4.8.2.1.1. statsmodels.tsa.adfvalues.mackinnoncrit

statsmodels.tsa.adfvalues.mackinnoncrit(N=1, regression='c', nobs=inf)

Returns the critical values for cointegrating and the ADF test.

In 2010 MacKinnon updated the values of his 1994 paper with critical values for the augmented Dickey-Fuller tests. These new values are to be preferred and are used here.

Parameters:

N : int

The number of series of I(1) series for which the null of non-cointegration is being tested. For N > 12, the critical values are linearly interpolated (not yet implemented). For the ADF test, N = 1.

reg : str {‘c’, ‘tc’, ‘ctt’, ‘nc’}

Following MacKinnon (1996), these stand for the type of regression run. ‘c’ for constant and no trend, ‘tc’ for constant with a linear trend, ‘ctt’ for constant with a linear and quadratic trend, and ‘nc’ for no constant. The values for the no constant case are taken from the 1996 paper, as they were not updated for 2010 due to the unrealistic assumptions that would underlie such a case.

nobs : int or np.inf

This is the sample size. If the sample size is numpy.inf, then the asymptotic critical values are returned.

References

MacKinnon, J.G. 1994 “Approximate Asymptotic Distribution Functions for

Unit-Root and Cointegration Tests.” Journal of Business & Economics Statistics, 12.2, 167-76.

MacKinnon, J.G. 2010. “Critical Values for Cointegration Tests.”

Queen’s University, Dept of Economics Working Papers 1227. http://ideas.repec.org/p/qed/wpaper/1227.html