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From |
"Leda Inga" <ledainga@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Endogenous count variable in a binary model |

Date |
Tue, 27 May 2008 18:46:20 -0500 |

Thanks Viktor. I've read qvf help and understand that it allows for different family distribution and that has support for instrumental variables. Nevertheless, I still have some doubts: 1. In previous emails (http://www.stata.com/statalist/archive/2005-01/msg00464.html), it has been said that qvf cannot be used for endogeneity if running a probit/logit models (which is my case). Is this fact also true for endogeneity caused by omitted variables instead of simultaneity?? 2. I've read qvf help and the paper wrote about it (http://www.stata-journal.com/sjpdf.html?articlenum=st0049) and havenīt found what estimation method is used for the instrumentalization. I think that it is OLS since the endogenous variables of the examples provided in both mentioned sources are continuous. Is this is the case, I wouldn't be using an appropiate model for my endogenous variable, since it is count data. Is there a way of managing with an endogenous (by omitted variables) count data? 3. What would be the procedure if the endogenous count variable also enters the model with a square term? Thanks, Leda 2008/5/27 Viktor Slavtchev <viktor.slavtchev@uni-jena.de>: > perhaps you can use -qvf- > search qvf > findit qvf > hth > viktor > > Leda Inga wrote: >> >> Hi, >> >> I'm runing a binary regression with survey data and I'm interested in >> the effect of a count explanatory variable (called CP) which might >> have a diminishing impact. Theoretically both variables, the dependent >> and the explanatory variable of my interest, could be determined by >> some others factors which can't be controlled and so go in the error >> terms. My objectives are: 1) Test if CP has significant effect on the >> probability of ocurrence of the event I'm studying, 2) If so, test if >> the effect is diminishing, based on the significance of a cuadractic >> term (CP^2), and finally 3) Know at which point the effect of CP >> reaches it peak. >> >> Since ivprobit doesn't allow for a cuadractic term and is for >> continuos data, I didn`t use it. Instead I ran a count data model, >> saved the predicted values and generated a new variable equal to the >> square of these. Then I ran a binary regression including both, the >> predicted values of CP and the square of them. But I'm not sure if >> this estimation procedure is correct and if I'm really getting >> consistent betas and standard errors. >> >> Just to give some details, CP takes values from 0 to 20, has a mean >> 7.48 and a variance of 12.8. >> >> I would really appreciate any help, >> >> >> Leda >> * >> * 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/ > * * 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/

**References**:**st: Endogenous count variable in a binary model***From:*"Leda Inga" <ledainga@gmail.com>

**Re: st: Endogenous count variable in a binary model***From:*Viktor Slavtchev <viktor.slavtchev@uni-jena.de>

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