Assessing the predictive power of financial spreads in the euro area: does parameters instability matter?

In the empirical literature there is wide consensus that financial spreads cannot constitute a broadly based assessment on future output growth and inflation because the bivariate estimated regressions are not stable over time and lead to relatively poor out-of-sample forecasting performance (e.g. J Econ Liter 41:788–829, 2003). This conclusion arised for the USA, as well as for several European countries. In this paper we check whether the marginal predictive content of some financial spreads (the slope of the yield curve, the reverse yield gap and the credit spread) for macroeconomic forecasting in the euro area can be recovered using techniques taking into account potential parameters instability. We set up a quarterly Bayesian vector autoregression model with time-varying coefficients, comprising both target variables, as well as other monetary policy indicators, to serve as a benchmark. Then, the properties of the spreads as leading indicators are assessed by augmenting this benchmark BVAR with the spreads, one at a time. We find time variation of the coefficients to be a relevant issue in our model, especially for forecasting output growth, but financial spreads continue to have no or negligible marginal predictive content for both output growth and inflation. Overall, our results confirm that there is no ready-to-use financial spread that can replace an encompassing multivariate model for the prediction of target variables in the euro area.