Unit Root Tests
A process might be non-stationary without being a unit root. The two concepts are related, but they are not identical and it is common to confuse the two. We can have non-stationarity without it being due to a unit root. We could have a seasonal model. Or, we could have a deterministic trend. (We can even have non-stationarity because the variance is changing over time.)
- Cheung, Y.-W., & Lai, K. S. (1995a). Lag order and critical values of the augmented Dickey–Fuller test. Journal of Business and Economic Statistics, 13(3), 277–280.Google Scholar
- Elliott, G., Rothenberg, T. J., & Stock, J. H. (1992). Efficient tests for an autoregressive unit root. Working Paper 130, National Bureau of Economic Research. http://www.nber.org/papers/t0130.
- MacKinnon, J. G. (1991). Critical values for cointegration tests, Chapter 13. In R. F. Engle & C. W. J. Granger (Eds.), Long-run economic relationships: Readings in cointegration. Oxford : Oxford University Press.Google Scholar
- MacKinnon, J. G. (2010). Critical values for cointegration tests (Technical report), Queen’s Economics Department Working Paper.Google Scholar
- Maddala, G. S., & Kim, I.-M. (1998). Unit roots, cointegration, and structural change. Cambridge: Cambridge University Press.Google Scholar
- Newey, W. K., & West, K. D. (1986). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Working Paper 55, National Bureau of Economic Research. http://www.nber.org/papers/t0055.
- Schwert, G. W. (1989). Tests for unit roots: A Monte Carlo investigation. Journal of Business and Economic Statistics, 7(2), 147–159.Google Scholar