Seminars 1, 2 ,3 ,4 ,5, 6 ,7 Flashcards

1
Q

What questions should we put ourselves first when we first observe a regression?

A
  • About the variables: is there an economic theory on them?
  • About missing variables: is there any bias from omitted variables?
  • About linear specifications: is it advisable to have a linearizable form?
  • About indivitual significance of coefficient: what are the interpretation?
  • About multicollinearity: how can we avoid it?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is the purpose of an economic theory in analysing variables?

A

An economic theory helps us predict the ways in which variables depend on each other.

Ex: higher education results in higher pay

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What is ommited variable bias?

A

It occurs when a key independent variable is not included in the regression model, leading to an overestimation/understimation of that model.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What are some cases in which using the logaritmic function is a good ideea?

A
  • When we want to interpret values in percentages
  • When we want to solve for the asymmetry of the dependent variable
  • Residuals have a “strongly” positively skewed distribution
  • In the case in which we want to solve for heteroskedasticity
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What is perfect multicolinearity?

A

It occurs when two identical variables are expressed in different measurement units

Example: dummy trap

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

How can you check for correlation between two variables in Eviews?

A
  • Open the variables as a group
  • Click View -> Covariance analysis
  • Check only correlation box
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is near multicollinearity?

A

It occurs when there is a high correlation between the independent variables.

(>0.7 or 0.8)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

How should you build an optimal regression model?

A

Include independent variables that are highly correlated with the dependent but not among themselves.

If you discover a pair of highly correlated independent variables, remove the one with the lowest correlation with the dependent one.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are the thresholds for the p-value?

A
  • p<1% (***)
  • p>1%&<5% (**)
  • p>5%&<10% (*)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What does the R squared coefficent show?

And the R squared adjusted coefficient

A

The R-squared coefficient shows the degree to which the variance of the dependent variable is explained by the independent variables.

R-squared increases with the number of variables included in the model.

ex: For R-squared=0.5 : 50% of the variance in crime rate is explained by the predictors included in the model, while the rest of 50% is explained by other predictors not included in the model

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is the Adjusted R-squared coefficient?

A

Adjusted R-squared adds a penalty to account for the problem of R-squared.

Meaning that its value goes down as more variables are added.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly