Chaos detection in economics. Metric versus topological tools
AbstractIn their paper Frank F., Gencay R., and Stengos T., (1988) analyze the quarterly macroeconomic data from 1960 to 1988 for West Germany, Italy, Japan and England. The goal was to check for the presence of deterministic chaos. To ensure that the data analysed was stationary they used a first difference then tried a linear fit. Using a reasonable AR specification for each time series their conclusion was that time series showed different structures. In particular the non linear structure was present in the time series of Japan. Nevertheless the application of metric tools for detecting chaos (correlation dimension and Lyapunov exponent) didn’t show presence of chaos in any time series. Starting from this conclusion we applied a topological tool Visual Recurrence Analysis to these time series to compare the results. The purpose is to verify if the analysis performed by a topological tool could give results different from ones obtained using a metric tool.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 30928.
Date of creation: Oct 2010
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economics time series; chaos; and topological tool;
Find related papers by JEL classification:
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
- C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
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- Blake LeBaron, 1994. "Chaos and Nonlinear Forecastability in Economics and Finance," Finance 9411001, EconWPA.
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