ABSTRACT
This chapter shows why chaotic processes in the economic data series have proved problematic and certain nonlinear time series tools and techniques inspired by chaos have thrived. The idea that markets are inherently dynamically unstable has always played a minor role in studies of economic phenomena, and this has changed only marginally with the diffusion of chaos theory. Researchers in economics and finance have been interested in testing nonlinear dependence and chaos in economic models and data. The search for chaos in economics has gradually become less enthusiastic, as no empirical support for the presence of chaotic behaviors in economics has been found. The relevance of addressing chaos in economic models is associated with detecting the presence of chaoticmotion in economic data. The difficulty of using chaos theory in economics is a direct consequence of some problems related to the application of these techniques to economic data.
