A non-parametric approach to non-linear causality testing

被引：42

作者：

Bell, D

Kay, J

Malley, J

机构：

[1] UNIV GLASGOW, DEPT STAT, GLASGOW G12 8QW, LANARK, SCOTLAND

[2] UNIV STIRLING, DEPT ECON, STIRLING FK9 4LA, SCOTLAND

来源：

ECONOMICS LETTERS | 1996年 / 51卷 / 01期

关键词：

non-linear Granger causality; non-parametric estimation;

D O I：

10.1016/0165-1765(95)00791-1

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

In this paper we propose a new procedure for causality testing using non-parametric additive models. Our results suggest that the major advantage of our method is that it can be applied if the underlying data generation process is either linear or non-linear.

引用

页码：7 / 18

页数：12

共 12 条

[1]

Baek E., 1992, Iowa State University and University of Wisconsin at Madison Working Paper, P137

[2]

BELL DNF, 1994, UNPUB NONPARAMETRIC

[3]

BUJA A, 1989, ANN STAT, V17, P453, DOI 10.1214/aos/1176347115

[4]

Chambers J.M., 1991, Statistical Models in S