of Johansen (2008, 2009). We propose a 4-step estimation procedure that is based on the switching algorithm employed in …

and the cointegration rank exactly in the same way as in the standard I(1) cointegration framework of Johansen (1995) and … procedure for this model that is based on the switching algorithm employed in Carlini and Mosconi (2014), together with the GLS … and Velasco (for cointegration strength >0.5) and Avarucci and Velasco (for cointegration strength <0.5). Therefore our …

characteristics of the filter for signal extraction, trend prediction and cointegration estimation for univariate and bivariate series …

-known residual-based test for cointegration in linear models by Engle and Granger (1987) and obtain its nonlinear analogue. We derive … cointegration, whereas the linear-based tests fail to do so. Further analysis of impulse response functions of error correction …

the maximum likelihood (ML) estimators of the matrix of the cointegration relations, the degree of fractional … cointegration, the matrix of the speed of adjustment to the equilibrium parameters and the variance-covariance matrix of the error … consistent estimates and provide their asymptotic distributions. The cointegration matrix is asymptotically mixed normal …

applications. As a result, the asymptotic theory of maximum likelihood and quasi-maximum likelihood estimators may be compromised … and misspecified models. The practical relevance of the theory is highlighted in a set of empirical examples. We further …