The causality proposed by Granger (1969) and several tests for it are often used in economic science to assess relationships among more than two factors of interest. However, the Granger causality presumes linearity and has limitation to analyze the relationship of \u22nonlinear\u22 factors. In this paper we extend the Granger causality to nonlinear relationships and propose methods for analysis of data by the causality; the efficiency of the methods is also investigated
This paper proposes an extension of the Granger (1969) causality definition to panel data models with...
Abstract. Granger causality (GC) is one of the most popular measures to re-veal causality influence ...
Granger-causality is a popular definition of causality that permits a statistical test to determine ...
Granger causality is a statistical concept of causality that is based on prediction. According to Gr...
A straightforward nonlinear extension of Grangers concept of causality in the kernel framework is s...
A straightforward nonlinear extension of Grangers concept of causality in the kernel framework is s...
A straightforward nonlinear extension of Granger’s concept of causality in the kernel framework is s...
Identifying causal relations among simultaneously acquired signals is an important problem in multiv...
Identifying causal relations among simultaneously acquired signals is an important problem in multiv...
Identifying causal relations among simultaneously acquired signals is an important problem in multiv...
An increasing number of recent articles applying powerful tests for non-linear causality have fuelle...
The Granger causality concept is extensively used in econometrics and several works have applied the...
The Granger causality concept is extensively used in econometrics and several works have applied the...
The Granger causality concept is extensively used in econometrics and several works have applied the...
An increasing number of recent articles applying powerful tests for non-linear causality have fuelle...
This paper proposes an extension of the Granger (1969) causality definition to panel data models with...
Abstract. Granger causality (GC) is one of the most popular measures to re-veal causality influence ...
Granger-causality is a popular definition of causality that permits a statistical test to determine ...
Granger causality is a statistical concept of causality that is based on prediction. According to Gr...
A straightforward nonlinear extension of Grangers concept of causality in the kernel framework is s...
A straightforward nonlinear extension of Grangers concept of causality in the kernel framework is s...
A straightforward nonlinear extension of Granger’s concept of causality in the kernel framework is s...
Identifying causal relations among simultaneously acquired signals is an important problem in multiv...
Identifying causal relations among simultaneously acquired signals is an important problem in multiv...
Identifying causal relations among simultaneously acquired signals is an important problem in multiv...
An increasing number of recent articles applying powerful tests for non-linear causality have fuelle...
The Granger causality concept is extensively used in econometrics and several works have applied the...
The Granger causality concept is extensively used in econometrics and several works have applied the...
The Granger causality concept is extensively used in econometrics and several works have applied the...
An increasing number of recent articles applying powerful tests for non-linear causality have fuelle...
This paper proposes an extension of the Granger (1969) causality definition to panel data models with...
Abstract. Granger causality (GC) is one of the most popular measures to re-veal causality influence ...
Granger-causality is a popular definition of causality that permits a statistical test to determine ...