This paper proposes a class of partial cointegrated models allowing for structural breaks in the deterministic terms. Moving-average representations of the models are given. It is then shown that, under the assumption of martingale difference innovations, the limit distributions of partial...

This article extends the Factor-Augmented Vector Autoregression Model (FAVAR) to mixed-frequency and incomplete panel data. Within the scope of a fully parametric two-step approach, the alternating application of two expectation-maximization algorithms jointly estimates model parameters and...

We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation...

This paper investigates if the impact of uncertainty shocks on the U.K. economy has changed over time. To this end, we propose an extended time-varying VAR model that simultaneously allows the estimation of a measure of uncertainty and its time-varying impact on key macroeconomic and financial...

It is well known that in a vector autoregressive (VAR) model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance matrix of the innovations. This note shows that...

The relation between causal structure and cointegration and long-run weak exogeneity is explored using some ideas drawn from the literature on graphical causal modeling. It is assumed that the fundamental source of trending behavior is transmitted from exogenous (and typically latent) trending...

We use a cointegrated structural vector autoregressive model to investigate the relation between monetary policy in the euro area and the stock market. Since there may be an instantaneous causal relation, we consider long-run identifying restrictions for the structural shocks and also used...

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...

This survey paper discusses the Cointegrated Vector AutoRegressive (CVAR) methodology and how it has evolved over the past 30 years. It describes major steps in the econometric development, discusses problems to be solved when confronting theory with the data, and, as a solution, proposes a...

Likelihood ratio tests of over-identifying restrictions on the common trends loading matrices in I(2) VAR systems are discussed. It is shown how hypotheses on the common trends loading matrices can be translated into hypotheses on the cointegration parameters. Algorithms for (constrained)...