[Limdep Nlogit List] Problem with NLSUR

[William Greene]

Dear Mr. James.  Continuing ...
Given that neither of the LHS variables appears on the RHS of these
equations, you probably don't need NL3SLS; nonlinear least squares
will suffice. But, if any of x2,x3 or x4 are endogenous, you'd need
5 instruments for the 5 parameters. If, say, it is x2, then you have
ONE,X3,X4, but you'd need two others.  You need at least one moment
equation for each parameter being estimated.  The shortage of instruments
is what is causing he singularity. The program is trying to invert a
5x5 matrix based only two instruments - it has rank 2.
/Bill Greene


----- Original Message -----
From: wgreene at stern.nyu.edu
To: "Limdep and Nlogit Mailing List" <limdep at limdep.itls.usyd.edu.au>
Sent: Thursday, March 12, 2009 7:07:01 PM GMT -05:00 US/Canada Eastern
Subject: Re: [Limdep Nlogit List] Problem with NLSUR


Dear limdep listers,

Am pretty new to limdep so kindly excuse my silly questions and mistakes. Am
trying to estimate a nonlinear system of equations using the NLSUR command
for NL3SLS exemplified as follows:

NLSUR   ;Lhs = lnY, lnfert_d
        ;Fn1 = a1 + a2*x2 + a3*x3
        ;Fn2 = -Log(a2) + b1*x3 + b2*x4
        ;Labels = a1, a2, a3, b1, b2
        ;Start = 0, 1, 0, 0, 0
        ;Inst = x3, x4$

Whenever I try to run this estimation I get the following error messages
"Error   143: Models - estimated variance matrix of estimates is singular"
"Error   447: Current estimated covariance matrix for slopes is singular"

Where could the mistake be?

=============================================================================
==
Rao E.O. James (Msc)
Research Associate/PhD Student

Department of Agricultural Economics and Rural Development
Georg-August University of Göttingen
Platz der Gottinger Sieben 5
37073 Göttingen, Germany.
 
Tell:+49-551-394443 (Office)
E-mail: jimrao2 at yahoo.co.uk;  James.Rao at agr.uni-goettingen.de

Courage is not the absence of fear but the triumph over it ... so fear not to
fear ... but strive to overcome fear!


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