<>
John writes
how does one do single-equation
estimation with in the context of a non-recursive system. Again, here
is the example:
Eq1: y = x1 + x2 + z
Eq2: x1 = m1 + m2 + x2 + z
Eq3: x2 = n1 + n2 + x1 + z
Eq4: m1 = q1 + q2 + z
Eq5: m2 = p1 + p2 + z
The predicted value of x2 enters in Eq. 2; however, the predicted value
of x1 enters in Eq. 3. So, how does one go about estimating this
non-recursive model using a single-equation estimator?
In the textbook example used to motivate 2SLS, we write down a demand equation and a supply equation, both of which contain Q and P along with demand shifters and supply shifters. How is that different from eq2-3?
Q = b0 + b1 P + b2 Y + e
P = g0 + g1 Q + g2 R + g3 T + v
with Y=income, R=rainfall, T=temperature.
Those who developed IV / 2SLS were able to consistently estimate these equations by limited-information (single-equation) before systems estimators were devised. For that matter LIML could be used to estimate these equations as well (in either -ivregress- or -ivreg2- from SSC).
Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html
An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html
*
* 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/
