Suchergebnisse

This monograph deals with the so-called Structural Vector Autoregressive (SVAR) approach, the most recent development of vector autoregressive econometric modeling. Three different types of models, which encompass all the models used so far in the SVAR applied literature, are analysed using a full-information likelihood-based set up and linear constraints of the more general form. Identification analysis andestimation of these models are carried out using compact formulae coming from an application of some new tools in matrix differential analysis. Using approximation theorems of mathematical statistics, the asymptotic distributions of impulse response and forecast error variance decomposition functions are analytically derived, avoiding the use of bootstrapping and Monte Carlo integration techniques. The monograph also contains a qualitative discussion of the results of an exercise on Italian data and two rats procedures implementing identification, estimation and simulation phases according to the proposed approach

This book provides a new approach to the identification and the estimation of structural VAR models. The role of deterministic variables and the connection with the concept of cointegration is discussed at length. The book also provides criteria to select among alternative structures. In addition, the asymptotic distributions of the structural estimates of impulse response functions and forecast error variance decomposition coefficients are obtained and used to construct asymptotically based confidence intervals around the maximum likelihood estimates. Moreover, the book contains a critical evaluation of the problem of non-fundamental representations and of their relevance on the interpretability of the results of structural VAR analysis. Finally, the book contains applied examples