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Hello,

I have a question about the restriction of a coefficient.
I need to regress a CCEP-estimator:
wgo is the employment rate of older people, d1 ... d16 are dummies for country 1 to 16, mwgo is the cross sectional mean of the employment rate. Cons is for example the consumtion tax.

wgo cons d1 d2 d3 d4 d5 d6 d7 d8 d9 d10 d11 d12 d13 d14 d15 d16 d1*mwgo d2*mwgo d3*mwgo d4*mwgo d5*mwgo d6*mwgo d7*mwgo d8*mwgo d9*mwgo d10*mwgo d11*mwgo d12*mwgo d13*mwgo d14*mwgo d15*mwgo d16*mwgo c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons c(x)*mcons

Now i need to restric c(x) to be equal to a certain value, say 0.5, how do you do this?

I will be grateful for any help you can provide,

Kind regards

So that in your regression output, you see that the impact of mcons on wgo is equal to say 0.5

If you want with the coefficient of x2=7 (or whatever), use

Thanks, but this works but it is not what i am looking for

I want to estimate this in EViews 9:
To estimate : Y
For simplicity, one variable: X
Y=c(2)*X
+dum1*(c(10)+c(11)*Y_av+c(11)*c(2)*X_av)
+dum2*(c(20)+c(21)*Y_av+c(21)*c(2)*X_av)
+dum3*(c(30)+c(31)*Y_av+c(31)*c(2)*X_av)
+dum4*(c(40)+c(41)*Y_av+c(41)*c(2)*X_av)
+dum5*(c(50)+c(51)*Y_av+c(51)*c(2)*X_av)
+dum6*(c(60)+c(61)*Y_av+c(61)*c(2)*X_av)
+dum7*(c(70)+c(71)*Y_av+c(71)*c(2)*X_av)
+dum8*(c(80)+c(81)*Y_av+c(81)*c(2)*X_av)
+dum9*(c(90)+c(91)*Y_av+c(91)*c(2)*X_av)
+dum10*(c(100)+c(101)*Y_av+c(101)*c(2)*X_av)

So I did this (now for 16 countries: 16 dummies) and I put this in my eviews command: (but it gives "near singular matrix")

ls wgl c(2)*mbwgl d1*(c(10)+c(11)*mwgl+c(11)*c(2)*mmbwgl) +d2*(c(20)+c(21)*mwgl+c(21)*c(2)*mmbwgl) +d3*(c(30)+c(31)*mwgl+c(31)*c(2)*mmbwgl) +d4*(c(40)+c(41)*mwgl+c(41)*c(2)*mmbwgl) +d5*(c(50)+c(51)*mwgl+c(51)*c(2)*mmbwgl) +d6*(c(60)+c(61)*mwgl+c(61)*c(2)*mmbwgl) +d7*(c(70)+c(71)*mwgl+c(71)*c(2)*mmbwgl) +d8*(c(80)+c(81)*mwgl+c(81)*c(2)*mmbwgl) +d9*(c(90)+c(91)*mwgl+c(91)*c(2)*mmbwgl) +d10*(c(100)+c(101)*mwgl+c(101)*c(2)*mmbwgl) +d11*(c(110)+c(111)*mwgl+c(111)*c(2)*mmbwgl) +d12*(c(120)+c(121)*mwgl+c(121)*c(2)*mmbwgl) +d13*(c(130)+c(131)*mwgl+c(131)*c(2)*mmbwgl) +d14*(c(140)+c(141)*mwgl+c(141)*c(2)*mmbwgl) +d15*(c(150)+c(151)*mwgl+c(151)*c(2)*mmbwgl) +d16*(c(160)+c(161)*mwgl+c(161)*c(2)*mmbwgl)

Can someone explain why I can't compute this regression?

Dummy variable trap?