Econometrics Quiz: Heteroscedasticity

Welcome to your Econometrics Quiz: Heteroscedasticity

Total MCQs: 28

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Name

OLS method:

Choose the correct description.

Maximizes Weighted Residual Sum of Squares

Minimizes Weighted Residual Sum of Squares

Maximizes Unweighted Residual Sum of Squares

Minimizes Unweighted Residual Sum of Squares

None

Comment

Hint

In the context of heteroscedasticity, BLUE stands for:

Expand the acronym BLUE.

Best Least Unbiased Estimator

Best Linear Uncorrelated Estimator

Best Linear Unbiased Estimator

Best Likelihood Unbiased Estimator

None

Comment

Hint

Which of the following is NOT a source of heteroscedasticity?

Select the correct answer.

Outliers

Skewness in regressors

Correct model specification

Cross-sectional data

None

Comment

Hint

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

Identify the effect.

Maximum

No longer minimum

Minimum

Always zero

None

Comment

Hint

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

Identify the purpose of WLS.

To detect outliers

To transform non-linear models

To reduce multicollinearity

To correct for heteroscedasticity

None

Comment

Hint

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

Choose the correct procedure.

Three equal groups

Four random groups

Groups based on the dependent variable

Two groups after omitting central observations

None

Comment

Hint

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

Identify the visual indication of heteroscedasticity.

Residuals form a straight horizontal band

Residuals show a funnel or cone shape

Residuals are always positive

Residuals are always negative

None

Comment

Hint

The main difference between WLS and GLS is:

Choose the correct distinction.

WLS uses a non-diagonal weight matrix

GLS is a special case of WLS

GLS cannot handle correlated errors

WLS handles only heteroscedasticity, GLS handles both heteroscedasticity and autocorrelation

None

Comment

Hint

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

Choose the correct meaning of homoscedasticity.

Variance of error terms is constant

Errors have non-zero mean

Variance of error terms is increasing with X

Errors are correlated

None

Comment

Hint

10.

The presence of heteroscedasticity affects:

Choose the correct statement.

Only the variance of estimators

Neither mean nor variance

Only the mean of estimators

Both mean and variance of estimators

None

Comment

Hint

11.

Which of the following is a cause of heteroscedasticity?

Select the best answer.

All of the above

Omitted variables

Incorrect functional form

Measurement errors

None

Comment

Hint

12.

Heteroscedasticity is more likely to occur in:

Select the correct data type.

Panel data

Cross-sectional data

Experimental data

Time series data

None

Comment

Hint

13.

Which of the following is NOT a consequence of heteroscedasticity?

Select the incorrect consequence.

Confidence intervals and hypothesis tests become unreliable

Standard errors become biased

OLS estimators are no longer BLUE

OLS estimators become biased

None

Comment

Hint

14.

Which method minimizes the weighted sum of squared residuals?

Identify the estimation method.

GLS

Both WLS and GLS

WLS

OLS

None

Comment

Hint

15.

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

Choose the formal test.

Goldfeld-Quandt test

Durbin-Watson test

Jarque-Bera test

Augmented Dickey-Fuller test

None

Comment

Hint

16.

In the presence of heteroscedasticity, OLS estimators are:

Choose the correct property of OLS estimators.

Biased and inefficient

Unbiased but inefficient

Unbiased and efficient

Biased and efficient

None

Comment

Hint

17.

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

Identify the phenomenon.

Homoscedasticity

Multicollinearity

Heteroscedasticity

Autocorrelation

None

Comment

Hint

18.

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

Choose the correct statement.

Are more powerful

Remain valid

Are not affected

Become unreliable

None

Comment

Hint

19.

Which estimator remains unbiased in the presence of heteroscedasticity?

Choose the correct answer.

OLS

WLS

None

Both OLS and WLS

None

Comment

Hint

20.

WLS method:

Choose the correct description.

Minimizes Weighted Residual Sum of Squares

Maximizes Weighted Residual Sum of Squares

Minimizes Unweighted Residual Sum of Squares

Maximizes Unweighted Residual Sum of Squares

None

Comment

Hint

21.

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

Choose the correct answer.

Heteroscedasticity

Homoscedasticity

Stationarity

Perfect multicollinearity

None

Comment

Hint

22.

Which of the following best defines heteroscedasticity?

Select the correct definition of heteroscedasticity.

Variance of error terms is not constant across all observations

Variance of error terms is constant across all observations

Mean of error terms is not zero

Errors are correlated across observations

None

Comment

Hint

23.

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

Identify the informal method.

Breusch-Pagan test

Plotting residuals against fitted values

White’s test

Park test

None

Comment

Hint

24.

In WLS method weights are:

Identify the appropriate weights.

Inverse of error variance

Square root of error variance

Inverse of Y

Inverse of X variable

None

Comment

Hint

25.

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

Identify the situation.

Autocorrelation

Increasing heteroscedasticity

Decreasing heteroscedasticity

Homoscedasticity

None

Comment

Hint

26.

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

Select the most appropriate example.

Height and weight of adults

Age and gender

Temperature and rainfall

Income and consumption patterns

None

Comment

Hint

27.

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

Select the incorrect test.

Durbin-Watson test

Spearman’s rank correlation test

Glejser test

Park test

None

Comment

Hint

28.

The Goldfeld-Quandt test is used to:

Identify the purpose of the test.

Detect heteroscedasticity

Detect normality

Detect autocorrelation

Detect endogeneity

None

Comment

Hint

1 out of 28

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