Robustness of nonlinearity and chaos tests to measurement error, inference method, and sample size

William A. Barnett, Andrew Ronald Gallant, Melvin J. Hinich, Jochen A. Jungeilges, Daniel T. Kaplan, Mark J. Jensen

Research output: Contribution to journalArticle

52 Citations (Scopus)

Abstract

Interest has been growing in testing for nonlinearity and chaos in economic data, but much controversy has arisen about the available results. This paper explores the reasons for these empirical difficulties. We apply five tests for nonlinearity or chaos to various monetary aggregate data series. We find that the inferences vary across tests for the same data, and within tests for varying sample sizes and various methods of aggregation of the data. Robustness of inferences in this area of research seems to be low and may account for the controversies surrounding empirical claims of nonlinearity and chaos in economics.

Original languageEnglish (US)
Pages (from-to)301-320
Number of pages20
JournalJournal of Economic Behavior and Organization
Volume27
Issue number2
DOIs
StatePublished - Jan 1 1995

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Sample size
Chaos
Nonlinearity
Robustness
Measurement error
Inference
Economics
Economic data
Monetary aggregates
Aggregate data
Testing

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics
  • Organizational Behavior and Human Resource Management

Cite this

Barnett, William A. ; Gallant, Andrew Ronald ; Hinich, Melvin J. ; Jungeilges, Jochen A. ; Kaplan, Daniel T. ; Jensen, Mark J. / Robustness of nonlinearity and chaos tests to measurement error, inference method, and sample size. In: Journal of Economic Behavior and Organization. 1995 ; Vol. 27, No. 2. pp. 301-320.
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Robustness of nonlinearity and chaos tests to measurement error, inference method, and sample size. / Barnett, William A.; Gallant, Andrew Ronald; Hinich, Melvin J.; Jungeilges, Jochen A.; Kaplan, Daniel T.; Jensen, Mark J.

In: Journal of Economic Behavior and Organization, Vol. 27, No. 2, 01.01.1995, p. 301-320.

Research output: Contribution to journalArticle

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