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Spurious regression under broken trend stationarity Author info | Abstract | Publisher info | Download info | Related research | Statistics Daniel Ventosa-Santaularia
Antonio E. Noriega
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We study the phenomenon of spurious regression between two random variables when the generating mechanism for individual series follows a stationary process around a trend with (possibly) multiple breaks in its level and slope. We develop relevant asymptotic theory and show that spurious regression occurs independently of the structure assumed for the errors. In contrast to previous findings, the spurious relationship is less severe when breaks are present, whether or not the regression model includes a linear trend. Simulations confirm our asymptotic results and reveal that, in finite samples, the spurious regression is sensitive to the presence of a linear trend and to the relative locations of the breaks within the sample
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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number
186.
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Date of creation: 11 Nov 2005Date of revision:
Handle: RePEc:sce:scecf5:186Contact details of provider: Email: Web page: http://comp-econ.org/ More information through EDIRC
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Keywords: Spurious regression Structural breaks Stationarity Other versions of this item:
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Antonio E. Noriega & Daniel Ventosa-Santaularia, .
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Hrishikesh D. Vinod, 2008.
"Heteroscedasticity and Autocorrelation Efficient (HAE) Estimation and Pivots for Jointly Evolving Series ,"
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