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Accelerated Estimation of Switching Algorithms: The Cointegrated VAR Model and Other Applications
Author(s) -
Doornik Jurgen A.
Publication year - 2018
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/sjos.12311
Subject(s) - vector autoregression , mathematics , expectation–maximization algorithm , autoregressive model , algorithm , acceleration , maximization , simplicity , estimation , econometrics , maximum likelihood , mathematical optimization , statistics , philosophy , physics , epistemology , classical mechanics , management , economics
Restricted versions of the cointegrated vector autoregression are usually estimated using switching algorithms. These algorithms alternate between two sets of variables but can be slow to converge. Acceleration methods are proposed that combine simplicity and effectiveness. These methods also outperform existing proposals in some applications of the expectation–maximization method and parallel factor analysis.