Re: st: Extension of Bivariate Probit

[Ayman Farahat <ayman.farahat@yahoo.com>]

Thanks for the response
However, the marketing_options in my case are endogenous. 
So i cant use the setting you described. 
Thanks

On Jul 30, 2012, at 9:28 PM, Muhammad Anees wrote:

> What I guess from your discussion,
> 
> You need to model:     Y(Fail/Succeed)=f(marketing Options)+Covariates
> 
> Is this not a case of simple Logistic Regression with Marketing
> Options as Categorical Indicator variables?
> 
> So your model should like:      -xt-logit y i.marketing options covariates
> 
> where -xt- is optional in case if you had panel data.
> 
> Best
> Anees
> 
> On Tue, Jul 31, 2012 at 3:19 AM, Ayman Farahat <ayman.farahat@yahoo.com> wrote:
>> Hello;
>> I am working on a modeling whether adopting a certain marketing scheme can lead to a firm's failure.
>> The firm has one of n+1 marketing option, where the first n represents the marketing choices and the "n+1" option represents not taking any action. I can model these decisions using a other exogenous covariate.
>> 
>> After adopting any of the "n+1" marketing options, the firm can fail or survive. I can again model the business failure using exogenous covariates.
>> 
>> I want to know whether the two outcomes (choice of marketing AND failure are related). If i only had one marketing decision, i could have used bivariate probit.
>> is there an extension of the Bivariate  probit to the case where one of the dependent variables is categorical (not binary and not ordinal)?
>> Thanks
>> Ayman
>> 
>> 
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> 
> 
> 
> -- 
> 
> Best
> ---------------------------
> Muhammad Anees
> Assistant Professor/Programme Coordinator
> COMSATS Institute of Information Technology
> Attock 43600, Pakistan
> http://www.aneconomist.com
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