In this paper the identification problem is considered for initial conditionsin a non-minimal state-space model that includes interpretable state variablesgenerated by non-stationary stochastic processes. In order to solve theidentification problem, structural restrictions are imposed on initial conditionsin a state-space model with redundant state variables. The correspondingrestricted maximum likelihood estimator of initial conditions is derived.The restricted estimator of initial conditions can be used in order tocompute uniquely identified realizations of interpretable latent variables. Theidentification problem is illustrated analytically using a simple structuraleconomic model.

This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach.

In this paper a semi-structural econometric model is implemented in order to estimate the natural rates of interest in two large economies of the Euro Area: Germany an Italy. The estimates suggest that after the financial crisis of 2007–2008 a decrease of the growth rate of potential output and the corresponding natural rate of interest was greater in Italy than in Germany which could have had important implications for the effectiveness of a common monetary policy. Unlike in other studies, it is found that the monetary policy stance was less expansionary in Italy as compared to Germany for the whole after-crisis period.

This paper proposes two nonlinear exact and simple state space models of a Zsource converter (ZSC) connected to an ac grid. A generic model of a ZSC accompanied with proper controllers are proposed and a dynamic model of the whole system is derived; as a result, based on a simple one, an equivalent block diagram of the current-controlled ZSC system is proposed. The ac small signal stability method is applied and the impact of controller parameters on network’s stability is discussed. Besides, overall system dynamic performance has been assessed in the event of perturbations. Time-domain simulations have been implemented in PSCAD/EMTDC to validate the accuracy of the models and effectiveness of the proposed controllers. The results of the exact model are compared with the response of the equations which are applied in MATLAB.