Program mlogit

[bonnieclyde]

Hello,

First, sorry for my english (I'm french).
I have a problem with the writing of a mlogit program. When the program is running, the error "dd2 is not define" appear. I don't no why, and I don't know if the program is write correctly.
I have 12 variables :
dependent variable : pa (7 states)
predictor varibales : ges (4 states), infce (3 states), formace (3 states), mo (6 states), eqbat (3 states), eqmat (5 states), stru (4 states), surf (5 states), capt (3 states), mort (4 states).

The program is :

Code: Select all

' Chargement de la base de données "bpm" load "bpm" ' déclaration du vecteur des paramètres coef (11) b2 coef (11) b3 coef (11) b4 coef (11) b5 coef (11) b6 coef (11) b7 logl mlogit mlogit.append @logl logl1 mlogit.append xb2 = b2(1)+b2(2)*ges+b2(3)*infce+b2(4)*formace+b2(5)*mo+b2(6)*eqbat+b2(7)*eqmat+b2(8)*stru+b2(9)*surf+b2(10)*capt+b2(11)*mort mlogit.append xb3 = b3(1)+b3(2)*ges+b3(3)*infce+b3(4)*formace+b3(5)*mo+b3(6)*eqbat+b3(7)*eqmat+b3(8)*stru+b3(9)*surf+b3(10)*capt+b3(11)*mort mlogit.append xb4 = b4(1)+b4(2)*ges+b4(3)*infce+b4(4)*formace+b4(5)*mo+b4(6)*eqbat+b4(7)*eqmat+b4(8)*stru+b4(9)*surf+b4(10)*capt+b4(11)*mort mlogit.append xb5 = b5(1)+b5(2)*ges+b5(3)*infce+b5(4)*formace+b5(5)*mo+b5(6)*eqbat+b5(7)*eqmat+b5(8)*stru+b5(9)*surf+b5(10)*capt+b5(11)*mort mlogit.append xb6 = b6(1)+b6(2)*ges+b6(3)*infce+b6(4)*formace+b6(5)*mo+b6(6)*eqbat+b6(7)*eqmat+b6(8)*stru+b6(9)*surf+b6(10)*capt+b6(11)*mort mlogit.append xb7 = b7(1)+b7(2)*ges+b7(3)*infce+b7(4)*formace+b7(5)*mo+b7(6)*eqbat+b7(7)*eqmat+b7(8)*stru+b7(9)*surf+b7(10)*capt+b7(11)*mort mlogit.append denom = 1+exp(xb2)+exp(xb3)+exp(xb3)+exp(xb4)+exp(xb5)+exp(xb6)+exp(xb7) mlogit.append pr1 = 1/denom mlogit.append pr2 = exp(xb2)/denom mlogit.append pr3 = exp(xb3)/denom mlogit.append pr4 = exp(xb4)/denom mlogit.append pr5 = exp(xb5)/denom mlogit.append pr6 = exp(xb6)/denom mlogit.append pr7 = exp(xb7)/denom mlogit.append logl1 = (1-dd2-dd3-dd4-dd5-dd6-dd7)*log(pr1)+dd2*log(pr2)+dd3*log(pr3)+dd4*log(pr4)+dd5*log(pr5)+dd6*log(pr6)+dd7*log(pr7) ' Dérivées analytiques for !i=2 to 7 mlogit.append @deriv b!i(1) grad !i1 b!i(2) grad !i2 b!i(3) grad !i3 b!i(4) grad !i4 b!i(5) grad !i5 b!i(6) grad !i6 b!i(7) grad !i7 b!i(8) grad !i8 b!i(9) grad !i9 b!i(10) grad !i10 b!i(11) grad !i11 mlogit.append grad !i1 = dd!i-pr!i mlogit.append grad !i2 = grad !i1*ges mlogit.append grad !i3 = grad !i1*infce mlogit.append grad !i4 = grad !i1*formace mlogit.append grad !i5 = grad !i1*mo mlogit.append grad !i6 = grad !i1*eqbat mlogit.append grad !i7 = grad !i1*eqmat mlogit.append grad !i8 = grad !i1*stru mlogit.append grad !i9 = grad !i1*surf mlogit.append grad !i10 = grad !i1*capt mlogit.append grad !i11 = grad !i1*mort next ' Calculer les valeurs initiales à partir de Logit Binomiaux equation eq2.binary(d=1) dd2 c ges infce formace mo eqbat eqmat stru surf capt mort b2 = eq2.@coefs equation eq3.binary(d=1) dd3 c ges infce formace mo eqbat eqmat stru surf capt mort b3 = eq3.@coefs equation eq4.binary(d=1) dd4 c ges infce formace mo eqbat eqmat stru surf capt mort b4 = eq4.@coefs equation eq5.binary(d=1) dd5 c ges infce formace mo eqbat eqmat stru surf capt mort b5 = eq5.@coefs equation eq6.binary(d=1) dd6 c ges infce formace mo eqbat eqmat stru surf capt mort b6 = eq6.@coefs equation eq2.binary(d=1) dd7 c ges infce formace mo eqbat eqmat stru surf capt mort b7 = eq7.@coefs ' Estimation Max. de Vraissemblance et affichage résultats mlogit.ml(d) show mlogit.output

Is anybody can help me ? I'm inexperienced in programation and i found this program in a book.

