Combination Forecasts of Output Growth in a Seven-Country Data Set

This paper uses forecast combination methods to forecast output growth in a
seven-country quarterly economic data set covering 1959 – 1999, with up to 73 predictors
per country. Although the forecasts based on individual predictors are unstable over time
and across countries, and on average perform worse than an autoregressive benchmark,
the combination forecasts often improve upon autoregressive forecasts. Despite the
unstable performance of the constituent forecasts, the most successful combination
forecasts, like the mean, are the least sensitive to the recent performance of the individual
forecasts. While consistent with other evidence on the success of simple combination
forecasts, this finding is difficult to explain using the theory of combination forecasting in
a stationary environment.