Ronnie,
Have you consider estimating the relationship in the
context of a production/profit function? You would need
some measure of output in your dataset, and unit cost/price
information in order to do this.
I recommend this approach, because ultimately it is in the
growers best interest to select the technology that he/she
expects will give the best crop yield for their effort(cost).
This observation implies that the choice of technology is not
independent of the expected returns for use of the technology,
or the mix of technologies. (I am ignoring some issues around
the access to technology, and the priors the growers hold around
the use of each technology both of which are not inconsiderable
issues in many markets around the world.)
Essentially, if you estimate the relationship with the
technology indicator on the left-side of the equation you are
implicitly inverting the profit function to get a set of
factor demand equations in latent form.
If I were pursuing this analysis, I would not go much further than
your proposed tabular analysis unless I had unit cost and yield
data to put on the right-side of the equation. I would also
set the analysis up as a system of simultaneous logit equations with
unit costs, yields, other independent variables, and the dummy
variables for the other technology choices on the right-hand side.
Obviously, this is not a trivial estimation exercise but it is
an interesting problem.
For simplicity you could ignore the simultaneity issues in the system
and then you have a straightforward set of single equation logit estimates
for the use of each technology, each of which represent a latent form
of the factor demand for that technology, conditional on the other
technologies, unit costs, expected yields, and other regressors.
Best Regards,
Rafael Bradley
(Tel) 602-296-4135
(Fax) 602-926-2560
(Mob) 602-793-8135
www.quanticle.com
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Ronnie Babigumira
Sent: Thursday, April 21, 2005 6:42 AM
To: [email protected]
Subject: st: Multiple responses on plot level data
Dear List (I hope the subject line reflects what I intend to present as my
problem), Something has been slowly eating away at me and at this point I
have decided to seek help from the list. I have plot level data on use of
soil conservation measures and would like to construct a "single" dependent
variable for each household for use in a multinomial logit. The data look
something like this
hhd_id plnum fert man fanyaju
1001 1 0 1 0
1001 2 0 1 1
1001 3 1 0 1
1002 1 0 0 0
1002 2 1 1 1
1003 1 1 0 0
Where
hhd_id: Household id
plnum: Plot number (a household may have more than one plot) And fert, man
and fanyaju are 3 possible soil conservation measures a household may
undertake (it is possible that more than one measure can be applied to a
plot)
My question is how do I go about with constructing a single dependent
variable for use in a multinomial logit in this case (and would this be
correct). I have considered the simplest case where I construct a simple
dummy for each plot indicating whether or not a household used at least one
of the measures however, I feel that it would be more interesting if I could
say something on the determinants for the use of the different measures
Many thanks
Ronnie
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