Hello,I am estimating a system of 3 equations using a nonlinear GMM.The first
and second equations consists of a linear part and a nonlinear part. The
nonlinear parts is specified as a logit and the logit as a whole has a
coefficient attached to it. For the first two equations, it is specified as
follows:The whole equation: (a1*x1 + a2*x2 +a3*x3 + a4*x4 + a5*x5 +
a22*(exp(a6*x6 + a7*x7 + a8*x9 + a9*x10 + a10*x11 + a11*x12 +
a14*x16)/(1+exp(a6*x6 + a7*x7 + a8*x9 + a9*x10 + a10*x11 + a11*x12 + a14*x16))))
The linear portion of the equation: a1*x1 + a2*x2 +a3*x3 + a4*x4 + a5*x5The
nonlinear portion of the equation: a22*(exp(a6*x6 + a7*x7 + a8*x9 + a9*x10 +
a10*x11 + a11*x12 + a14*x16)/(1+exp(a6*x6 + a7*x7 + a8*x9 + a9*x10 + a10*x11 +
a11*x12 + a14*x16)))The third equation is a logit with seven independent
variables.The first and the second equation have 12 variables while the third
equation have 7 variables. I did calculate my gradient from the moment
conditions which led to a 12 by 12 matrix for the first equation, a 12 by 12
matrix for the second equation and a 7 by 7 matrix for the third equation
because I have 12, 12, and 7 instruments for the three equations
respectively.Since it is estimated as a system of equations, I made it into a
block diagonal matrix which is a 31 by 31 matrix.
This is the matrix that I used in my optimx routine which gave me the error
message
Maximizing -- use negfn and neggrError: Gradient function might be wrong -
check it! In addition: Warning message:In gn - ga : longer object length is
not a multiple of shorter object length
When I used optim routine, I got a similar error messageError in optim(parm, fn
= obj, gr = gradient, method = "BFGS", hessian = TRUE) : gradient in optim
evaluated to length 1023 not 35
I used the numDeriv to compare my gradient with the numerical gradient and I
have the following error> require(numDeriv)> mygrad = gradient(parm)> numgrad =
jacobian(obj, parm)> cbind(mygrad,numgrad)Error in cbind(mygrad, numgrad) :
number of rows of matrices must match (see arg 2)> all.equal(mygrad,numgrad)[1]
"Attributes: < Length mismatch: comparison on first 1 components >"
"Attributes: < Component “dim”: Mean relative difference: 0.5625 >"[3]
"Numeric: lengths (1023, 35) differ"
A way forward will be appreciated.
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