We derive a closed-form expression for the posterior probability of Granger noncausality in a gaussian vector autoregression with a conjugate prior. We also express in closed form the posterior probability of Granger causal priority, a more general relation that accounts for indirect effects between variables and therefore is suitable in a multivariate context. One can use these results to answer the classic question, ?Is variable z relevant for variable x?? and to choose variables for a vector autoregression.
%0 Journal Article
%1 Jarocinski2016Granger
%A Jarociński, Marek
%A Maćkowiak, Bartosz
%D 2016
%I MIT Press
%J The Review of Economics and Statistics
%K causality, time-series, vector-autoregression econometrics
%N 2
%P 319--329
%R 10.1162/rest\_a\_00601
%T Granger Causal Priority and Choice of Variables in Vector Autoregressions
%U http://dx.doi.org/10.1162/rest\_a\_00601
%V 99
%X We derive a closed-form expression for the posterior probability of Granger noncausality in a gaussian vector autoregression with a conjugate prior. We also express in closed form the posterior probability of Granger causal priority, a more general relation that accounts for indirect effects between variables and therefore is suitable in a multivariate context. One can use these results to answer the classic question, ?Is variable z relevant for variable x?? and to choose variables for a vector autoregression.
@article{Jarocinski2016Granger,
abstract = {{We derive a closed-form expression for the posterior probability of Granger noncausality in a gaussian vector autoregression with a conjugate prior. We also express in closed form the posterior probability of Granger causal priority, a more general relation that accounts for indirect effects between variables and therefore is suitable in a multivariate context. One can use these results to answer the classic question, ?Is variable z relevant for variable x?? and to choose variables for a vector autoregression.}},
added-at = {2019-06-10T14:53:09.000+0200},
author = {Jaroci\'{n}ski, Marek and Ma\'{c}kowiak, Bartosz},
biburl = {https://www.bibsonomy.org/bibtex/2a8f2f578df2cf612dd83fa1d5dc770da/nonancourt},
citeulike-article-id = {14470885},
citeulike-linkout-0 = {http://dx.doi.org/10.1162/rest\_a\_00601},
citeulike-linkout-1 = {http://www.mitpressjournals.org/doi/abs/10.1162/REST\_a\_00601},
day = 23,
doi = {10.1162/rest\_a\_00601},
interhash = {0e74af11ca8ead622464ddd95eb104b4},
intrahash = {a8f2f578df2cf612dd83fa1d5dc770da},
journal = {The Review of Economics and Statistics},
keywords = {causality, time-series, vector-autoregression econometrics},
month = mar,
number = 2,
pages = {319--329},
posted-at = {2017-11-03 17:50:09},
priority = {2},
publisher = {MIT Press},
timestamp = {2019-08-01T16:18:55.000+0200},
title = {{Granger Causal Priority and Choice of Variables in Vector Autoregressions}},
url = {http://dx.doi.org/10.1162/rest\_a\_00601},
volume = 99,
year = 2016
}