This paper provides some test cases, called circuits, for the evaluation of Gaussian likelihood maximization algorithms of the cointegrated vector autoregressive model. Both I(1) and I(2) models are considered. The performance of algorithms is compared first in terms of effectiveness, defined as the ability to find the overall maximum. The next step is to compare their efficiency and reliability across experiments. The aim of the paper is to commence a collective learning project by the profession on the actual properties of algorithms for cointegrated vector autoregressive model estimation, in order to improve their quality and, as a consequence, also the reliability of empirical research.
Doornik, J.A., R. Mosconi & Parole, P. (2018). `Formula I(1) and I(2): Race Tracks for Likelihood Maximization Algorithms of I(1) and I(2) VAR Models’. Econometrics, 5(4), p.49.