Asymmetries in the Conditional Mean Dynamics of Real GNP: Robust Evidence
研究美国实际GNP条件均值中的非对称性，通过控制异常值、条件异方差和长记忆性后，发现统计显著的非线性特征仍然存在。
We investigate asymmetries in the conditional mean dynamics of U.S. GNP. Because the statistical evidence on nonlinearities in the conditional mean could be influenced by the presence of outliers or by a failure to model conditional heter oske dasticity, we explicitly account for outliers by assuming that the innovations are drawn from the stable family, and model time-varying volatility by a GARCH(1, 1) process. We also allow for the possibility of long memory in the series with fractional differencing. Our results indicate statistically significant nonlinearities in the conditional mean that persist even after accounting for these features in the data. © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology