Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

zEconometrics > 10.) Heteroskedasticity > Flashcards

10.) Heteroskedasticity Flashcards

1
Q

Heteroskedasticity is the violation of…

A

Classical Assumption V, which states that the observations of the error term are drawn from a distribution tha thas a constant variance.

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

Heteroskedasticity is important because…

A

OLS, when applied to heteroskedastic models, is no longer the minimum variance estimator (it still is unbiased however)

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

Heteroskedasticity is more likely to take place in…

A

cross-sectional models than in time-series models.

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

Heteroskedasticity can be divided into…

A

pure and impure versions

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

Pure heteroskedasticity is caused by…

A

the error term of the correctly specified equation

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

Impure heteroskedasticity is caused by …

A

a specification error such as an omitted variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Pure heteroskedasticity refers to …

A

heteroskedasticity that is a function of the error term of a correctly specified regression equation

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

Pure heteroskedasticity occurs when…

A

classical assumption V, which assumes tha the variance of the error term is constant, is violated in a correctly specified equation

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

In homoscedasticity the error term has a constant variance, so..

A

the observation are continually drawn from the same distribution

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

The larger disparity between the size of observations of the dependent variable in a sample…

A

the larger the likelihood tha the error term observations associated with them will have different variances and therefore be heteroskedastic.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Discrete Heteroskedastic can be grouped visually into …

A

these two distributions “wide” & “narrow”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

The variable Z is called a …

A

proportionality factor because the variance of the error term changes proportionally to the square of Zi.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

The higher the value of Zi…

A

the higher the variance of the distribution of the ith observation of the error term.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Heteroskedastic distribution gets wider as…

A

Z increases

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Homoskedastic distribution…

A

maintains the same width no matter what value Z takes.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Heteroskedasticity is likely to occur in cross-sectional models because of..

A

the large variation in the size of the dependent variable involved.

17
Q

Heteroskedasticity can occur in a …

A

time-series model with a significant amount of change in the dependent variable

18
Q

Heteroskedasticity can occur in any model, where…

A

the quality of data collection changes dramatically within the sample.

19
Q

As data collection techniques get better, the …

A

variance of the error term should fall because measurement errors decrease in size, so should the variance of the error term

20
Q

Impure Heteroskedasticity…

A

is caused by an error in the specification, such as an omitted variable

21
Q

An omitted variable can cause a heteroskedasticy error term because…

A

the portion of the omitted effect not represented by one of the included explanatory variables must be absorbed by the error term

22
Q

Pure heteroskedastcity does not…

A

cause bias in the coefficient estimates

23
Q

Heteroskedasticty typically causes OLS to …

A

no longer be the minimum-variance estimator (of all the linear unbiased estimators)

24
Q

Heteroskedasticity cause the OLS estimates of the SE(B)S to be…

A

biased, leading to unreliable hypothesis testing.

25
Q

What sort of bias does heteroskedasticity tend to cause?

A

SE(B) is negative, OLS underestimates the size of the standard errors o the coefficients

26
Q

What’ll happen to hypothesis testing if OLS underestiamtes the SE(B)s and therefore overestimates the t-scores

A

The “too low” SE(Bhat) will cause a “too high” t-score for a particular coefficient

27
Q

The first thing to do if the Park test or the White test indicates…

A

the possibility of heteroskedasticy is to examine the equation carefully for specification errors

28
Q

If there are no obvious specification errors, the heteroskedastcity is probably,..

A

pure in nature

29
Q

The most popular remedy for heteroskedasticity is …

A

heteroskedastcity correct standard errors

30
Q

heteroskedastcity correct standard errors adjust for…

A

the SE(B) for heteroskedasticty while using the OLS estimates of the slope coefficients.

31
Q

The heteroskedastcity correct standard errors are…

A

SE(B)s that have been calculated specifically to avoid the consequences of heteroskedasticity.

32
Q

The HC procedure yields an…

A

estimator of the standard errors that, while they are biased, are generally more accurate than the

zEconometrics (16 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions