Recurrence analysis techniques for non-stationary and non-linear data
Philip Kostov and
Additional contact information
John Lingard: University of Newcastle
Microeconomics from University Library of Munich, Germany
When 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.
JEL-codes: C22 C40 (search for similar items in EconPapers)
Pages: 22 pages
New Economics Papers: this item is included in nep-ets
Note: Type of Document - pdf; pages: 22
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpmi:0409003
Access Statistics for this paper
More papers in Microeconomics from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ().