Combination forecasts of output growth in a seven-country data set

被引:643
作者
Stock, JH [1 ]
Watson, MW
机构
[1] Harvard Univ, Dept Econ, Littauer Ctr, Cambridge, MA 02138 USA
[2] Natl Bur Econ Res, Cambridge, MA 02138 USA
[3] Princeton Univ, Woodrow Wilson Sch, Princeton, NJ 08544 USA
[4] Princeton Univ, Dept Econ, Princeton, NJ 08544 USA
关键词
macroeconomic forecasting; high-dimensional forecasting; time-varying parameters; forecast pooling;
D O I
10.1002/for.928
中图分类号
F [经济];
学科分类号
02 ;
摘要
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 amoregressive 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. Copyright (C) 2004 John Wiley Sons, Ltd.
引用
收藏
页码:405 / 430
页数:26
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