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Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data

Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data
Author: Anindya Banerjee
Publisher: Oxford University Press
Total Pages: 344
Release: 1993-05-27
Genre: Business & Economics
ISBN: 0191638919

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This book provides a wide-ranging account of the literature on co-integration 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 analysing such data are of recent origin and there are few existing expositions of the literature. This book focuses on the exploration of relationships among integrated data series and the exploitation of these relationships in dynamic econometric modelling. The concepts of co-integration and error-correction 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 econometric theorists and applied econometricians alike. By explaining the important concepts informally, but also presenting them formally, the book bridges the gap between purely descriptive and purely theoretical accounts of the literature. The asymptotic theory of integrated processes is described and the tools provided by this theory are used to develop the distributions of estimators and test statistics. Practical modelling advice, and the use of techniques for systems estimation, are also emphasized. A knowledge of econometrics, statistics, and matrix algebra at the level of a final-year undergraduate or first-year undergraduate course in econometrics is sufficient for most of the book. Other mathematical tools are described as they occur.


The Econometric Analysis of Non-Stationary Spatial Panel Data

The Econometric Analysis of Non-Stationary Spatial Panel Data
Author: Michael Beenstock
Publisher: Springer
Total Pages: 280
Release: 2019-03-27
Genre: Business & Economics
ISBN: 3030036146

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This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.


The Econometric Analysis of Non-stationary Spatial Panel Data

The Econometric Analysis of Non-stationary Spatial Panel Data
Author: Michael Beenstock
Publisher:
Total Pages: 275
Release: 2019
Genre: Electronic books
ISBN: 9783030036157

Download The Econometric Analysis of Non-stationary Spatial Panel Data Book in PDF, ePub and Kindle

This monograph deals with spatially dependent non-stationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial non-stationarity in spatial cross-section data, and a full exposition of non stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel. .


Cointegration For The Applied Economist

Cointegration For The Applied Economist
Author: B Bhaskara Rao (Ed.)
Publisher: Allied Publishers
Total Pages: 254
Release: 1997
Genre:
ISBN: 9788170237211

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Using R for Principles of Econometrics

Using R for Principles of Econometrics
Author: Constantin Colonescu
Publisher: Lulu.com
Total Pages: 278
Release: 2017-12-28
Genre: Business & Economics
ISBN: 1387473611

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This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.


Analysis of Integrated and Cointegrated Time Series with R

Analysis of Integrated and Cointegrated Time Series with R
Author: Bernhard Pfaff
Publisher: Springer Science & Business Media
Total Pages: 193
Release: 2008-09-03
Genre: Business & Economics
ISBN: 0387759670

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This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.


Modelling Non-Stationary Economic Time Series

Modelling Non-Stationary Economic Time Series
Author: S. Burke
Publisher: Springer
Total Pages: 253
Release: 2005-06-14
Genre: Business & Economics
ISBN: 0230005780

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Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of econometrics to real world problems. This book provides direction and guidance to the now vast literature facing students and graduate economists. Econometric theory is linked to practical issues such as how to identify equilibrium relationships, how to deal with structural breaks associated with regime changes and what to do when variables are of different orders of integration.


Macroeconometrics and Time Series Analysis

Macroeconometrics and Time Series Analysis
Author: Steven Durlauf
Publisher: Springer
Total Pages: 417
Release: 2016-04-30
Genre: Business & Economics
ISBN: 0230280838

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Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.