Skip to main content
10 events
when toggle format what by license comment
Dec 19, 2019 at 13:50 comment added Richard Hardy @Confounded, I am not entirely sure, but I think that MLE is also biased. Under a normality assumption for the errors, MLE should coincide or nearly coincide with OLS estimator for AR and VAR models. There should be some literature on the topic, but I am not ready to look it up this time.
Dec 19, 2019 at 12:51 comment added Confounded My understanding is that in such cases a Maximum Likelihood (or quasi-likelihood) estimator should be used instead, no?
Dec 19, 2019 at 12:49 comment added Richard Hardy OK, if you only want a brief answer, then yes, the estimator is biased. (It is still consistent, i.e. asymptotically unbiased, and asymptotically normal.) A follow up question would be, is there a better estimator? Shrinkage estimators are usually good in terms of mean squared error and similar metrics, but they are typically even more biased in small samples.
Dec 19, 2019 at 12:32 comment added Confounded Because my question (or rather, point) is directly related to the OP, in my opinion. I believe, the bias of OLS in AR is a well-know issue. An demonstration of the phenomenon is given, for example, here: Asatoshi Maeshiro (2000) "An Illustration of the Bias of OLS for $Y_t = λY_{t-1} + U_t$", The Journal of Economic Education, 31:1, 76-80.
Dec 18, 2019 at 19:51 comment added Richard Hardy @Confounded, why don't you post it as a separate question?
Dec 18, 2019 at 19:25 comment added Confounded But isn't the assumption of strict exogenity violated in, say, AR model and doesn't this then mean that OLS estimate is biased? Thank you
Jun 26, 2017 at 18:55 history edited Richard Hardy CC BY-SA 3.0
edited body
Jun 26, 2017 at 18:55 comment added Richard Hardy @Kuma, thanks! A lot of credit goes to Matthew Gunn and Christoph Hanck, of course.
Jun 26, 2017 at 18:32 vote accept Kuma
Jun 25, 2017 at 19:45 history answered Richard Hardy CC BY-SA 3.0