[Limdep Nlogit List] Finding confidence intervals of WTA after LCRPLOGIT
Kolady, Deepthi Elizabeth P
deepthi.kolady at okstate.edu
Thu Mar 28 00:30:50 AEDT 2024
Hello Dr.Greene,
I use discrete choice data to estimate latent class-wise willingness to accept (WTA) values. I am using the LCRPLOGIT command because I would like to combine the random parameter logit model with the latent class model to account for heterogeneity. I am using the LCM command to use a variable of interest to determine class probability (in my case, the climate change concern scale).
I have attached my model estimation and results. I used this result to estimate class-wise WTA values. Can I estimate the confidence interval for WTA values using Krinsky and Robb's method after LCRPLOGIT estimation?
I can generate a K-density plot and show the distribution of class-wise or individual WTA, but as a reviewer asked, I need help figuring out how to get confidence intervals to report.
Thank you in advance for your help.
Sincerely,
Deepthi
-------------- next part --------------
|-> IMPORT;FILE="C:\Users\amrit\OneDrive\Desktop\Pramisha\data LCM (3).csv"$
Last observation read from data file was 6858
|-> LCRPLOGIT ; Lhs = yvec
; Choices = 1,2,3
; Rhs = price, none, constont, convtoct, convtont, noctocc,tencon, fivecon, nonprofi, private, governme
; Pds = 6
; Rpl ; Fcn = none (n), constont (n), convtoct (n), convtont (n), noctocc (n),tencon (n), fivecon (n), nonprofi (n), private (n), governme (n); Draws = 20 ; Halton
; LCM =ccscl; Pts = 2$
+------------------------------------------------------+
|WARNING: Bad observations were found in the sample. |
|Found 41 bad observations among 2286 individuals. |
|You can use ;CheckData to get a list of these points. |
+------------------------------------------------------+
Iterative procedure has converged
Normal exit: 5 iterations. Status=0, F= .2295341D+04
-----------------------------------------------------------------------------
Start values obtained using MNL model
Dependent variable Choice
Log likelihood function -2295.34134
Estimation based on N = 2245, K = 11
Inf.Cr.AIC = 4612.7 AIC/N = 2.055
---------------------------------------
Log likelihood R-sqrd R2Adj
Constants only -2390.1683 .0397 .0306
Note: R-sqrd = 1 - logL/Logl(constants)
Warning: Model does not contain a full
set of ASCs. R-sqrd is problematic. Use
model setup with ;RHS=one to get LogL0.
---------------------------------------
Response data are given as ind. choices
Number of obs.= 2286, skipped 41 obs
--------+--------------------------------------------------------------------
| Standard Prob. 95% Confidence
YVEC| Coefficient Error z |z|>Z* Interval
--------+--------------------------------------------------------------------
NONE| .98391*** .13597 7.24 .0000 .71741 1.25041
CONSTONT| -.42031*** .10316 -4.07 .0000 -.62251 -.21812
CONVTOCT| -.43842*** .10341 -4.24 .0000 -.64109 -.23574
CONVTONT| -.52237*** .10362 -5.04 .0000 -.72546 -.31927
NOCTOCC| -.07759 .07115 -1.09 .2755 -.21705 .06187
TENCON| -.63616*** .08483 -7.50 .0000 -.80242 -.46991
FIVECON| -.21314** .08380 -2.54 .0110 -.37739 -.04888
NONPROFI| .36301** .14279 2.54 .0110 .08314 .64287
PRIVATE| .29432* .16079 1.83 .0672 -.02082 .60946
GOVERNME| .52775*** .14949 3.53 .0004 .23475 .82074
PRICE| .06289*** .00731 8.60 .0000 .04855 .07723
--------+--------------------------------------------------------------------
***, **, * ==> Significance at 1%, 5%, 10% level.
Model was estimated on Feb 20, 2024 at 09:07:09 AM
-----------------------------------------------------------------------------
Line search at iteration 37 does not improve the function
Exiting optimization
-----------------------------------------------------------------------------
Latent Class Mixed (RP) Logit Model
Dependent variable YVEC
Log likelihood function -1988.56101
Restricted log likelihood -2466.38459
Chi squared [ 42](P= .000) 955.64716
Significance level .00000
McFadden Pseudo R-squared .1937344
Estimation based on N = 2245, K = 42
Inf.Cr.AIC = 4061.1 AIC/N = 1.809
---------------------------------------
Log likelihood R-sqrd R2Adj
No coefficients -2466.3846 .1937 .1861
Constants only -2390.1683 .1680 .1602
At start values -2287.0409 .1305 .1223
Note: R-sqrd = 1 - logL/Logl(constants)
Warning: Model does not contain a full
set of ASCs. R-sqrd is problematic. Use
model setup with ;RHS=one to get LogL0.
---------------------------------------
Response data are given as ind. choices
Replications for simulated probs. = 20
Used Halton sequences in simulations.
Number of latent classes = 2
Average Class Probabilities
.492 .508
LCM model with panel has 381 groups
Fixed number of obsrvs./group= 6
Number of obs.= 2286, skipped 41 obs
--------+--------------------------------------------------------------------
| Standard Prob. 95% Confidence
YVEC| Coefficient Error z |z|>Z* Interval
--------+--------------------------------------------------------------------
|This is THETA(01) in class probability model........................
