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

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Release : 1993-05-27
Genre : Business & Economics
Kind : eBook
Book Rating : 919/5 ( reviews)

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Book Synopsis Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data by : Anindya Banerjee

Download or read book Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data written by Anindya Banerjee. This book was released on 1993-05-27. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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

Download Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data PDF Online Free

Author :
Release : 1993
Genre : Econometric models
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data by :

Download or read book Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data written by . This book was released on 1993. Available in PDF, EPUB and Kindle. Book excerpt:

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

Download Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data PDF Online Free

Author :
Release : 1993
Genre : Econometric models
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data by :

Download or read book Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data written by . This book was released on 1993. Available in PDF, EPUB and Kindle. Book excerpt:

The Econometric Analysis of Non-Stationary Spatial Panel Data

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Author :
Release : 2019-03-27
Genre : Business & Economics
Kind : eBook
Book Rating : 146/5 ( reviews)

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Book Synopsis The Econometric Analysis of Non-Stationary Spatial Panel Data by : Michael Beenstock

Download or read book The Econometric Analysis of Non-Stationary Spatial Panel Data written by Michael Beenstock. This book was released on 2019-03-27. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Author :
Release : 2019
Genre : Electronic books
Kind : eBook
Book Rating : 157/5 ( reviews)

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Book Synopsis The Econometric Analysis of Non-stationary Spatial Panel Data by : Michael Beenstock

Download or read book The Econometric Analysis of Non-stationary Spatial Panel Data written by Michael Beenstock. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: 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. .

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