Spurious Regressions With Time-Series data: Further Asymptotic Results

David Giles

No 603, Econometrics Working Papers from Department of Economics, University of Victoria

Abstract: A “spurious regression” is one in which the time-series variables are non-stationary and independent. It is well-known that in this context the OLS parameter estimates and the R2 converge to functionals of Brownian motions; the “t-ratios” diverge in distribution; and the Durbin-Watson statistic converges in probability to zero. We derive corresponding results for some common tests for the Normality and homoskedasticity of the errors in a spurious regression.

Keywords: Spurious regression; normality; homoskedasticity; asymptotic theory; unit roots (search for similar items in EconPapers)
JEL-codes: C12 C22 C52 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2006-08-17
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: ISSN 1485-6441
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:vic:vicewp:0603

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