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Statistical Inference in Regressions with Integrated Processes: Part 2

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Abstract

This paper continues the theoretical investigation of Park and Phillips [7]. We develop an asymptotic theory of regression for multivariate linear models that accommodates integrated processes of different orders, nonzero means, drifts, time trends and cointegrated regressors. The framework of analysis is general but has a common architecture that helps to simplify and codify what would otherwise be a myriad of isolated results. A good deal of earlier research by the authors and by others comes within the new framework. Special models of some importance are considered in detail, such as VAR systems with multiple lags and cointegrated variants.

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File URL: http://cowles.econ.yale.edu/P/cd/d08a/d0819-r.pdf
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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 819R.

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Length: 63 pages
Date of creation: 1986
Date of revision: Feb 1987
Publication status: Published in Econometric Theory (1989), 5: 95-131
Handle: RePEc:cwl:cwldpp:819r

Note: CFP 722.
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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