Spurious Common Factors
We conduct Monte Carlo simulations of principal components analyses of unrelated time series in order to investigate whether the stationarity properties of the data matter, as they do for least-squares regression analysis. We find that for stationary series the results are standard and reflect the lack of a relationship. For non-stationary series however spurious common factors may persist in large samples.
|Date of creation:||Oct 2012|
|Date of revision:||Oct 2012|
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- Peter C.B. Phillips, 1985.
"Understanding Spurious Regressions in Econometrics,"
Cowles Foundation Discussion Papers
757, Cowles Foundation for Research in Economics, Yale University.
- Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
- Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
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