Thanks

[startz]

Hello,

First, sorry for my english (I'm french).
I have a problem with the writing of a mlogit program. When the program is running, the error "dd2 is not define" appear. I don't no why, and I don't know if the program is write correctly.
I have 12 variables :
dependent variable : pa (7 states)
predictor varibales : ges (4 states), infce (3 states), formace (3 states), mo (6 states), eqbat (3 states), eqmat (5 states), stru (4 states), surf (5 states), capt (3 states), mort (4 states).

The program is :

Code: Select all

' Chargement de la base de données "bpm" load "bpm" ' déclaration du vecteur des paramètres coef (11) b2 coef (11) b3 coef (11) b4 coef (11) b5 coef (11) b6 coef (11) b7 logl mlogit mlogit.append @logl logl1 mlogit.append xb2 = b2(1)+b2(2)*ges+b2(3)*infce+b2(4)*formace+b2(5)*mo+b2(6)*eqbat+b2(7)*eqmat+b2(8)*stru+b2(9)*surf+b2(10)*capt+b2(11)*mort mlogit.append xb3 = b3(1)+b3(2)*ges+b3(3)*infce+b3(4)*formace+b3(5)*mo+b3(6)*eqbat+b3(7)*eqmat+b3(8)*stru+b3(9)*surf+b3(10)*capt+b3(11)*mort mlogit.append xb4 = b4(1)+b4(2)*ges+b4(3)*infce+b4(4)*formace+b4(5)*mo+b4(6)*eqbat+b4(7)*eqmat+b4(8)*stru+b4(9)*surf+b4(10)*capt+b4(11)*mort mlogit.append xb5 = b5(1)+b5(2)*ges+b5(3)*infce+b5(4)*formace+b5(5)*mo+b5(6)*eqbat+b5(7)*eqmat+b5(8)*stru+b5(9)*surf+b5(10)*capt+b5(11)*mort mlogit.append xb6 = b6(1)+b6(2)*ges+b6(3)*infce+b6(4)*formace+b6(5)*mo+b6(6)*eqbat+b6(7)*eqmat+b6(8)*stru+b6(9)*surf+b6(10)*capt+b6(11)*mort mlogit.append xb7 = b7(1)+b7(2)*ges+b7(3)*infce+b7(4)*formace+b7(5)*mo+b7(6)*eqbat+b7(7)*eqmat+b7(8)*stru+b7(9)*surf+b7(10)*capt+b7(11)*mort mlogit.append denom = 1+exp(xb2)+exp(xb3)+exp(xb3)+exp(xb4)+exp(xb5)+exp(xb6)+exp(xb7) mlogit.append pr1 = 1/denom mlogit.append pr2 = exp(xb2)/denom mlogit.append pr3 = exp(xb3)/denom mlogit.append pr4 = exp(xb4)/denom mlogit.append pr5 = exp(xb5)/denom mlogit.append pr6 = exp(xb6)/denom mlogit.append pr7 = exp(xb7)/denom mlogit.append logl1 = (1-dd2-dd3-dd4-dd5-dd6-dd7)*log(pr1)+dd2*log(pr2)+dd3*log(pr3)+dd4*log(pr4)+dd5*log(pr5)+dd6*log(pr6)+dd7*log(pr7) ' Dérivées analytiques for !i=2 to 7 mlogit.append @deriv b!i(1) grad !i1 b!i(2) grad !i2 b!i(3) grad !i3 b!i(4) grad !i4 b!i(5) grad !i5 b!i(6) grad !i6 b!i(7) grad !i7 b!i(8) grad !i8 b!i(9) grad !i9 b!i(10) grad !i10 b!i(11) grad !i11 mlogit.append grad !i1 = dd!i-pr!i mlogit.append grad !i2 = grad !i1*ges mlogit.append grad !i3 = grad !i1*infce mlogit.append grad !i4 = grad !i1*formace mlogit.append grad !i5 = grad !i1*mo mlogit.append grad !i6 = grad !i1*eqbat mlogit.append grad !i7 = grad !i1*eqmat mlogit.append grad !i8 = grad !i1*stru mlogit.append grad !i9 = grad !i1*surf mlogit.append grad !i10 = grad !i1*capt mlogit.append grad !i11 = grad !i1*mort next ' Calculer les valeurs initiales à partir de Logit Binomiaux equation eq2.binary(d=1) dd2 c ges infce formace mo eqbat eqmat stru surf capt mort b2 = eq2.@coefs equation eq3.binary(d=1) dd3 c ges infce formace mo eqbat eqmat stru surf capt mort b3 = eq3.@coefs equation eq4.binary(d=1) dd4 c ges infce formace mo eqbat eqmat stru surf capt mort b4 = eq4.@coefs equation eq5.binary(d=1) dd5 c ges infce formace mo eqbat eqmat stru surf capt mort b5 = eq5.@coefs equation eq6.binary(d=1) dd6 c ges infce formace mo eqbat eqmat stru surf capt mort b6 = eq6.@coefs equation eq2.binary(d=1) dd7 c ges infce formace mo eqbat eqmat stru surf capt mort b7 = eq7.@coefs ' Estimation Max. de Vraissemblance et affichage résultats mlogit.ml(d) show mlogit.output

