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The Resource Cointegration, error correction, and the econometric analysis of nonstationary data, Anindya Banerjee [and others]
Cointegration, error correction, and the econometric analysis of nonstationary data, Anindya Banerjee [and others]
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The item Cointegration, error correction, and the econometric analysis of nonstationary data, Anindya Banerjee [and others] represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Cointegration, error correction, and the econometric analysis of nonstationary data, Anindya Banerjee [and others] represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 This book is wideranging in its account of literature on cointegration and the modelling of integrated processes (those which accumulate the effects of past shocks). Data series which display integrated behaviour are common in economics, although techniques appropriate to analyzing such data are relatively new, with few existing expositions of the literature. This book explores relationships among integrated data series and their use in dynamic econometric modelling. The concepts of cointegration and errorcorrection models are fundamental components of the modelling strategy. This area of time series econometrics has grown in importance over the past decade and is of interest to both econometric theorists and applied econometricians. By explaining the important concepts informally and presenting them formally, the book bridges the gap between purely descriptive and purely theoretical accounts of the literature. The work describes the asymptotic theory of integrated processes and uses the tools provided by this theory to develop the distributions of estimators and test statistics. It emphasizes practical modelling advice and the use of techniques for systems estimation. A knowledge of econometrics, statistics, and matrix algebra at the level of a finalyear undergraduate or firstyear undergraduate course in econometrics is sufficient for most of the book. Other mathematical tools are described as they occur.  Publisher description
 Language
 eng
 Extent
 xiii, 329 pages
 Contents

 Introduction and Overview  Equilibrium relationships and the long run  Stationarity and equilibrium relationships  Equilibrium and the specification of dynamic models  Estimation of longrun relationships and testing for orders of integration and cointegration  Preliminary concepts and definitions  Data representation and transformations  Examples: typical ARMA processes  Empirical time series: money, prices, output, and interest rates  Outline of later chapters  Appendix  Linear Transformations, Error Correction, and the Long Run in Dynamic Regression  Transformations of a simple model  The errorcorrection model  Bardsen and Bewley transformations  Equivalence of estimates from different transformations  Homogeneity and the ECM as a linear transformation of the ADL  Variances of estimates of longrun multipliers  Expectational variables and the interpretation of longrun solutions  Properties of Integrated Processes  Spurious regression  Trends and random walks  Some statistical features of integrated processes  Asymptotic theory for integrated processes  Using Wiener distribution theory  Nearintegrated processes  Testing for a Unit Root  Similar tests and exogenous regressors in the DGP  General dynamic models for the process of interest  Nonparametric tests for a unit root  Tests on more than one parameter  Further extensions  Asymptotic distributions of test statistics  Cointegration  Polynomial matrices  Integration and cointegration: formal definitions and theorems  Significance of alternative representations  Alternative representations of cointegrated variables: two examples  EngleGranger twostep procedure  Regression with Integrated Variables  Unbalanced regressions and orthogonality tests  Dynamic regressions  Functional forms and transformations  Appendix: Vector Brownian Motion  Cointegration in Individual Equations  Estimating a single cointegrating vector  Tests for cointegration in a single equation  Response surfaces for critical rabies  Finitesample biases in OLS estimates  Powers of singleequation cointegration tests  An empirical illustration  Fully modified estimation  A fully modified leastsquares estimator  Dynamic specification  Appendix: Covariance Matrices  Cointegration in Systems of Equations  Cointegration and error correction  Estimating cointegrating vectors in systems  Inference about the cointegration space  An empirical illustration  A second example of the Johansen maximum likelihood approach  Asymptotic distributions of estimators of cointegrating vectors in I(1) systems  Conclusion
 Isbn
 9780198287001
 Label
 Cointegration, error correction, and the econometric analysis of nonstationary data
 Title
 Cointegration, error correction, and the econometric analysis of nonstationary data
 Statement of responsibility
 Anindya Banerjee [and others]
 Language
 eng
 Summary
 This book is wideranging in its account of literature on cointegration and the modelling of integrated processes (those which accumulate the effects of past shocks). Data series which display integrated behaviour are common in economics, although techniques appropriate to analyzing such data are relatively new, with few existing expositions of the literature. This book explores relationships among integrated data series and their use in dynamic econometric modelling. The concepts of cointegration and errorcorrection models are fundamental components of the modelling strategy. This area of time series econometrics has grown in importance over the past decade and is of interest to both econometric theorists and applied econometricians. By explaining the important concepts informally and presenting them formally, the book bridges the gap between purely descriptive and purely theoretical accounts of the literature. The work describes the asymptotic theory of integrated processes and uses the tools provided by this theory to develop the distributions of estimators and test statistics. It emphasizes practical modelling advice and the use of techniques for systems estimation. A knowledge of econometrics, statistics, and matrix algebra at the level of a finalyear undergraduate or firstyear undergraduate course in econometrics is sufficient for most of the book. Other mathematical tools are described as they occur.  Publisher description
 Cataloging source
 DLC
 Illustrations
 illustrations
 Index
 index present
 LC call number
 HB141
 LC item number
 .C62 1993
 Literary form
 non fiction
 Nature of contents
 bibliography
 http://library.link/vocab/relatedWorkOrContributorName
 Banerjee, Anindya
 http://library.link/vocab/subjectName

