TESTING FOR CINTEGRATION WHEN SOME OF THE COINTEGRATING VECTORS ARE KNOWN PDF Download
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Author: Michael T.K. HORVATH
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Michael T.K. HORVATH
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Mark W. Watson
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Many economic models imply that ratios, simple differences, or spreads' of variables are I(0). In these models, cointegrating vectors are composed of 1's, 0's and -1's, and contain no unknown parameters. In this paper we develop tests for cointegration that can be applied when some of the cointegrating vectors are known under the null or under the alternative hypotheses. These tests are constructed in a vector error correction model (VECM) and are motivated as Wald tests in the version of this Gaussian model. When all of the cointegrating vectors are known under the alternative, the tests correspond to the standard Wald tests for the inclusion of error correction terms in the VAR. Modifications of this basic test are developed when a subset of the cointegrating vectors contains unknown parameters. The asymptotic null distribution of the statistics are derived, critical values are determined, and the local power properties of the test are studied. Finally, the test is applied to data on foreign exchange future and spot prices to test the stability of forward-spot premium
Author: Michael T. K. Horvath
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 56
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Author: Erik Hjalmarsson
Publisher: International Monetary Fund
ISBN:
Category : Business & Economics
Languages : en
Pages : 28
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We investigate the properties of Johansen's (1988, 1991) maximum eigenvalue and trace tests for cointegration under the empirically relevant situation of near-integrated variables. Using Monte Carlo techniques, we show that in a system with near-integrated variables, the probability of reaching an erroneous conclusion regarding the cointegrating rank of the system is generally substantially higher than the nominal size. The risk of concluding that completely unrelated series are cointegrated is therefore non-negligible. The spurious rejection rate can be reduced by performing additional tests of restrictions on the cointegrating vector(s), although it is still substantially larger than the nominal size.
Author: Anindya Banerjee
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 56
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Author: G. S. Maddala
Publisher: Cambridge University Press
ISBN: 9780521587822
Category : Business & Economics
Languages : en
Pages : 528
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Book Description
A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Author: Peter Reinhard Hansen
Publisher: Oxford University Press, USA
ISBN: 9780198776086
Category : Business & Economics
Languages : en
Pages : 178
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Book Description
Aimed at graduates and researchers in economics and econometrics, this is a comprehesive exposition of Soren Johansen's remarkable contribution to the theory of cointegration analysis.
Author: Jeff B. Cromwell
Publisher: SAGE
ISBN: 9780803954403
Category : Social sciences
Languages : en
Pages : 116
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Book Description
Which time series test should researchers choose to best describe the interactions among a set of time series variables? Providing guidelines for identifying the appropriate multivariate time series model to use, this book explores the nature and application of these increasingly complex tests.
Author: Jeroen J. M. Kremers
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 44
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Book Description
Author: Katarina Juselius
Publisher: OUP Oxford
ISBN: 0191622966
Category : Business & Economics
Languages : en
Pages : 478
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Book Description
This valuable text provides a comprehensive introduction to VAR modelling and how it can be applied. In particular, the author focuses on the properties of the Cointegrated VAR model and its implications for macroeconomic inference when data are non-stationary. The text provides a number of insights into the links between statistical econometric modelling and economic theory and gives a thorough treatment of identification of the long-run and short-run structure as well as of the common stochastic trends and the impulse response functions, providing in each case illustrations of applicability. This book presents the main ingredients of the Copenhagen School of Time-Series Econometrics in a transparent and coherent framework. The distinguishing feature of this school is that econometric theory and applications have been developed in close cooperation. The guiding principle is that good econometric work should take econometrics, institutions, and economics seriously. The author uses a single data set throughout most of the book to guide the reader through the econometric theory while also revealing the full implications for the underlying economic model. To test ensure full understanding the book concludes with the introduction of two new data sets to combine readers understanding of econometric theory and economic models, with economic reality.
