Nonlinear Phillips curves in the Euro Area and USA? Evidence from linear and neural network models

被引:4
|
作者
McNelis, PD [1 ]
机构
[1] Georgetown Univ, Dept Econ, Washington, DC 20057 USA
关键词
neural networks; Phillips curve; out-of-sample forecasting;
D O I
10.1109/CIFER.2003.1196254
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper applies neural network methodology to inflation forecasting in the Euro-area and the USA. Neural network methodology outperforms linear forecasting methods for the Euro Area at forecast horizons of one, three, and six month horizons, while the linear model is preferable for US data. The nonlinear estimation shows that unemployment is a significant predictor of inflation for the Euro Area. Neither model detects a significant effect of unemployment on inflation for the US data.
引用
收藏
页码:145 / 149
页数:5
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