_ONE|1| 1.05658** .43214 2.44 .0145 .20960 1.90357
_CCSCL|1| -.36602*** .13780 -2.66 .0079 -.63610 -.09593
|This is THETA(02) in class probability model........................
_ONE|2| 0.0 .....(Fixed Parameter).....
_CCSCL|2| 0.0 .....(Fixed Parameter).....
--------+--------------------------------------------------------------------
***, **, * ==> Significance at 1%, 5%, 10% level.
Fixed parameter ... is constrained to equal the value or
had a nonpositive st.error because of an earlier problem.
Model was estimated on Feb 20, 2024 at 09:09:19 AM
-----------------------------------------------------------------------------
-----------------------------------------------------------------------------
Mixed Logit Model Random Utility Class 1
--------+--------------------------------------------------------------------
| Standard Prob. 95% Confidence
YVEC| Coefficient Error z |z|>Z* Interval
--------+--------------------------------------------------------------------
|Random parameters in utility functions..............................
NONE| 1.79738*** .27210 6.61 .0000 1.26407 2.33070
CONSTONT| -1.00916*** .24835 -4.06 .0000 -1.49591 -.52241
CONVTOCT| -.87422*** .24285 -3.60 .0003 -1.35020 -.39824
CONVTONT| -.71212*** .22827 -3.12 .0018 -1.15953 -.26471
NOCTOCC| -.18461 .17928 -1.03 .3031 -.53599 .16677
TENCON| -1.31894*** .23823 -5.54 .0000 -1.78585 -.85202
FIVECON| -.47191** .20490 -2.30 .0213 -.87350 -.07032
NONPROFI| -.24968 .34279 -.73 .4664 -.92154 .42219
PRIVATE| -.43424 .40523 -1.07 .2839 -1.22847 .36000
GOVERNME| .03432 .36532 .09 .9251 -.68170 .75035
|Nonrandom parameters in utility functions...........................
PRICE| .09847*** .01787 5.51 .0000 .06345 .13349
|Distns. of RPs. Std.Devs or limits of triangular....................
NsNONE| .00332 .07391 .04 .9641 -.14154 .14818
NsCONSTO| .02130 .15127 .14 .8880 -.27517 .31778
NsCONVTO| .00781 .09594 .08 .9351 -.18024 .19585
NsCONVTO| .00781 .09594 .08 .9351 -.18024 .19585
NsNOCTOC| .00145 .10217 .01 .9887 -.19880 .20169
NsTENCON| .01758 .15828 .11 .9116 -.29265 .32781
NsFIVECO| .01025 .12718 .08 .9358 -.23902 .25951
NsNONPRO| .00012 .12589 .00 .9992 -.24662 .24686
NsPRIVAT| .01667 .14701 .11 .9097 -.27147 .30480
NsGOVERN| .02246 .11014 .20 .8385 -.19342 .23834
--------+--------------------------------------------------------------------
***, **, * ==> Significance at 1%, 5%, 10% level.
Model was estimated on Feb 20, 2024 at 09:09:19 AM
-----------------------------------------------------------------------------
-----------------------------------------------------------------------------
Mixed Logit Model Random Utility Class 2
--------+--------------------------------------------------------------------
| Standard Prob. 95% Confidence
YVEC| Coefficient Error z |z|>Z* Interval
--------+--------------------------------------------------------------------
|Random parameters in utility functions..............................
NONE| .21222 .21046 1.01 .3133 -.20027 .62471
CONSTONT| -.14869 .13920 -1.07 .2854 -.42152 .12414
CONVTOCT| -.13854 .13775 -1.01 .3145 -.40853 .13144
CONVTONT| -.23595* .14128 -1.67 .0949 -.51286 .04097
NOCTOCC| .18049* .09311 1.94 .0526 -.00200 .36299
TENCON| -.69544*** .11206 -6.21 .0000 -.91507 -.47581
FIVECON| -.39366*** .11470 -3.43 .0006 -.61847 -.16884
NONPROFI| .67366*** .17124 3.93 .0001 .33803 1.00929
PRIVATE| .24390 .19592 1.24 .2132 -.14009 .62789
GOVERNME| .61897*** .17562 3.52 .0004 .27476 .96318
|Nonrandom parameters in utility functions...........................
PRICE| .10705*** .01257 8.52 .0000 .08241 .13169
|Distns. of RPs. Std.Devs or limits of triangular....................
NsNONE| .00170 .08560 .02 .9842 -.16607 .16947
NsCONSTO| .00989 .08743 .11 .9099 -.16146 .18124
NsCONVTO| .00531 .06185 .09 .9316 -.11592 .12654
NsCONVTO| .00531 .06185 .09 .9316 -.11592 .12654
NsNOCTOC| .01575 .06649 .24 .8127 -.11457 .14607
NsTENCON| .02666 .08303 .32 .7481 -.13608 .18941
NsFIVECO| .01115 .08277 .13 .8929 -.15107 .17337
NsNONPRO| .00483 .08282 .06 .9535 -.15749 .16715
NsPRIVAT| .01847 .08589 .22 .8297 -.14987 .18682
NsGOVERN| .03388 .07943 .43 .6697 -.12180 .18956
--------+--------------------------------------------------------------------
***, **, * ==> Significance at 1%, 5%, 10% level.
Model was estimated on Feb 20, 2024 at 09:09:19 AM
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