Re: st: which STATA version for Poi's QUAIDS command

[Luca Tiberti <ltiberti@gmail.com>]

Thanks so much Brian. After I reduced down the number of demographic
variables, I was able to run the command.

Thanks for your prompt help,
Luca

2013/3/18 Brian P. Poi <bpoi@stata.com>:
> On 03/18/2013 04:15 PM, Luca Tiberti wrote:
>>
>> Hi Nick, thanks for this
>>
>> here is the output of describe, short
>>
>>
>> obs:         3,860
>> vars:            39                          18 Mar 2013 15:37
>> size:       455,480
>> Sorted by:  serial
>>       Note:  dataset has changed since last saved
>>
>> For your info, I had already tried by keeping only variables finally
>> entering into the demand system and compress them. However I was not
>> able to run succesfully the command.
>>
>> Thanks for your help,
>> Luca
>>
>
> Luca,
>
> How many goods are in your demand system?  How many demographic variables
> are you specifying?
>
> To estimate the model, -quaids- must create temporary variables to hold
> observation-level derivatives of each equation with respect to each of the
> parameters.  The details are in the methods and formulas section of [R]
> nlsur.
>
> For a basic AIDS model, with three goods there are 7 free parameters and 2
> estimated equations, for a total of 14 temporary variables -quaids- needs to
> create.  With four goods, there are 12 free parameters and 3 estimated
> equations, for a total of 36 temporary variables.  If my math is correct, a
> basic AIDS model with 15 goods has 133 parameters and 14 estimated equations
> for a total of 1,862 temporary variables.  If you have 16 goods, there are
> 2,250 derivatives that must be stored in temporary variables, too many for
> Stata/IC to handle.
>
> If you include the quadratic income term (the QUAIDS model), then you will
> hit Stata/IC's variable limit if you try to fit a 15-good model.
>
> Throw one demographic variable into the QUAIDS model, and you are down to 13
> goods.  Five demographic variables and you're down to 11 goods.
>
> In short, having many goods and demographics can quickly balloon the number
> of parameters in the model and hence the number of temporary variables
> needed during estimation.
>
> I hope this helps.
>
>    -- Brian Poi
>    -- bpoi@stata.com
>
>
>
>
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