Econometrics Quiz: Heteroscedasticity

Welcome to your Econometrics Quiz: Heteroscedasticity

Total MCQs: 28

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Name

Which of the following is NOT a source of heteroscedasticity?

Select the correct answer.

Cross-sectional data

Correct model specification

Skewness in regressors

Outliers

None

Comment

Hint

If the variance of the error term increases as the value of X increases, this is an example of:

Identify the phenomenon.

Heteroscedasticity

Multicollinearity

Autocorrelation

Homoscedasticity

None

Comment

Hint

Which estimator remains unbiased in the presence of heteroscedasticity?

Choose the correct answer.

OLS

None

WLS

Both OLS and WLS

None

Comment

Hint

In the presence of heteroscedasticity, OLS estimators are:

Choose the correct property of OLS estimators.

Biased and efficient

Unbiased but inefficient

Biased and inefficient

Unbiased and efficient

None

Comment

Hint

In the classical linear regression model, what does homoscedasticity mean?

Choose the correct meaning of homoscedasticity.

Variance of error terms is increasing with X

Variance of error terms is constant

Errors have non-zero mean

Errors are correlated

None

Comment

Hint

In the presence of heteroscedasticity, the variance of OLS estimators is:

Identify the effect.

No longer minimum

Always zero

Minimum

Maximum

None

Comment

Hint

The main difference between WLS and GLS is:

Choose the correct distinction.

WLS uses a non-diagonal weight matrix

WLS handles only heteroscedasticity, GLS handles both heteroscedasticity and autocorrelation

GLS is a special case of WLS

GLS cannot handle correlated errors

None

Comment

Hint

Which of the following is a formal test for detecting heteroscedasticity?

Choose the formal test.

Goldfeld-Quandt test

Augmented Dickey-Fuller test

Jarque-Bera test

Durbin-Watson test

None

Comment

Hint

What is the main purpose of Weighted Least Squares (WLS)?

Identify the purpose of WLS.

To correct for heteroscedasticity

To detect outliers

To transform non-linear models

To reduce multicollinearity

None

Comment

Hint

10.

Which of the following is an informal method of detecting heteroscedasticity?

Identify the informal method.

White’s test

Plotting residuals against fitted values

Breusch-Pagan test

Park test

None

Comment

Hint

11.

Heteroscedasticity is more likely to occur in:

Select the correct data type.

Panel data

Experimental data

Time series data

Cross-sectional data

None

Comment

Hint

12.

Which of the following is a real-world example of heteroscedasticity?

Select the most appropriate example.

Temperature and rainfall

Height and weight of adults

Age and gender

Income and consumption patterns

None

Comment

Hint

13.

In WLS method weights are:

Identify the appropriate weights.

Inverse of Y

Inverse of X variable

Square root of error variance

Inverse of error variance

None

Comment

Hint

14.

Which method minimizes the weighted sum of squared residuals?

Identify the estimation method.

WLS

OLS

Both WLS and GLS

GLS

None

Comment

Hint

15.

If the variance of the error term decreases as X increases, this is:

Identify the situation.

Increasing heteroscedasticity

Decreasing heteroscedasticity

Homoscedasticity

Autocorrelation

None

Comment

Hint

16.

In the context of heteroscedasticity, BLUE stands for:

Expand the acronym BLUE.

Best Linear Unbiased Estimator

Best Least Unbiased Estimator

Best Likelihood Unbiased Estimator

Best Linear Uncorrelated Estimator

None

Comment

Hint

17.

Which of the following is a cause of heteroscedasticity?

Select the best answer.

Omitted variables

Incorrect functional form

Measurement errors

All of the above

None

Comment

Hint

18.

WLS method:

Choose the correct description.

Maximizes Weighted Residual Sum of Squares

Minimizes Weighted Residual Sum of Squares

Minimizes Unweighted Residual Sum of Squares

Maximizes Unweighted Residual Sum of Squares

None

Comment

Hint

19.

In the presence of heteroscedasticity, the usual t and F tests:

Choose the correct statement.

Remain valid

Are more powerful

Are not affected

Become unreliable

None

Comment

Hint

20.

Which of the following best defines heteroscedasticity?

Select the correct definition of heteroscedasticity.

Errors are correlated across observations

Mean of error terms is not zero

Variance of error terms is constant across all observations

Variance of error terms is not constant across all observations

None

Comment

Hint

21.

Which of the following is NOT a consequence of heteroscedasticity?

Select the incorrect consequence.

Standard errors become biased

OLS estimators become biased

OLS estimators are no longer BLUE

Confidence intervals and hypothesis tests become unreliable

None

Comment

Hint

22.

OLS method:

Choose the correct description.

Minimizes Unweighted Residual Sum of Squares

Maximizes Weighted Residual Sum of Squares

Minimizes Weighted Residual Sum of Squares

Maximizes Unweighted Residual Sum of Squares

None

Comment

Hint

23.

In the Goldfeld-Quandt test, the data is typically divided into:

Choose the correct procedure.

Three equal groups

Two groups after omitting central observations

Four random groups

Groups based on the dependent variable

None

Comment

Hint

24.

The presence of heteroscedasticity affects:

Choose the correct statement.

Both mean and variance of estimators

Only the mean of estimators

Only the variance of estimators

Neither mean nor variance

None

Comment

Hint

25.

Which of the following tests is NOT used for detecting heteroscedasticity?

Select the incorrect test.

Glejser test

Durbin-Watson test

Spearman’s rank correlation test

Park test

None

Comment

Hint

26.

The Goldfeld-Quandt test is used to:

Identify the purpose of the test.

Detect autocorrelation

Detect normality

Detect endogeneity

Detect heteroscedasticity

None

Comment

Hint

27.

Which of the following is a graphical sign of heteroscedasticity in a residual plot?

Identify the visual indication of heteroscedasticity.

Residuals are always negative

Residuals show a funnel or cone shape

Residuals form a straight horizontal band

Residuals are always positive

None

Comment

Hint

28.

In a regression model, the presence of outliers can cause:

Choose the correct answer.

Perfect multicollinearity

Stationarity

Heteroscedasticity

Homoscedasticity

None

Comment

Hint

1 out of 28

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