Recurrence analysis techniques for non-stationary and non-linear data
AbstractWhen analysing food consumption data a number of problems arise when one departs from the comparative statics of conventional demand theory. Two of these properties, non-linearity and non-stationarity present a major challenge for econometric modelling. A new method for time series analysis, namely recurrence analysis, is outlined which allows for robust analysis of data that can not be satisfactorily handled with established econometric methods. The method is explained and applied to specific food consumption data. General implications for empirical modelling of similar data are inferred.
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Bibliographic InfoPaper provided by EconWPA in its series Microeconomics with number 0409003.
Length: 22 pages
Date of creation: 15 Sep 2004
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Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
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