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From |
"Rodrigo Alfaro" <[email protected]> |

To |
<[email protected]> |

Subject |
st: Re: question for fixed effect model/random effect model |

Date |
Thu, 1 Dec 2005 10:15:59 -0500 |

Hi Lijun: xtlogit with fe option is the as clogit, which means conditional logit... this kind of procedure is common called fixed-effects logit but it is not a "true" fixed-effects, created (I guess) by McFadden (read carefully the help for clogit in the manual). You will loose the observations that do not change, for example Karen always attend the class then you cannot compute the conditional probability for Karen, you don't have information where she is at home. Also, time-invariant will be omitted because there is not within-group variance. For random effects, you need that the unobservable is uncorrelated with all x (time-variant and time-invariant)... and you will use the entire sample (in particular Karen will be in the sample). In other words, in random-effects you will use all the variables (after collinearity and all the sample). A easy reference is Chamberlian 1980, but also you can start with this hand-written note http://people.bu.edu/vaguirre/courses/bu709/ec709_binary_1104.pdf. Finally, I don't understand what do you mean with two-wave, but if you think that some left-hand variable is endogenous, you have to move onto instruments estimators. Good luck, Rodrigo.

Hi all,

I come to three questions.

First, I am trying to use ramdom effect model or fixed effect model to predict

a dummy variable, the high wage using education and job experience.

The simple command look like

xtlogit highwage educ jobexp, fe i(id)

I got a note "note: multiple positive outcomes within groups encountered.

note: 644 groups (1288 obs) dropped due to all positive or all negative outcomes."

What does this mean?

Second, for variables that are constant overtime within individuals,

do I still need to include them into my model? If I include such variables,

the fixed effect model will drop them while the random effect model with consider them.

Third, if my data is two-wave cross-sectional time series data,

I wonder whether I still could not infer causality since dependent variables

and independent variables are measured at the same time. Is that right?

Best

--

Lijun Song

Department of Sociology

Box 90088,Duke University

Durham, NC 27708

Phone (919) 660-5604

Cell (919) 724-3811

FAX (919) 660-5623

[email protected]

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**References**:**st: question for fixed effect model/random effect model***From:*Lijun Song <[email protected]>

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