Is anybody can help me ? I'm inexperienced in programation and i found this program in a book.

Thanks

This may be an obvious question, but do you have a series named "dd2" in the workfile?
(By the way, your English is pretty good!)

[bonnieclyde]

No, i haven't a serie named "dd2". I don't know what "dd2" means.
It's seams to be used in order to specify likelihood

[startz]

No, i haven't a serie named "dd2". I don't know what "dd2" means.
It's seams to be used in order to specify likelihood

Ah, dd2 is a variable in the workfile for which the example program was written. It doesn't have anything to do with general issue of specifying the log-likelihood.

[bonnieclyde]

I found the problem. I'm going to explain it, maybe someone will need to know.
Because of mlogit doesn't exist, the program is made on the model of binomial logit. The dependent variable has to be change in binary data. Then, dd2=1 if the individual has the second state of the dependent variable, if not, dd2=0.
I don't know if it's understanding (because of my bad english)....

Thanks startz for your answer

[thinhlien]

Hi bonnieclyde,

First, I am sorry for my bad English too.

I am now learning how to write an eviews program and facing the same problem with mlogit program.

I don't understand d1, d2, d3 and dd2, dd3 in the workfile mlogit of Eviews book.

I read your explanations about dd but still can't understand.

could you pls explain it in details for me?

Thanks alot.

thinhlien.

[trubador]

In order to carry out a multinomial logit analysis, one category of the dependent variable has to be chosen as the comparison (or reference) category. After that, you should define binary variables for the remaining categories (similar to constructing a dummy variable). dd2 and dd3 are these binary variables and created from a dependent variable that has 3 different categories (for details please see the reference book mentioned in the beginning of the sample program).

[thinhlien]

Thank you very much, Trubador!

I will try to read the reference book as you suggested. If I still face difficulties, pls allow me to ask you.

Sincerely thanks,
thinhlien.

[thinhlien]

Dear Trubador,

I already read your suggested reference book and could understand a little bit. Thanks alot.

This is my problem. I would like to investigate how the real output (regressor X1) and inflation rate (regressor X2) affect the mechanism of monetary policy (dependent variable Y). Thus, there are 3 cases: (1) a decrease in interest rate (or an expansionary monetary policy); (2) an increase in interest rate (or a tightened monetary policy) (3) no change in interest rate (or a neutral monetary policy). All my data are time series data (quarterly data, from 1999q1 to 2008q4)

In this case, I determine dd2 for an expansionary monetary policy; dd3 for a tightened monetary policy and dd1 for a neutral policy as follows:
Quarter intrate1 dd2 dd3
1999Q1 12.00 0.00 0.00
1999Q2 9.60 1.00 0.00
1999Q3 8.40 1.00 0.00
1999Q4 6.00 1.00 0.00
2000Q1 6.00 0.00 0.00
2000Q2 5.40 1.00 0.00
2000Q3 5.40 0.00 0.00
2000Q4 6.00 0.00 1.00

for the first period (1999q1) I assume that dd2=dd3=0.

Then dd1 is determined = 1 - dd2 - dd3

Is the above description correct? Could you pls help me with the determination of dd2, dd3 for my program?

Once again, thank you very much.

Best regards,
thinhlien.

[trubador]

Yes, your binary variables seem correct.

[thinhlien]

Thanks alot, dear kind Trubador!!!

I will try to run the program now. I wish to consult you next time also.

Wish you all the best,
thinhlien

[thinhlien]

Dear Trubador,

I have just run the program and got the results. Now I have to study how to read and explain the results. I just know how to read OLS regression result: based on the p-values, the size and sign of coefficients, the Durbin Watson stat,... For LogL maximization, should we base on p-values to conclude? (I got all the p-values which are bigger than 5% even 10%, unfortunately). What are the important bases for us to conclude?

Could you pls consult me how to interpret the results of LogL maximization problem? Or could you pls suggest me any reference book?

Thank you very much for your kindness.
thinhlien.

[trubador]

Any of these Textbooks or Books using EViews might be helpful. You can search the forum as well.

[thinhlien]

Thanks alot, dear Trubador!!!

I study alot from you and this forum! Hope to receive ur help next time!

Best regards,
thinhlien