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From |
Richard Williams <richardwilliams.ndu@gmail.com> |

To |
statalist@hsphsun2.harvard.edu, "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
re: Re: st: MIXLOGIT: marginal effects |

Date |
Wed, 08 Feb 2012 19:50:51 -0500 |

At 03:22 PM 2/8/2012, Christopher Baum wrote:

<> Clive said However, both of you, IMVHO, are wrong, wrong, wrong about the linear probability model. There is no justification for the use of this model _at all_ when regressing a binary dependent variable on a set of regressors. Pampel's (2000) excellent introduction on logistic regression spent the first nine or so pages carefully explaining just why it is inappropriate (imposing linearity on a nonlinear relationship; predicting values out of range; nonadditivity; etc). Since when was it in vogue to advocate its usage? I'm afraid that I don't really understand this.I don't understand it either, and I agree wholeheartedly with thesentiment. The undergrad textbook from which I teach Econometrics,Jeff Wooldridge's excellent book, has a section on the LPM; I skipit and tell students to stay away from it. Unfortunately, much of thebuzz about the usefulness of the LPM has arisen from theotherwise-excellent book by Angrist and Pischke, Mostly HarmlessEconometrics, in which they make strong arguments for the use of theLPM as an alternative to logistic regression.

One of my econometrician colleagues has come up with a nifty exampleof how, in a very simple context involving a LPM witha binary treatment indicator, the LPM gets the sign wrong! Alogistic regression, even though it fails to deal with any further issuesregarding the treatment variable, gets the right sign.

Is this a shareable example? I would love to see it. ------------------------------------------- Richard Williams, Notre Dame Dept of Sociology OFFICE: (574)631-6668, (574)631-6463 HOME: (574)289-5227 EMAIL: Richard.A.Williams.5@ND.Edu WWW: http://www.nd.edu/~rwilliam * * 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/

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