This paper presents and exemplifies results developed for cointegration analysis with state space models by Bauer and … Wagner in a series of papers. Unit root processes, cointegration and polynomial cointegration are defined. Based upon these … employed for cointegration analysis. By means of detailing the cases most relevant for empirical applications, the I(1), MFI(1 …

estimate the covariance matrix of the latent states through a Kalman smoother and Expectation Maximization (KEM) algorithm …

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

these proposal densities are used in an independent Metropolis-Hastings algorithm. A particular feature of our approach is … that smoothed estimates of the states and the marginal likelihood are obtained directly as an output of the algorithm. Our …

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 …

really have unit roots in the data. This uncertainty is practical – for many macroeconomic and financial variables theory … models as well as examine the effects of erroneously assuming cointegration. It is shown that inconclusive theoretical … imposing cointegration can be more or less useful for different horizons. The problem of forecasting variables with trending …

This paper presents and exemplifies results developed for cointegration analysis with state space models by Bauer and … Wagner in a series of papers. Unit root processes, cointegration and polynomial cointegration are defined. Based upon these … employed for cointegration analysis. By means of detailing the cases most relevant for empirical applications, the I(1), MFI(1 …

computationally efficient filtering algorithm to estimate the nonlinear model. The algorithm is shown to be accurate in approximating …