EViews.com

I'm very new and I have the a problem.
At the Equation Estimation Tab, How can I command Eviews not to estimate coefficient on the variable X here (2 places) ??
You can see in the below picture. Because when I press spacebar in my keyboard, Eviews always assign the coefficient value on that point.
How can I write the command for this model.
This is my final research on master degree, and it's very difficult for me who is not familiar with Eviews. Thank you so much for your kindness.

if you want estimate

Hello,

You can also use an explicit equation specification to control which coefficients are estimated, e.g.,

Hello,

You can also use an explicit equation specification to control which coefficients are estimated, e.g.,

Code: Select all

industry_excess_return = c(1) * (1-betamarketexcess) + c(2) * Betafs + betamarketexcess*MARKET_EXCESS_RETURN + Betafs*fswhole

Matt's solution is better, as it works easily even for a more complicated equation. Do note that the two methods give different R^2 and you may want to think about which one is appropriate.

Matt's solution is better, as it works easily even for a more complicated equation. Do note that the two methods give different R^2 and you may want to think about which one is appropriate.

Assuming you care about R^2 :D

I have tried both solution from Startz and Matt. For me, Matt's solution seems to be easier since I just type the command accordingly. While startz's solution, I have to subtract the variable (I do it in excel file and copy to eviews as a serie of variable), then run the equation accordingly.

Somehow, I found the very different R-squared. I just think basically that Eviews should give me the same result since it just the 2 different in method to type command in the Eviews. And, I just wonder whether I can use only Matt's solution to go another final step. The final step is that I have to run the chi-square goodness of fit statistic is computed using the restricted and unrestricted models (likelihood ratio statistics).

And, I just noticed that the original research paper, which I'm studying, does not talk about R-squared at all. So, I think that it might not be important for this case.

Again thank you all for your help. :)

The difference in R^2 is because you are changing the variance of the dependent variable. Note that the coefficients, t-statistics, etc., are the same.