st: Dynamic quadratic almost ideal demand system

[Nigussie Tefera <nigussie.tefera@gmail.com>]

Dear statlist,

I am trying to estimate dynamic quadratic almost ideal demand system
using Poi's 2012 nlsur _quaids approach.  Poi's 2012 approach, available
with stata 13 version, can handle the linear and quadratic demand system
with an extension for demographic variables. However, I need to extend
the model for dynamic quaids as I am dealing with panel data analysis.
Moreover, I need to control for expenditure endogeneity as well as zero
consumption expenditure problem. The approaches for dealing with zero
consumption expenditure varies but I prefer running multivariate probit
estimation at first stage (to determine the probability of consuming
that food items/groups and also to control any correlation among food
items) and predicting the standard normal density function (PDF) and the
standard normal cumulative distribution function (CDF) which could be
augmented in the demand specification following Pan et al., 2008; Zheng
and Henneberry, 2010 approaches. Predicting CDF and PDF is easy but
augmenting in the demand system is a bit challenging as the Poi's 2012
approach does not allow us to do so.

Moreover, I have tried to write stata code based on Poi's 2008 nlsur
code (available on the website) but I came up with different regression
results as compared to the results with Poi's 2012 quaids. One causes of
the difference could be the way that demographic variable entered in the
model.  In order to do so I am modifying the alpha(i) both in the share
equations as well as total price aggregate equation (a(p)) not in
(b(p)). But I am not sure whether poi's quaids are doing the same or
not. Any suggestion would be very grateful.

Best

Nigussie

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