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Hello,

Could you please assist with the following query.

I have estimated a state space and used a probit function to constrain the coefficient c(1) to below 1. I understand that the estimate of c(1) must be transformed in order to back out beta, using the following transformation: beta=(1/(1+exp(c(1))).

What I am not sure is whether the same transformation can be applied to transform the standard errors. I found that when doing this, the transformed standard errors are very small, even though the coefficients are insignificant, so I suspect this approach may not be correct. Could you please advise on how to back out the standard errors?

Many thanks in advance!

It’s a touch messy. Basically var(f(b)) = f’(b)var(b)f’(b), where f’ means first derivative.

Probably the easiest way to get the standard error is to look under coefficient,views,wald test and test

Thanks for the advice. I have tried this approach but have run into an issue - it produces a standard error which seems very low, considering the coefficient is insignificant.

The results show that: beta=0.99; SE=0.087, p-value = 0.74

Since beta has been constrained to below 0.95, the p-value result seems fine, but the low standard error doesn’t appear credible. Is there any other way the standard error can be transformed within Eviews to double check the result?

I attach the workfile. Please see tab ‘2024’ > state space object ‘ss_0’ > results for c(1) and saved ‘wald_test’ as per your suggestion.

I think you've done everything correctly. But you may be misinterpreting significance.

Suppose c(1) is almost exactly zero, so not "significant." Then

1/(1+exp(c(1))) = 1/(1+e^0)=1/(1+1) = 0.5

which is significantly different from zero.