Find it at other libraries via WorldCat Limited preview. Bibliography Includes bibliographical references and index. Summary This monograph, written by a leading statistician working in econometrics, gives a detailed mathematical and statistical analysis of the cointegrated vector autoregressive model. The book is a self-contained presentation for graduate students and researchers with a good knowledge of multivariate regression analysis and likelihood methods.
The theoretical analysis is illustrated with the empirical analysis of two sets of economic data. This model had gained popularity because it can at the same time capture the short-run dynamic properties as well as the long-run equilibrium behaviour of many non-stationary time series. It also allows relevant economic questions to be formulated in a consistent statistical framework. Part I of the book is planned so that it can be used by those who want to apply the methods without going into too much detail about the probability theory.
The main emphasis is on the derivation of estimators and test statistics through a consistent use of the Guassian likelihood function. It is shown that many different models can be formulated within the framework of the autoregressive model and the interpretation of these models is discussed in detail.
In particular, models involving restrictions on the cointegration vectors and the adjustment coefficients are discussed, as well as the role of the constant and linear drift. In Part II, the asymptotic theory is given the slightly more general framework of stationary linear processes with i. Some useful mathematical tools are collected in Appendix A, and a brief summary of weak convergence in given in Appendix B. The book is intended to give a relatively self-contained presentation for graduate students and researchers with a good knowledge of multivariate regression analysis and likelihood methods.
The asymptotic theory requires some familiarity with the theory of weak convergence of stochastic processes. The theory is treated in detail with the purpose of giving the reader a working knowledge of the techniques involved. Many exercises are provided. Subjects Econometric models. Autoregression Statistics. Bibliographic information. Librarian view Catkey: More Filters. 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, … Expand. Highly Influenced.
View 9 excerpts, cites methods. Econometric Theory. We investigate the asymptotic and finite sample properties of a number of methods for estimating the cointegration rank in integrated vector autoregressive systems of unknown autoregressive order … Expand. View 20 excerpts, cites background and methods.
Adjustment coefficients and exact rational expectations in cointegrated vector autoregressive models. In cointegrated vector autoregressive models exact linear rational expectation relations can imply restrictions on the adjustment parameters. We show how such restrictions can be tested, in … Expand. View 7 excerpts, cites methods and background. The forward search interactive outlier detection in cointegrated VAR analysis. Mathematics, Computer Science. Data Anal. View 2 excerpts, cites background.
It is well known that inference on the cointegrating relations in a vector autoregression CVAR is difficult in the presence of a near unit root. The test for a given cointegration vector can have … Expand. We address the issue of parameter dimensionality reduction in Vector Autoregressive models VARs for many variables by imposing specific reduced rank restrictions on the coefficient matrices that … Expand. Long-run restrictions have been used extensively for identifying structural shocks in vector autoregressive VAR analysis.
Such restrictions are typically just-identifying but can be checked by … Expand. View 6 excerpts, cites background and methods.
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