Multiple Time Series Regression with Integrated Processes

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ID: 302208
1986
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Abstract
This paper develops a general asymptotic theory of regression for processes which are integrated of order one. The theory includes vector autoregressions and multivariate regressions amongst integrated processes that are driven by innovation sequences which allow for a wide class of weak dependence and heterogeneity. The models studied cover cointegrated systems such as those advanced recently by Granger and Engle and quite general linear simultaneous equations systems with contemporaneous regressor error correlation and serially correlated errors. Problems of statistical testing in vector autoregressions and multivariate regressions with integrated processes are also studied. It is shown that the asympotic theory for conventional tests involves major departures from classical theory and raises new and important issues of the presence of nuisance parameters in the limiting distribution theory.
Reference Key
openalex_W1981020475 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors P. C. B. Phillips, Steven N. Durlauf
Journal The Review of Economic Studies
Year 1986
DOI
10.2307/2297602
URL
https://doi.org/10.2307/2297602
Keywords Keywords not found

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