Developments in the Nonlinear Analysis of Economic Series
综述了经济序列非线性分析的方法，讨论了区分确定性混沌与随机噪声的可能性，并指出经济数据中存在非线性但无混沌证据，同时介绍了基于神经网络的非线性检验及长记忆的非线性协整定义。
Various aspects of the analysis of nonlinearities are surveyed in this paper. A possibility of distinguishing between a (low-dimensional) deterministic chaotic process and a white noise stochastic process using estimates of the correlation dimension is discussed. It is concluded that there is no evidence of chaos--as opposed to nonlinearity--in the economic data. The modes of testing for nonlinearity are briefly surveyed, with particular attention paid to a new test based on a neural network specification. It is found that aggregation can reduce nonlinearity and a definition of long memory is proposed that suggests a nonlinear generalization of cointegration. Copyright 1991 by The editors of the Scandinavian Journal of Economics.