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On more thing trubador (sorry to rebump old thread): My restricted model which has data from all three seasons has 16 parameters whereas each season modelled separately has 14 (since we drop the 2 season dummies when modelling each season separately). Therefore on the first line of code ( scalar dof...

Okay so what you're saying is the pooled regression is the restricted one because we re imposing the restriction that the coefficient for each variable is the same across each season. Whereas, in the unresticted one it is because we are allowing the parameters to vary across the seasons?

FIRSTLY- thank you for replying I promise I'll try not to bother you, but this actually the last thing I need help with. Your reply and help is very useful and appreciated!!! Forigive me for my stupidity but is what you are trying to say we have for example 20 variables for the pooled regression (se...

Thank you ever so much for replying that clears things up but just one thing. Shouldn't the restricted model be when we model each season sepretely and then add up the likilhoods (this is because in these models we are imposing that the season dummy variables are=0). From this, the unrestricted mode...

Bump, still can't find the Null of a LR test in my case...

No, that is valid for a single model where you restrict the coefficients of variables of interest. In your case, you have 3 models with m variables. So, as I clearly indicated in the code, the degrees of freedom should be (3-1)*m. You already compute the probability, so you do not need the critical...

You cannot use Chow test here, because the result of F-test is no longer valid in this context. What your supervisor suggests is called Likelihood Ratio (LR) test. In the first step, you fit the restricted model to data from all three seasons and get the log likelihood (e.g. Rlogl). Next, estimate ...

In short, I'm running a probit regression on whether a team was given a penalty kick decision and using it to investigate whether social pressures such as the audience have an effect on referee's in the awarding of penalty kicks. I want to test for parameter stability since the I've collected data f...

Hi, I'm currently trying to run a regression which determines what affects penalty kick decisions. I've only just found out that because I'm modelling for penalty or no penalty it is bes to use a probit estimation instead of least squares. My issue is that if I do for example run such a regression, ...