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From |
"C.T.Shehzad" <c.t.shehzad@rug.nl> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Simulatenous equation model with xtprobit |

Date |
Fri, 22 Aug 2008 17:21:39 +0200 |

Dear Stas:

Yes, the difference between categories is same and y1 and y2 (actual values ) should cause x but they can be endogenous and that's why I am using simulateneous equation model. Unfortunately, I donot have access to the book mentioned by Maatren for one or two weeks and I have to rely solely on gallam manual for the time being.

As an alternate approach i can also use ivprobit but that doesnot account for panel structure of data.

Best regards,

Shehzad

Stas Kolenikov wrote:

so if y's are ordinal, is the distance between categories 1 and 2 of

y1 the same as the distance between categories 2 and 3? That's what

your model explicitly assumes. Does your x depend on the realized

values of y*, or on their continuous propensity counterparts?

-gllamm- will do pretty much anything, you need to rearrange your data

in a marginally tricky way, and form appropriate -link-s.

On Fri, Aug 22, 2008 at 5:49 AM, Choudry T Shehzad <C.T.Shehzad@rug.nl> wrote:

Thanks Maarten... gllamm seems relevant but I have a question again. My

model is like

x = a + b1*y1 + b2*y2 + b3*y3

y1 = a2 + b4*y4 + b5* y3

y2 = a3 + b6*y6 + b4*y4

where x is binary and y1 and y2 are ordered. This is balanced panel

dataset (countries and years) and I want to run simultaneous equation

model becuase I suspect y1 and y2 are endogenous. Are you suggesting me

to use structural equation modelling via gllamm? If the data had been

continuous, I would have gone for reg3 but now after reading gllamm

manual, I still could not get a clear idea that how can I model y1 and y2.

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**References**:**Re: st: Simulatenous equation model with xtprobit***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Simulatenous equation model with xtprobit***From:*Choudry T Shehzad <C.T.Shehzad@rug.nl>

**Re: st: Simulatenous equation model with xtprobit***From:*"Stas Kolenikov" <skolenik@gmail.com>

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