Spurious regressions with stationary series
نویسندگان
چکیده
منابع مشابه
Spurious Regressions with Time-series Data: Further Asymptotic Results
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 R 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 Normal...
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It is very common to see reported in applied econometric literature time series regression equations with an apparently high degree of fit, as measured by the coefficient of multiple correlation R2 or the corrected coefficient R2, but with an extremely low value for the Durbin-Watson statistic. We find it very curious that whereas virtually every textbook on econometric methodology contains exp...
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The purpose of this paper is to study the exact nite sample properties of estimators and test statistics for regression coeÆcients of spurious regressions with unit root nonstationary variables. The conditional probability version of the Gauss-Markov theorem is used to nd eÆcient estimators. Then with an additional assumption that the error is normally distributed conditional on the regressors,...
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The literature on spurious regressions has found that the t-statistic for testing the null of no relationship between two independent variables diverges asymptotically under a wide variety of nonstationary data generating processes for the dependent and explanatory variables. This paper introduces a simple method which guarantees convergence of this t-statistic to a pivotal limit distribution, ...
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ژورنال
عنوان ژورنال: Applied Economics
سال: 2001
ISSN: 1466-4283,0003-6846
DOI: 10.1080/00036840152022232