Re: st: predicting consumption

[gemini mtei <gjmt_99@yahoo.com>]

Thanks for the suggestion Joerg,

I have tried the glm-gamma option but the estimated coefficient am getting a almost similar to the one i get using OLS. These give similar prediction as OLS.

G.

--- On Wed, 9/3/11, Joerg Luedicke <joerg.luedicke@gmail.com> wrote:

> From: Joerg Luedicke <joerg.luedicke@gmail.com>
> Subject: Re: st: predicting consumption
> To: statalist@hsphsun2.harvard.edu
> Date: Wednesday, 9 March, 2011, 16:34
> On Wed, Mar 9, 2011 at 11:03 AM,
> gemini mtei <gjmt_99@yahoo.com>
> wrote:
> > I am trying to predict household total consumption
> from the national household budget survey to a small survey
> that we conducted but didn't collect consumption. I have
> used a linear model (OLS) as follow,
> >
> > log(consumption)= B0 +B1wealth+B2log(household size) +
> B3wealth*log(household size) +B4wealth*location, where
> >
> > wealth is measured by asset index constructed from
> ownership of assets, housing characteristics, source of
> utilities, and household head specific characteristics (i.e.
> education and employment). Location captures urban-rural
> differences.
> >
> > The model is giving me R-square of .55 and i have done
> all diagnostic tests and it seems fine. I have used the
> split half method for validation of the predicted
> consumption but (i.e. selecting a random sample from the
> households survey, run consumption model and predict into
> the remaining sample then compare with actual consumption)
> the problem i am facing is the model over predicts
> consumption for the households with low consumption while it
> under predict for households with higher consumption.
> >
> > I need the predicted consumption for the analysis of
> out of pocket financing incidence in the small survey i
> mentioned above. These survey had small difference in their
> implimentation time and the assumption i am putting is that
> since the household budget survey is nationally
> representative i can use it to predict consumption into this
> small survey.  Can you advise whether i am making mistake
> in model specification? Is there a special case in
> predicting with interactions?
> >
> 
> I am merely guessing but an OLS model might not be the
> right choice.
> The fact that:
> 
> Quote:
>  "i am facing is the model over predicts consumption for
> the
> households with low consumption while it under predict for
> households
> with higher consumption"
> 
> seems to indicate that other distributions may be of better
> fit. Have
> you checked anything beyond OLS? For instance, using a
> gamma glm:
> 
> glm  consumption [your indep vars] , family(gamma)
> link(log)
> 
> would be a better fit?
> 
> J.
> 
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