yields.…”

“…The particular survey asks approximately 50 economic forecasters and financial professionals every month for their forecasts of interest rates and certain key macroeconomic variables for the current quarter and for one- to five-quarters ahead. Although the literature examining analysts' forecasts of macroeconomic indicators is not as deep as the literature for corporate earnings (Broughton and Lobo, 2018), the performance of professional survey-based forecasts has been the subject of a number of studies (indicatively see, Filiz et al (2019); Baghestani, 2019; Kunze, 2020 and the references therein). Existing research has not provided conclusive evidence, and this may be attributed to research design choices.…”

Predicting United Arab Emirates' real effective exchange rates using oil prices

“…Diebold and Lopez (), among others, note that a random walk forecast is not necessarily a naïve forecast for many economic and financial indicators. This is especially so for both exchange rates (Baghestani ; Rossi ) and long‐term interest rates (Baghestani ; ).…”