Nonlinear phillips curves in the Euro area and USA? Evidence from linear and neural network models

摘要

The 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.