[Limdep Nlogit List] confidence intervals
Caroline Johanna Biehl
Caroline-Johanna.Biehl at gmx.de
Fri Nov 28 23:25:32 EST 2008
Thank you very much!
I tried the first command you sent and it worked very well. Sorry for asking some few more questions...
- according to the results the confidence intervals for WTP for la2 are for example:
3.19365901 -0.15632744320738740 and 3.19365901+0.48240435955084390 -->is that ok,they do not vary much is that ok?
- i tried it for my basic model without interactions. does it make a difference when i include interactions and alternative specific variable?
Thank you,
kind regards,
caroline
?Basic model without interactions
matrix; b1=b(1:9);
varb1=varb(1:9,1:9)$ ? where parameter 8 is monetary
--> wald; start=b1; var=varb1; labels=la1,la2,la3,la4,la5,la6,la7,la8,la9; pt...
fn1=la1/-la8;
fn2=la2/-la8;
fn3=la3/-la8;
fn4=la4/-la8;
fn5=la5/-la8;
fn6=la6/-la8;
fn7=la7/-la8;
fn8=la9/-la8$
+-----------------------------------------------+
| WALD procedure. Estimates and standard errors |
| for nonlinear functions and joint test of |
| nonlinear restrictions. |
| Wald Statistic = 59.29035 |
| Prob. from Chi-squared[ 8] = .00000 |
+-----------------------------------------------+
+---------+--------------+----------------+--------+---------+
|Variable | Coefficient | Standard Error |b/St.Er.|P[|Z|>z] |
+---------+--------------+----------------+--------+---------+
Fncn(1) 4.31877554 .86729487 4.980 .0000
Fncn(2) 3.19365901 .83182887 3.839 .0001
Fncn(3) 5.58142725 1.34115924 4.162 .0000
Fncn(4) 2.99220987 .94987736 3.150 .0016
Fncn(5) 2.55705922 .78202319 3.270 .0011
Fncn(6) 2.25837620 .72111477 3.132 .0017
Fncn(7) 5.18089119 1.29777437 3.992 .0001
Fncn(8) -2.19753703 .49537136 -4.436 .0000
--> CALC ; List ;
; WTP01_hi = WALDFNS(1,1) + ((Sqr(VARWALD(1,1))*1.96))
; WTP01_lo = WALDFNS(1,1) - ((Sqr(VARWALD(1,1))*1.96))
; WTP02_hi = WALDFNS(2,1) + ((Sqr(VARWALD(2,2))*1.96))
; WTP02_lo = WALDFNS(2,1) - ((Sqr(VARWALD(2,2))*1.96))
; WTP03_hi = WALDFNS(3,1) + ((Sqr(VARWALD(3,3))*1.96))
; WTP03_lo = WALDFNS(3,1) - ((Sqr(VARWALD(3,3))*1.96))
; WTP04_hi = WALDFNS(4,1) + ((Sqr(VARWALD(4,4))*1.96))
; WTP04_lo = WALDFNS(4,1) - ((Sqr(VARWALD(4,4))*1.96))
; WTP05_hi = WALDFNS(5,1) + ((Sqr(VARWALD(5,5))*1.96))
; WTP05_lo = WALDFNS(5,1) - ((Sqr(VARWALD(5,5))*1.96))
; WTP06_hi = WALDFNS(6,1) + ((Sqr(VARWALD(6,6))*1.96))
; WTP06_lo = WALDFNS(6,1) - ((Sqr(VARWALD(6,6))*1.96))
; WTP07_hi = WALDFNS(7,1) + ((Sqr(VARWALD(7,7))*1.96))
; WTP07_lo = WALDFNS(7,1) - ((Sqr(VARWALD(7,7))*1.96))
; WTP08_hi = WALDFNS(8,1) + ((Sqr(VARWALD(8,8))*1.96))
; WTP08_lo = WALDFNS(8,1) - ((Sqr(VARWALD(8,8))*1.96))
$
= .00000000000000000D+00
WTP01_HI= .60186734759887110D+01
WTP01_LO= .26188775956936310D+01
WTP02_HI= .48240435955084390D+01
WTP02_LO= .15632744320738740D+01
WTP03_HI= .82100993686122940D+01
WTP03_LO= .29527551289163540D+01
WTP04_HI= .48539694942756940D+01
WTP04_LO= .11304502495498310D+01
WTP05_HI= .40898246750262330D+01
WTP05_LO= .10242937587840950D+01
WTP06_HI= .36717611534372210D+01
WTP06_LO= .84499123784393900D+00
WTP07_HI= .77245289617620880D+01
WTP07_LO= .26372534160408200D+01
WTP08_HI= -.12266091594742700D+01
WTP08_LO= -.31684648985403690D+01
Calculator: Computed 17 scalar results
-------- Original-Nachricht --------
> Datum: Fri, 28 Nov 2008 11:23:04 +0100
> Von: "Mikołaj Czajkowski" <miq at wne.uw.edu.pl>
> An: Limdep and Nlogit Mailing List <limdep at limdep.itls.usyd.edu.au>
> Betreff: Re: [Limdep Nlogit List] confidence intervals
> Caroline Johanna Biehl wrote:
> > Dear all,
> > I try to estimate confidence intervalls for willingsness to pay
> estimates of a mnl model. Is there a command in nlogit for the krisky and robb
> (1986)-parametric bootstrapping or anything else similar?
