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I’m currently trying to estimate a model on panel data that should look like
y = c(1) + c(2)*x + c(3)*(composite)
with composite being the "best" weighted average of 4 indicators (a, b, d, e). Thus, compo should be of the form
compo = c(4)*a + c(5)*b + c(6)*d +c(7)*e
with 0 < c(4), c(5), c(6), c(7) < 1 and c(4)+c(5)+c(6)+c(7) = 1
I’ve looked at the above but it does not seem to work, results are quite strange… Any idea ?

Hallo,

I have tried to use the logistic transformation, i.e. (H-L)*@logit(c(1)) + L, to estimate a two-sided restricted parameter within a State Space framework, but I always get the same error message "WARNING: Singular covariance - coefficients are not unique". More specifically

{%model}_ss.add @STATE sv1 = sv1(-1)+ (0.4*@logit({%theta1})+0.3)*d(ltu)+[VAR = {%varstate}]

where H=0.7, L=0.3 and %varstate is equal to an assigned specific value.
The same error message is produced also in case of the one-sided restriction transformation (0.7-exp({%theta1}))*d(ltu). It is not necessarily linked to the weakness of SS models to treat nonlinearities because both the logistic and the exponential transformations can be correctly solved. Hence, I was wondering what is the reason and the solution.
Thanks in advance.

I was wondering what is the reason and the solution.

Hard to say without seeing the workfile. But you should consider the possibility that data strongly disagrees with your constraint.

HI All,

I would like to put a restriction on one of the coefficients that it is equal to 1.

So Y1 = a + b Y2 + c X2 where b=1.

But what I was wondering is, if I run the regression

Y1-Y2 = a + c X2

Does this regression above impose the restriction that b=1? - Im pretty sure it does, but it would be great if I could get some confirmation.

Cheers,
Andrew.

You got it right.

Hi All,

Is it possible to force c(1) = 1 in the following equation, and how could one do it?

Y = c(1)*Y(-1)*(X/X(-1))

Thanks!

If you do that there is nothing left to estimate...

Right. But if I do the following,

sample large 2014q2 2024q2
smpl large
series X = (@pch(Y)+1)*X(-1)

it performs the calculation for the first time period. How do I get it to perform this calculation for all other periods?

Thank you so much!

If you are generating the variable Y, rather than running an estimate, try
taking some care about the sample to avoid NAs from being propagated.

Oh yes, thank you!

Hi, this still doesn't work for some reason. Please help!

I am trying to do something simple. I have quarterly series, call it X, for period 2014q1 to 2018q4. I would like to make series Y by using series X's percent change. I only have one observation on Y, 2014q1.

I set my sample to 2014q1 - 2018q4.

If I try to do this

series y = (x/x(-1))*y(-1), I get only one value for y for 2014q2, the rest is NA. The same happens when I use 'genr' instead of 'series'.

What am I doing wrong?

Thanks so much!

You may want to post your workfile.

Thank you so much! Here is the workfile.

set your sample to

Oh, I can't thank you enough! That worked. Thanks, again.