Re: st: an estimation method question

[Xiang Ao <xao@hbs.edu>]

Hi Maarten,

Thanks for the suggestions.  Indeed the categories need to have the same 
meaning across groups.  In our case, that does not fit.  If it's a 
market share study of, say five different brands of products, then it 
would make sense. 

We are interested in founder level.  I am thinking whether we can do a 
maximum likelihood with some constraints by observation.  That is, 
assume each share conforms to beta distribution, for example, then 
within each firm, the shares add up to one.  Would that be valid?

I also like your idea of thinking of founders nested under firms.  But 
we have to take care of the sum constraint somehow.

Xiang

Maarten buis wrote:
> --- On Tue, 16/3/10, Xiang Ao  wrote:
>   
> > There are different numbers of founders for each firm. 
> > The smallest number is 2, it can be as many as 10
> > co-founders.  As far as I understand, the number of
> > categories need to be fixed in the methods you
> > mentioned. 
> >     
>
> That is right, but more importantly the categories need
> to have the same meaning across observations. For example
> imangine we are looking at the proprotion of spending in 
> a firm on labour and capital (I am no business economist 
> so forgive me if this doesn't make substantive sense). 
> Across firms the proportion spent on labour has (sorta) 
> the same meaning. The aim of such an analysis is to find
> variables that make some firms spend more on labour and 
> others more on capital goods.
>
> I find it harder to come up with something similar for 
> the different founders. Who would fall in the first 
> category, who in the second, etc. (alphabetical order?). 
> A solution would depend on what your unit of analysis 
> is for your study, i.e. who do you want to study: the 
> firms or their founders. 
>
> If you want to study the firms, than I could imagine 
> that you are interested in explaining differences in 
> the "structure" of ownership. I would than try to 
> operationalize that in one number per firm and use an 
> appropriate regression like command to analyse that. 
> For example, I could imagine someone interested in the 
> share of the largest founder as a measure of 
> concentration of ownership, in which case I would use 
> the -glm- trick or -betafit- (zero or one proportions 
> are no problem there as you stated that the minimum 
> number of founders in your dataset is 2). Alternatively,
> you could try other summaries of the concentration of
> ownership like entropy. Don't take my reference to 
> entropy too literaly, I only know that there are many
> such measure, and entropy was the only one I could
> remember.
>
> If you want to study founders, I would for now forget
> about the constaint that the proportions should add
> up to one, and transform the data to a panel dataset 
> where the observations are founders nested in firms. 
> I would than try -xtgee- to model these proportions,
> just like the -glm- trick. It will be a population
> averaged model, so no individual level effects, 
> which seems to be considered a problem in economics.
> However, it would be a good place to start.
>
> Hope this helps,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://www.maartenbuis.nl
> --------------------------
>
>
>       
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>   

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/