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From |
Alejandro Delafuente <alejandro.delafuente@sant.ox.ac.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: mfx with xtlogit |

Date |
Wed, 05 Mar 2008 23:12:01 +0000 |

Dear Johannes, Many thanks for your suggestion, I agree with you diagnostic: simply marginal effects depending on the rest of variables make hard to predict significance. Did try with margeff, but apparently this is the only command that xtlogit rejects for estimating marginal effects. It asks for mfx. Do you have any other suggestion? My sample is large enough, I have around 8,000 observations. Alejandro In message <OF65E55122.4FCD5F48-ONC12573FB.0039244D-C12573FB.003AF645@diw.de> statalist@hsphsun2.harvard.edu writes: > Dear Alejandro, > > it happens that coefficients are significant and marginal effects not. > They simply depend on all other coefficients which makes it hard to > predict their significance - e.g. it might be important to decide whether > to include insignificant coefficients of other variables in your > calculation. > You have to decide over which marginal effect to calculate - did you try > -margeff- by Tamas Bartus? In my view it is more flexible than mfx. You > can e.g. calculate average marginal effects, i.e. calculate the mean > effect in your sample (margeff can do this) or simply evaluate your > function at sample means (mfx default). If your sample is small you could > also think of bootstrapping standard errors of marginal effects. > > Hope that helps, > > Johannes > > ---------------------- > Johannes Geyer > Deutsches Institut für Wirtschaftsforschung (DIW Berlin) > German Institute for Economic Research > Department of Public Economics > DIW Berlin > Mohrenstraße 58 > 10117 Berlin > Tel: +49-30-89789-258 > > > > Alejandro Delafuente <alejandro.delafuente@sant.ox.ac.uk> > Gesendet von: owner-statalist@hsphsun2.harvard.edu > 26/02/2008 11:20 > Bitte antworten an > statalist@hsphsun2.harvard.edu > > > An > statalist@hsphsun2.harvard.edu > Kopie > > Thema > st: mfx with xtlogit > > > > > > > Dear statalisters, > > I estimated marginal effects after running xtlogit with fixed effects as > follows: > > xtlogit depvar independentvars, i(folio) fe > mfx, predict(pu0) > > Where depvar indicates reception of transfers. All the marginal effects of > > interest are insignificant (most of which are dummy variables), except for > one > variable which has few observations across my 3-round panel. This came as > a > surprise for two reasons: > 1) the xtlogit coefficients for some of those same > variables were significant; > 2) I had run probit over the pooled sample (ie: dprobit depvar > indepvars)and > xtprobit (ie: xtprobit depvar indepvars, re) BEFORE xtlogit and some of > those > same coefficients were highly significant as well. > > My understanding is that there isn't one single way for capturing marginal > > effects after xtlogit, but am a bit puzzled with what I've found thus far > and > wonder whether other commands for estimating mfx after xtlogit exist? Or > any > advice as to why this insignificancy might be taking place? > > Thanks, > > Alejandro > -- > Alejandro de la Fuente > Department of International Development/QEH > University of Oxford, Mansfield Road, Oxford OX1 3TB > Tel: 01865 281836 > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > > > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ -- Alejandro de la Fuente Department of International Development/QEH University of Oxford, Mansfield Road, Oxford OX1 3TB Tel: 01865 281836 * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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