The natural rate of interest is a key benchmark steady-state rate of return that is used by central banks to measure the stance of monetary policy. Asset managers rely on estimates of the natural rate to make long-term investment decisions for their clients. This paper outlines a number of important econometric issues in the estimation of the natural rate of interest from a widely used structural model. Using a simulation experiment as well as empirical data for the U.S., I show that one of the key parameters of the structural model is overestimated and leads to a spuriously amplified downward trend in the natural rate. The paper shows how the overestimation can be remedied and provides alternative estimates of the natural rate. Various other issues are discussed that policy makers should be aware of when utilizing this model’s natural rate estimates for policy decision.

We use a dynamic model averaging (DMA) approach to construct forecasts of individual equity returns for a large cross-section of stocks contained in the SP500, FTSE100, DAX30, CAC40 and SPX30 headline indices, taking value, momentum, and quality factors as predictor variables. Fixing the set of 'forgetting factors' in the DMA prediction framework, we show that highly significant return forecasts relative to the historic average benchmark are obtained for 173 (281) individual equities at the 1% (5%) level, from a total of 895 stocks. These statistical forecast improvements also translate into considerable economic gains, producing out-of-sample R-2 values above 5% (10%) for 283 (166) of the 895 individual stocks. Equally weighted long only portfolios constructed from a ranking of the best 25% forecasts in each headline index can generate sizable returns in excess of a passive investment strategy in that index itself, even when transaction costs and risk taking are accounted for.