Journal of Economic Behavior and Organization, Vol. 27 (1995) 301-320

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

William A. Barnetta,*, A. Ronald Gallantb,
Melvin J. Hinichc, Jochen A. Jungeilgesd, Daniel T. Kaplane,
Mark J. Jensena

aWashington University in St. Louis, St. Louis, MO 63130, USA
bUniversity of North Carolina at Chapel Hill, Chapel Hill, USA
cUniversity of Texas at Austin, Austin, USA
dUniversity of Osnabrück, Osnabrück, Germany
eMcGill University, Montreal, Canada

Received 1 September 1992; revised 1 August 1994


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.

JEL classification: C22; C14

Keywords: Chaos; Nonlinearity; Robustness