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I have a time-series which is autocorrelated by construction, and might be heteroscedastic. I have calculated the sample mean of this time-series, and would like to calculate the t-statistic corresponding to the hypothesis that the mean of this time-series is zero. It is my understanding that since my time-series is autocorrelated and possibly heteroscedastic, that I must use a t-statistic "adjusted for serial dependence according to the Newey-West method".

  1. I have problem understanding the method, and how to implement this in Matlab. As far as I understand, Newey-West is used in regressions to obtain HAC standard errors, since the OLS standard errors are not a reliable basis for inference under serial correlation of the error term in a regression. But in my case, I am not regressing anything, so how does the Newey-West method fit in? Under no autocorrelation and homoscedasticity, I would have simply divided the sample mean (minus 0) by the standard error (sample standard deviation over square root of the number of observations). There would therefore be no need for regressing anything.
  2. How can I implement computation of Newey-West t-statistics in Matlab?
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This seems like quite a common situation, I am surprised that no answer has surfaced! –  lodhb Nov 20 '12 at 13:26
Is this still relevant? I can answer this if it is.. –  user29427 Aug 22 '13 at 12:21
Yes! The principle of this forum is that regardless of whether the OP has lost interest or is still watching, the answers should still interest anyone else with the same problem. –  Nick Cox Aug 22 '13 at 12:32
@NickCox is correct. In addition, you should edit this to answer or delete it. At present, it is not an answer by CV's standards & doesn't belong. (Note that we prefer an answer, of course.) –  gung Aug 22 '13 at 12:43
@daniel please go right ahead and answer the question –  Glen_b Aug 22 '13 at 16:10

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