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From |
Prakash Singh <prakashbhu@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: hetroscedasticity test after probit |

Date |
Thu, 5 Jul 2012 17:03:22 +0530 |

Maarten and Yuval I just saw this paper (Parikh ans Sen 2006, Applied Economics Letters 2006, 13, 699-707) where they have tested the presence of hetroscedasticity both in probit and hetpro estimators. Though, I agree with Maarten but I wanted to do this test as the referee has asked me perform so if there is any way I can test it. Prakash On Thu, Jul 5, 2012 at 3:23 PM, Maarten Buis <maartenlbuis@gmail.com> wrote: > On Thu, Jul 5, 2012 at 11:27 AM, Yuval Arbel wrote: >> Maarten, I believe your implication refers to specification errors in >> the model, i.e., omission of relevant explanatory variables, leading >> to biased and inconsistent estimates and predictions. Am I correct? > > Not quite, as we defined the probability in terms of the variables in > our model, so we are by definition not omitting relevant variables. > The problem is that the probability is only defined within the context > of the model. A probability is a measure of uncertainty. This does not > mean that uncertainty is "unexplainable", we can always find > "explanations" for random events and put those "explanations" into > variables. However, (hopefully) for substantive reasons we have > classified these variables as random/unsystematic. (*) Once we have > made our choice there is, by definition, no omitted variable problem, > but the difference in variance of the omitted/random/unsystematic > variables across included co-variates will still cause problems if we > wish to interpret our results in a causal/counter-factual way. > > Another way to think about this is to consider what would happen if we > could control for everything. In that case there is no uncertainty > left and the "probabilities" would be either 0 or 1 for all > observations and the (linear additive) effects could only be -1, 0, or > 1. This is typically not the kind of estimate of interest. > > Hope this helps, > Maarten > > (*) In practice we typically we do so by omission: we choose a set of > variables to include in our model and define everything else as > random/unsystematic. > > -------------------------- > Maarten L. Buis > Institut fuer Soziologie > Universitaet Tuebingen > Wilhelmstrasse 36 > 72074 Tuebingen > Germany > > > http://www.maartenbuis.nl > -------------------------- > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: hetroscedasticity test after probit***From:*Maarten Buis <maartenlbuis@gmail.com>

**References**:**st: hetroscedasticity test after probit***From:*Prakash Singh <prakashbhu@gmail.com>

**Re: st: hetroscedasticity test after probit***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: hetroscedasticity test after probit***From:*Prakash Singh <prakashbhu@gmail.com>

**Re: st: hetroscedasticity test after probit***From:*Muhammad Anees <anees@aneconomist.com>

**Re: st: hetroscedasticity test after probit***From:*Prakash Singh <prakashbhu@gmail.com>

**Re: st: hetroscedasticity test after probit***From:*Muhammad Anees <anees@aneconomist.com>

**Re: st: hetroscedasticity test after probit***From:*Yuval Arbel <yuval.arbel@gmail.com>

**Re: st: hetroscedasticity test after probit***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: hetroscedasticity test after probit***From:*Yuval Arbel <yuval.arbel@gmail.com>

**Re: st: hetroscedasticity test after probit***From:*Maarten Buis <maartenlbuis@gmail.com>

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