Multivariate subset autoregressive modelling with zero constraints for detecting ‘overall causality’ |
| |
Authors: | JHW Penm RD Terrell |
| |
Institution: | The Australian National University, Canberra, A.C.T. 2601, Australia |
| |
Abstract: | The necessary and sufficient condition to test for ‘overall causality’, i.e., the presence of Granger- causality and instantaneous causal relations, in a bivariate and trivariate autoregressive model with recursive form is discussed. It is argued that the conventional AR model (the reduced form AR) is a more straightforward and effective means of testing for ‘overall causality’. To detect instanta- neous causality it is proposed to select the best subset system in a residual regression system in conjunction with model selection criteria. The Canadian money-income-bank rate system is re-examined in this way and by using a previously proposed algorithm we identify the optimum multivariate subset AR with constraints to detect whether there is ‘overall causality’ in that system. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|