ROBUSTNESS OF NONLINEARITY AND CHAOS TESTS TO MEASUREMENT ERROR, INFERENCE METHOD, AND SAMPLE-SIZE

被引：46

作者：

BARNETT, WA

GALLANT, AR

HINICH, MJ

JUNGEILGES, JA

KAPLAN, DT

JENSEN, MJ

机构：

[1] UNIV N CAROLINA, CHAPEL HILL, NC USA

[2] UNIV TEXAS, AUSTIN, TX 78712 USA

[3] UNIV OSNABRUCK, W-4500 OSNABRUCK, GERMANY

[4] MCGILL UNIV, MONTREAL, PQ, CANADA

来源：

JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION | 1995年 / 27卷 / 02期

基金：

英国医学研究理事会; 美国国家科学基金会;

关键词：

CHAOS; NONLINEARITY; ROBUSTNESS;

D O I：

10.1016/0167-2681(94)00082-P

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：301 / 320

页数：20

共 26 条

[1] DETERMINISTIC CHAOS AND FRACTAL ATTRACTORS AS TOOLS FOR NONPARAMETRIC DYNAMICAL ECONOMETRIC INFERENCE - WITH AN APPLICATION TO THE DIVISIA MONETARY AGGREGATES [J].