[Limdep Nlogit List] Stochastic frontier with sample selection
Risto.Herrala at bof.fi
Risto.Herrala at bof.fi
Wed Feb 3 19:57:01 EST 2010
Hi all!
I am using the new 'stochastic frontier with selection' feature, and am constantly running into 'Error 806: (The log likelihood is flat at the current estimates.)'.
For example, a simple normal/half normal model without selection runs smoothly with the result:
--> FRONTIER; If[T=1988 & DLI=1 & W#-999];Lhs=L;Rhs=one,W; $ /*M1 in converge...
Normal exit from iterations. Exit status=0.....
+--------+--------------+----------------+--------+--------+----------+
|Variable| Coefficient | Standard Error |b/St.Er.|P[|Z|>z]| Mean of X|
+--------+--------------+----------------+--------+--------+----------+
---------+Primary Index Equation for Model
Constant| 3.25073849 .07065629 46.008 .0000
W | .27606220 .01554707 17.757 .0000 3.95278986
---------+Variance parameters for compound error
Lambda | 4.09604670 .25779771 15.889 .0000
Sigma | 2.07506813 .00098495 2106.774 .0000
The sample selection algorithm
--> Sample; All $
--> PROBIT; If[T=1988 & W#-999];Lhs=DLI;Rhs=one,W;Hold $
--> FRONTIER; If[T=1988 & W#-999];Lhs=L;Rhs=one,W; Output=3;Selection $
runs into trouble after four iterations. I have tried different algorithms, start values, samples (from alternative years, or subsamples of specific years), alternative specifications for the selection probit and the frontier. The log (from Output=3) suggests that 1) likelihood is not improving after four iterations 2) the gradient even increases slightly at 4th iteration. I am not certaint that I understand correctly what is in the parameter vector but it looks to me like some of the parameters in the covariance matrix are pretty erratic. I cannot interpret the end result as a satisfactory outcome since different start values for the main parameters lead to very different outcomes at abort.
Any suggestions about how to proceed? Is this a sign that the sampling model may be incorrect, and in fact there is no sampling issue in the data? Can I test the non-sample specification against a sampling correction without actually estimating the sampling corrected frontier model?
Risto
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