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.
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