Intro. Econometrics Assignment

[twatter]

alright, too easy, thanks man

[Sam_95]

goddamn, just started the assignment tonight too.

For 1d. did you guys just use the same regression as you did in 1c. and then do the wald test for the hypothesis test?

[Sam_95]

Later in the assignment there are regressions where you need constant term in there. You leave out sp100 for those ones.

would that be for Question 2, cause I'm getting that error too, unless I drop a regressor

[kinslayer]

would that be for Question 2, cause I'm getting that error too, unless I drop a regressor

Ya you can't include all the dummy variables and the constant. Still haven't started it, but lecturer (and my tutor) told me to drop sp100 for Q2 onwards

[UBS]

In Q2b. What does it mean when it asks 'Use this interval to test whether B1 differs significantly from one'?

Is it asking whether the coefficient of Sp100 (B1) in Q1 differs significantly to B1 in Q2? If so, how do go about finding that?

[twatter]

In Q2b. What does it mean when it asks 'Use this interval to test whether B1 differs significantly from one'?

Is it asking whether the coefficient of Sp100 (B1) in Q1 differs significantly to B1 in Q2? If so, how do go about finding that?

yeah confused about that question myself, terribly worded

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with 2c. it's asking to compute a 95% PI, with risk of 4% - but for small companies fund

I think you'd change the equation (tr_err - 0.4)...but what's the other step in order to make sure you get answers for a small companies fund?

[Reckoner]

In Q2b. What does it mean when it asks 'Use this interval to test whether B1 differs significantly from one'?

Is it asking whether the coefficient of Sp100 (B1) in Q1 differs significantly to B1 in Q2? If so, how do go about finding that?

I interpreted it as you're effectively testing the null that B1=1, and using the interval to do so.

with 2c. it's asking to compute a 95% PI, with risk of 4% - but for small companies fund

I think you'd change the equation (tr_err - 0.4)...but what's the other step in order to make sure you get answers for a small companies fund?

Remember, think of the intercept as a point prediction for the return when all of the regressors are equal to 0. So we need to transform certain variables so that the intercept tell us the point prediction when the transformed variabels are equal to 0. So if the model is Wage = B0 + B1age + B2education; the intercept would give a point prediction for a when education=0 and age=0.

So if we want to do a point prediction for when age = 40, we do the transformation age'=age-40. As such when we estimate Wage = B0 + B1age' + B2education, the intercept will give us the point prediction for when age'=0 and education = 0.

Note that when
age'=0
age-40=0
age=40

So the point prediction for age' being 0 is really a point prediction for age being equal to 40.

See if you can use this template to help with figuring out what to do for your questions (ie change the variables names). (hint: what value of the variable small do we want to make a prediction for?)

Hopefully this helps you get to the answer, if you're still confused maybe I'll be less vague if you ask again (or someone a bit nicer will answer for you )

Edit, changed variable names in example

[twatter]

ohh right, in this case, dealing with dummy variables, the small and risk components of the equation will be changed to be 'small-1' & tr_err - 0.4

[kinslayer]

If you have a confidence interval for a population parameter that means that any point estimate within that interval would be significant at the same significance level.

So if the confidence interval you found for β₁ contains 1, then...

[Sam_95]

for Q2d. the marginal effect, of an additional 2 percentage points of risk, did you guys just change the risk & small components of the reg. to (TR_ERR-0.4)/2 and small - 1?

And to construct the 95% PI, just look at the coeff. & std.error of (TR_ERR-0.4)/2?

[UBS]

wait, why are you guys doing 0.4? isn't the the 4% just going to be tr_err - 4?

gaah, so stuck on Q2d.  I know we did marginal effect in tutes last week, but we only looked at quadratic & log regressions...not the basic regression.

[twatter]

Completely stumped with finding the regression in Q3. No idea what to do, other than obviously including the 'conc' dummy variable somewhere.

Someone pleasee help!!

[twatter]

someone...anyone!

[kinslayer]

include conc and conc*tr_err dummy variables like in tutorial 7/8 or whatever it was

I dunno what to put for 4.d). for i) I have something about how the effect is linear in the first case but in the second case it's logarithmic, i.e. increasing risk will increase returns but relative to the return you already have.. for ii) I'm not sure... the intervals overlap, and I got that the second one was slightly narrower, giving a 'better' prediction? for iii) no idea. We can't use R^2, not sure whether just using Schwarz criterion is okay.

[Sam_95]

We can use R-squared can't we given we have the same number of explanatory variables in reg. 1 & 2? (If not, look at the adjusted R-squared)I used the Schwarz criterion criteria as well, that should be enough.

And seriously guys...is it TR_ERR-0.4 or TR_ERR- 4 for Q2c. That's doing my head in!