the no-change forecast. Our key finding is that substantial reductions in the mean-squared prediction error (MSPE) of … greater reductions in MSPEs are possible by constructing a pooled forecast that assigns equal weight to five of the most …

This paper explores a range of different forecast methods for Brent oil prices and analyses their performance relative … across forecast horizons. To address this instability, we propose a forecast combination for predicting quarterly real Brent … generates forecasts whose performance is robust over time. The improvements in forecast accuracy and stability are noticeable in …

has implications for the estimation of economic models of energy-intensive durables, for oil price forecasting, and for …

quite rapidly with the forecast horizon, and (b) AugGVAR forecasts do as well as other data-rich forecasting techniques for … short horizons, and tend to do better for longer forecast horizons. …

realized sales, we document that only major forecast errors are predictable and display autocorrelation. This result is a … forecast errors are neither predictable nor autocorrelated. To arrive at this result, we develop a novel methodology to … environments where information processing is more costly. This results in major forecast errors that are predictable and …

-switching models, and forecast combination to predict the dynamics in the S&P 500. First, we aggregate the weekly information of 115 …

growth, inflation, and unemployment over 1985-2020, we find pervasive overreaction to news at most of the monthly forecast …

We examine forecast accuracy and efficiency of the Social Security Administration's projections for cost rate, trust …