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From |
Austin Nichols <[email protected]> |

To |
[email protected] |

Subject |
Re: st: dprobit and lincom |

Date |
Fri, 22 Jan 2010 10:06:53 -0500 |

Maarten-- It only makes sense to look at marginal effects at the mean if the vector of means of the explanatory variables is a sensible point to examine the marginal effect for; if that vector represents a unit that is not observed in the data, or cannot be observed, as is often the case--for example, with many binary explanatory variables in the list of explanatory variables, it is rare that a vector of means represents a sensible point at which to examine the marginal effect. It may be that the combinations of mean x1 and mean x2 are logically inconsistent, even, so that point could never exist. Capturing the distribution of explanatory variables is precisely the aim of looking at the mean marginal effect rather than the marginal effect at the mean, but I agree looking at marginal effects for various specific vectors of explanatory variables, for vectors that represent some hypothetical unit of interest, also makes sense; I just don't think the mean vector often falls in this category, and certainly does not by default--it is an assertion that needs to be examined in each specific case that a marginal effect at the mean is informative in any way. Of course, in practice, the marginal effect at the mean is often very close to any average of observation-specific marginal effects you might actually be interested in, but that does not change the essential point. I don't think my statement is a bit strong, in other words--I could make it even stronger and back it up with examples--and yet I think we are not too far apart in our fundamental attitudes toward marginal effects. On Fri, Jan 22, 2010 at 5:53 AM, Maarten buis <[email protected]> wrote: > > --- Austin Nichols wrote: >> You should really not use -mfx- or -dprobit- at all, as the marginal >> effect at the mean is not informative for most purposes > > I think that is a bit strong. When it comes to interpreting these > interaction effects with marginal effects I would probably use both, > as the average marginal effects not only include differences in > effect but also differences in the distribution of the controll > variables. The marginal effects at the means, by necesity control > for this. So by looking at both I get an idea of how much is due > differences in effects and how much is due to differences in > distributions of the controll variables. > * * 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/

**References**:**RE: st: dprobit and lincom***From:*Melanee Thomas <[email protected]>

**RE: st: dprobit and lincom***From:*Maarten buis <[email protected]>

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