Pdf Cointegration Overview And Development Springer
This article presents a survey of the analysis of cointegration using the vector autoregressive model. After a few illustrative economic examples, the three model based approaches to the analysis of cointegration are discussed.The vector autoregressive model is defined and the moving average representation of the solution, the Granger representation,... Next the interpretation of the model and its parameters and likelihood based inference follows using reduced rank regression. The asymptotic analysis includes the distribution of the Gaussian maximum likelihood estimators, the rank test, and test for hypotheses on the cointegrating vectors. Finally, some applications and extensions of the basic model are mentioned and the survey concludes with some open problems. This is a preview of subscription content, log in via an institution to check access.
Tax calculation will be finalised at checkout Unable to display preview. Download preview PDF. Unable to display preview. Download preview PDF. This article presents a survey of the analysis of cointegration using the vector autoregressive model.
After a few illustrative economic examples, the three model based approaches to the analysis of cointegration are discussed.The vector autoregressive model is defined and the moving average representation of the solution, the Granger representation,... Next the interpretation of the model and its parameters and likelihood based inference follows using reduced rank regression. The asymptotic analysis includes the distribution of the Gaussian maximum likelihood estimators, the rank test, and test for hypotheses on the cointegrating vectors. Finally, some applications and extensions of the basic model are mentioned and the survey concludes with some open problems. This is a preview of subscription content, log in via an institution to check access. Tax calculation will be finalised at checkout
Unable to display preview. Download preview PDF. Unable to display preview. Download preview PDF. The concept of co-integration posits that the linear combination of two or more nonstationary time series can be stationary if they are co-integrated (Granger 1981). Co-integration and error correction models are largely applied to solve the spurious regression problem resulting from the inclusion of nonstationary variables in a regression model.
Two main approaches to modeling co-integration are single-equation residual-based and system-based analyses. One precondition for the above tests is that all variables in the co-integration regression should be integrated with the same order. When different orders of integration are identified, alternative tests such as the autoregressive distributed lag bounds test can be applied (Pesaran et al. 2001). Since the mid-1990s, a considerable number of tourism researchers have adopted the co-integration method to address a variety of topics related to tourism demand modeling and forecasting. Numerous efforts have been undertaken to empirically...
This is a preview of subscription content, log in via an institution to check access. Tax calculation will be finalised at checkout (University of Copenhagen, Department of Applied Mathematics and Statistics) All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-540-71297-8_29.
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BT - Cointegration. Overview and Development CY - Department of Applied Mathematics and Statistics / University of Copenhagen Part of the book series: The New Palgrave Economics Collection ((NPHE)) Cointegration means that two or more time series share common stochastic trends. Thus, while each series exhibits smooth or trending behaviour, a linear combination of the series exhibits no trend.
For example, short-term and long-term interest rates are highly serially correlated (so they are smooth and in this sense exhibit a stochastic trend), but the difference between long rates and short rates — the... Long rates and short rates are cointegrated. This is a preview of subscription content, log in via an institution to check access. Tax calculation will be finalised at checkout Unable to display preview. Download preview PDF.
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This Article Presents A Survey Of The Analysis Of Cointegration
This article presents a survey of the analysis of cointegration using the vector autoregressive model. After a few illustrative economic examples, the three model based approaches to the analysis of cointegration are discussed.The vector autoregressive model is defined and the moving average representation of the solution, the Granger representation,... Next the interpretation of the model and its...
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Tax calculation will be finalised at checkout Unable to display preview. Download preview PDF. Unable to display preview. Download preview PDF. This article presents a survey of the analysis of cointegration using the vector autoregressive model.
After A Few Illustrative Economic Examples, The Three Model Based
After a few illustrative economic examples, the three model based approaches to the analysis of cointegration are discussed.The vector autoregressive model is defined and the moving average representation of the solution, the Granger representation,... Next the interpretation of the model and its parameters and likelihood based inference follows using reduced rank regression. The asymptotic analys...
Unable To Display Preview. Download Preview PDF. Unable To Display
Unable to display preview. Download preview PDF. Unable to display preview. Download preview PDF. The concept of co-integration posits that the linear combination of two or more nonstationary time series can be stationary if they are co-integrated (Granger 1981). Co-integration and error correction models are largely applied to solve the spurious regression problem resulting from the inclusion of ...
Two Main Approaches To Modeling Co-integration Are Single-equation Residual-based And
Two main approaches to modeling co-integration are single-equation residual-based and system-based analyses. One precondition for the above tests is that all variables in the co-integration regression should be integrated with the same order. When different orders of integration are identified, alternative tests such as the autoregressive distributed lag bounds test can be applied (Pesaran et al. ...