 Econometric models
 Modèles économétriques
 Econometric models
 Econometrische modellen
 Séries chronologiques
 Économétrie
 Modèles économétriques
 Label
 Cointegration, error correction, and the econometric analysis of nonstationary data, Anindya Banerjee [and others]
 Bibliography note
 Includes bibliographical references (p. 311321) and indexes
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Introduction and Overview  Equilibrium relationships and the long run  Stationarity and equilibrium relationships  Equilibrium and the specification of dynamic models  Estimation of longrun relationships and testing for orders of integration and cointegration  Preliminary concepts and definitions  Data representation and transformations  Examples: typical ARMA processes  Empirical time series: money, prices, output, and interest rates  Outline of later chapters  Appendix  Linear Transformations, Error Correction, and the Long Run in Dynamic Regression  Transformations of a simple model  The errorcorrection model  Bardsen and Bewley transformations  Equivalence of estimates from different transformations  Homogeneity and the ECM as a linear transformation of the ADL  Variances of estimates of longrun multipliers  Expectational variables and the interpretation of longrun solutions  Properties of Integrated Processes  Spurious regression  Trends and random walks  Some statistical features of integrated processes  Asymptotic theory for integrated processes  Using Wiener distribution theory  Nearintegrated processes  Testing for a Unit Root  Similar tests and exogenous regressors in the DGP  General dynamic models for the process of interest  Nonparametric tests for a unit root  Tests on more than one parameter  Further extensions  Asymptotic distributions of test statistics  Cointegration  Polynomial matrices  Integration and cointegration: formal definitions and theorems  Significance of alternative representations  Alternative representations of cointegrated variables: two examples  EngleGranger twostep procedure  Regression with Integrated Variables  Unbalanced regressions and orthogonality tests  Dynamic regressions  Functional forms and transformations  Appendix: Vector Brownian Motion  Cointegration in Individual Equations  Estimating a single cointegrating vector  Tests for cointegration in a single equation  Response surfaces for critical rabies  Finitesample biases in OLS estimates  Powers of singleequation cointegration tests  An empirical illustration  Fully modified estimation  A fully modified leastsquares estimator  Dynamic specification  Appendix: Covariance Matrices  Cointegration in Systems of Equations  Cointegration and error correction  Estimating cointegrating vectors in systems  Inference about the cointegration space  An empirical illustration  A second example of the Johansen maximum likelihood approach  Asymptotic distributions of estimators of cointegrating vectors in I(1) systems  Conclusion
 Dimensions
 24 cm.
 Extent
 xiii, 329 pages
 Isbn
 9780198287001
 Lccn
 92027344
 Media category
 unmediated
 Media MARC source
 rdamedia
 Media type code

 n
 Other physical details
 illustrations
 System control number

 (OCoLC)26305706
 (OCoLC)ocm26305706
 Label
 Cointegration, error correction, and the econometric analysis of nonstationary data, Anindya Banerjee [and others]
 Bibliography note
 Includes bibliographical references (p. 311321) and indexes
 Carrier category
 volume
 Carrier category code

 nc
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Introduction and Overview  Equilibrium relationships and the long run  Stationarity and equilibrium relationships  Equilibrium and the specification of dynamic models  Estimation of longrun relationships and testing for orders of integration and cointegration  Preliminary concepts and definitions  Data representation and transformations  Examples: typical ARMA processes  Empirical time series: money, prices, output, and interest rates  Outline of later chapters  Appendix  Linear Transformations, Error Correction, and the Long Run in Dynamic Regression  Transformations of a simple model  The errorcorrection model  Bardsen and Bewley transformations  Equivalence of estimates from different transformations  Homogeneity and the ECM as a linear transformation of the ADL  Variances of estimates of longrun multipliers  Expectational variables and the interpretation of longrun solutions  Properties of Integrated Processes  Spurious regression  Trends and random walks  Some statistical features of integrated processes  Asymptotic theory for integrated processes  Using Wiener distribution theory  Nearintegrated processes  Testing for a Unit Root  Similar tests and exogenous regressors in the DGP  General dynamic models for the process of interest  Nonparametric tests for a unit root  Tests on more than one parameter  Further extensions  Asymptotic distributions of test statistics  Cointegration  Polynomial matrices  Integration and cointegration: formal definitions and theorems  Significance of alternative representations  Alternative representations of cointegrated variables: two examples  EngleGranger twostep procedure  Regression with Integrated Variables  Unbalanced regressions and orthogonality tests  Dynamic regressions  Functional forms and transformations  Appendix: Vector Brownian Motion  Cointegration in Individual Equations  Estimating a single cointegrating vector  Tests for cointegration in a single equation  Response surfaces for critical rabies  Finitesample biases in OLS estimates  Powers of singleequation cointegration tests  An empirical illustration  Fully modified estimation  A fully modified leastsquares estimator  Dynamic specification  Appendix: Covariance Matrices  Cointegration in Systems of Equations  Cointegration and error correction  Estimating cointegrating vectors in systems  Inference about the cointegration space  An empirical illustration  A second example of the Johansen maximum likelihood approach  Asymptotic distributions of estimators of cointegrating vectors in I(1) systems  Conclusion
 Dimensions
 24 cm.
 Extent
 xiii, 329 pages
 Isbn
 9780198287001
 Lccn
 92027344
 Media category
 unmediated
 Media MARC source
 rdamedia
 Media type code

 n
 Other physical details
 illustrations
 System control number

 (OCoLC)26305706
 (OCoLC)ocm26305706
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