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.
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Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number
0603.
Length: 18 pages Date of creation: 17 Aug 2006 Date of revision: Handle: RePEc:vic:vicewp:0603
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