# 8.) Multicollinearity Flashcards

1
Q

Strictly speaking, perfect multicollinearity is the..

A

violation of Classical Assumption VI - that no independent variable is a perfect linear function of one or more other independent variables.

2
Q

Recall that the coefficient betak can be thought of as…

A

the impact on the dependent variable of a one-unit increase in the independent variable Xk holding constant the other independent variables in the equations.

3
Q

Perfect multicollinearity violates …

A

Classical Assumption VI, which specifies that no explanatory variable is a perfect linear function of any other variable.

4
Q

A perfect linear function has all data points..

A

on the same straight line.

5
Q

Perfect multicollinearity ruins our ability to…

A

estimate the coefficients because the two variables cannot be distinguished.

6
Q

Dominant Variable

A

is by definition related so highly correlated with the independent variable that it completely masks the effects of all other independent variables in the equation.

7
Q

Dominant variables should be recognized as..

A

being virtually identical to the dependent variable.

8
Q

imperfect Multicolinearity can be defined as…

A

a linear functional relationship between two or more independent variable that is so strong that it can significantly affect the estimation of the coefficients of the variable

9
Q

What are the consequences of multicolinearity?

A
1. ) Estimates will remain unbiased.
2. ) The variances and standard errors of the estimates will increase.
3. ) The computed t-scores will fall.
4. ) Estimates will become very sensitive to changes in specification.
5. ) The overall fit of the equation and the estimation of the coefficients of multicollinear variables will be largely unaffected.
10
Q

The main purpose in discussing multicollinearity is to learn to determine…

A

how much multicolinearity exists in an equation, not whether any multicolinearity exists.

11
Q

The severity of multicollinearity in a given equation can change from sample to sample …

A

depending on the characteristics of the sample

12
Q

The trick is to find variables that are…

A

theoretically relevant (for meaningful interpretation) and that are also statistically nonmulticolinear (for meaningful inference)

13
Q

Are there accepted tests to find multicolinearity?

A

No, there are none.

14
Q

The use of simple correlation coefficients as an indication of the extent of multicolinearity involves..

A

a major limitation if there are more than two explanatory variables.

15
Q

r is high if..

A

it causes unacceptably large variances in the coefficient estimates in which we’re interested.

16
Q

The variance inflation factor (VIF)

A

is a method of detecting the severity of multicollinearity by looking at the extent to which a given explanatory variable can be explained by all the other explanatory variables in the equation.

17
Q

There is a VIF for…

A

every explanatory variable in an equation.

18
Q

What are the steps for variance inflation factor (VIF)

A
1. ) Run an OLS regression that has Xi as a function of all the other explanatory variables in the equation
2. ) Calculate the variance inflation factor for beta hat i.