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.


Doornik, J.A. (2018). `Accelerated estimation of switching algorithms: The cointegrated VAR Model and other applications’. Scandinavian Journal of Statistics, 45(2), pp.283-300.
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