> > Thank you very much!
> > Caroline
>
> You can get confidence intervals for WTP using the delta method with the
> wald command, e.g. like this:
>
> matrix; b1=b(1:4);
> varb1=varb(1:4,1:4)$ ? where parameter 4 is monetary
>
> wald; start=b1; var=varb1; labels=la1,la2,la3,la4; pts=10000;
> fn1=la1/-la4;
> fn2=la2/-la4;
> fn3=la3/-la4$
>
> CALC ; List ;
> ; WTP01_hi = WALDFNS(1,1) + ((Sqr(VARWALD(1,1))*1.96))
> ; WTP01_lo = WALDFNS(1,1) - ((Sqr(VARWALD(1,1))*1.96))
> ; WTP02_hi = WALDFNS(2,1) + ((Sqr(VARWALD(2,2))*1.96))
> ; WTP02_lo = WALDFNS(2,1) - ((Sqr(VARWALD(2,2))*1.96))
> ; WTP03_hi = WALDFNS(3,1) + ((Sqr(VARWALD(3,3))*1.96))
> ; WTP03_lo = WALDFNS(3,1) - ((Sqr(VARWALD(3,3))*1.96))$
>
> The same is possible with additional ; K&R switch in the wald command.
> This will simulate draws from the structural parameters, but the upper
> and lower bounds of the confidence intervals are again derived assuming
> normal distribution (i.e. using 1.96 critical value).
>
> Alternatively I use the following procedure to get c.i. without the
> normality assumption (however, the draws are still from multivariate
> normal):
>
> matrix; reset$
> matrix;
> B1=B(1:4); ? manipulate these matrices to get K&R for only the
> variables you want
> VARB1=VARB(1:4,1:4); ? useful to cut b and varb for big n, if the
> matrix size would exceed 50000 cells
> T2=init(10000,4,0)$ ? change n for no. of trials and 4 for no. of
> variables to keep (including cost)
> calc; ran(179424673);
> cont=1$
>
> Proc
> matrix; coef=Rndm(B1,VARB1);
> T1=coef'*{-1/coef(4)}; ? adjust 4 if necessary
> T2(cont,*)=T1;
> cont=cont+1$
> endproc
> execute; n=10000$
>
> create; a1=0;a2=0;a3=0;a4=0$
> namelist; CIV=a1,a2,a3,a4$
> create; CIV=T2$
> dstats; rhs=CIV;all;quantiles;normality test;matrix$
>
> calc; list; qnt(a1,.05);
> qnt(a1,.95);
> qnt(a2,.05);
> qnt(a2,.95);
> qnt(a3,.05);
> qnt(a3,.95)$
>
> The results of all the methods should be quite similar for most
> applications.
>
> Best regards,
>
> --
> Mikołaj Czajkowski
>
> Warsaw Ecological Economics Center
> Warsaw University
> http://www.woee.pl/
> _______________________________________________
> Limdep site list
> Limdep at limdep.itls.usyd.edu.au
> http://limdep.itls.usyd.edu.au
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