RE: st: Adding up constraints in a nonlinear system of share equations

[Alex Olssen <Alex.Olssen@motu.org.nz>]

Thanks Brian,

I will follow up those links.

I am aware the shares SUM to one because of the restrictions.  My question is whether or not the individual shares are constrained to the [0,1] interval.  I.e., could I get some shares to be zero or others to be one.  I think your recommended articles may well solve this problem because it is essentially a corner solution problem and I guess in demand share estimation the corner solution expenditure share = 1 is never really a problem.

Thanks a lot, you have been very helpful these last two days.

Warm regards,

Alex Olssen
Research Analyst
Motu Economic & Public Policy Research
Ph 939 4250  Fax 939 4251
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-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Brian P. Poi
Sent: Thursday, February 24, 2011 3:03 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Adding up constraints in a nonlinear system of share equations


On 2/23/2011 7:18 PM, Alex Olssen wrote:
> Hi Statalisters,
>
> I am estimating a system of nonlinear share equations.  It is similar to an AIDS model but I want to make sure the predicted shares always lie in the [0,1] interval.  Am I correct in thinking that predicted vaules from AIDS and QUAIDS models can fall outside this interval?
>
> In a linear system of share equations there are adding up constraints which make sure the sum of the shares is always one.  Such constraints correspond to the net marginal effect of changing a regressor being zero.
>
> My question is whether the equivalent constraints for a nonlinear system provide for an estimable model.  The specific nonlinear model I am thinking results in assuming the shares follow a logit model - this assumption may be shaky but please bear with me.
>
> In the logit case the marginal effect of changing x_k is well known to be  e^(v_i)/((1+e^(v_i))^2)*B_k.  Where v_i is the linear combination of regressors and coefficients and B_k is the estimated coefficient on x_k.  Following the logic from the linear system I translated the adding up constraint to say that the sum of these marginal effects over i must be equal to zero.
> Is this correct?  Can it be estimated?  My problem with estimation is that the constraint must hold across all values of x_k as the marginal effects vary with x_k.  To estimate this, must I solve for parameters as functions of x_k?
>
> Does anyone know of an easier solution?  I have yet to see an AIDS/QUAIDS paper that guarantees predicted values to fall in the [0,1] interval.  If you know of one I would be very grateful for the pointer!
>
> Kind regards,
>

The predicted expenditure shares from an AIDS model will sum to one by 
virtue of the fact that the parameters were constrained during 
estimation to ensure that happens.

The more common issue that arises in demand system estimation is how to 
deal with expenditure shares that equal zero (a "corner" solution).  One 
strand of literature started by Wales and Woodland (1983) is based on 
the Kuhn-Tucker conditions for constrained maximization, while another 
strand tries to tackle the problem from a multivariate generalization of 
the tobit model; Heien and Wessells (1990 and 1993) are well-known 
papers in this area.  The American Journal of Agricultural Economics 
would be a good place to browse for more recent developments.  I've 
never tried fitting any of those models, so I can't be of more help.

    -- Brian Poi
    -- brian@poiholdings.com


Heien, D. and Wessells, C. R.  Demand systems estimation with microdata: 
A censored regression approach.  J. Business and Economic Statistics 
8:365-71.

Wales, T. J. and Woodland, A. D.  Estimation of consumer demand systems 
with binding non-negativity constraints.  J. Econometrics 21: 263-85.


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