Question 1

The linear probability model always contains heteroskedasticity when the dependent variable is a binary variable unless all of the slope parameters are zero.

Accepted Answer

A) True 
 B)False  True

Question 2

The heteroskedasticity-robust _____ is also called the heteroskedastcity-robust Wald statistic.

Accepted Answer

A) t statistic 
B) F statistic 
C) LM statistic 
D) z statistic 
A) t statistic 
B) F statistic 
C) LM statistic 
D) z statistic B

Question 3

Which of the following tests helps in the detection of heteroskedasticity?

Accepted Answer

A) The Breusch-Pagan test 
B) The Breusch-Godfrey test 
C) The Durbin-Watson test 
D) The Chow test 
A) The Breusch-Pagan test 
B) The Breusch-Godfrey test 
C) The Durbin-Watson test 
D) The Chow test A

Question 4

Which of the following is a difference between the White test and the Breusch-Pagan test?

Accepted Answer

A) The White test is used for detecting heteroskedasticty in a linear regression model while the Breusch-Pagan test is used for detecting autocorrelation. 
B) The White test is used for detecting autocorrelation in a linear regression model while the Breusch-Pagan test is used for detecting heteroskedasticity.. 
C) The number of regressors used in the White test is larger than the number of regressors used in the Breusch-Pagan test. 
D) The number of regressors used in the Breusch-Pagan test is larger than the number of regressors used in the White test. 
A) The White test is used for detecting heteroskedasticty in a linear regression model while the Breusch-Pagan test is used for detecting autocorrelation. 
B) The White test is used for detecting autocorrelation in a linear regression model while the Breusch-Pagan test is used for detecting heteroskedasticity.. 
C) The number of regressors used in the White test is larger than the number of regressors used in the Breusch-Pagan test. 
D) The number of regressors used in the Breusch-Pagan test is larger than the number of regressors used in the White test.

Question 5

Multicollinearity among the independent variables in a linear regression model causes the heteroskedasticity-robust standard errors to be large.

Accepted Answer

A) True 
 B)False

Question 6

The generalized least square estimators for correcting heteroskedasticity are called weighed least squares estimators.

Accepted Answer

A) True 
 B)False

Question 7

If the Breusch-Pagan Test for heteroskedasticity results in a large p-value,the null hypothesis of homoskedasticty is rejected.

Accepted Answer

A) True 
 B)False

Question 8

Weighted least squares estimation is used only when _____.

Accepted Answer

A) the dependent variable in a regression model is binary 
B) the independent variables in a regression model are correlated 
C) the error term in a regression model has a constant variance 
D) the functional form of the error variances is known 
A) the dependent variable in a regression model is binary 
B) the independent variables in a regression model are correlated 
C) the error term in a regression model has a constant variance 
D) the functional form of the error variances is known

Question 9

The general form of the t statistic is _____.

Accepted Answer

A)    
B)    
C)    
D)    
A)    
B)    
C)    
D)

Question 10

Which of the following is true of the White test?

Accepted Answer

A) The White test is used to detect the presence of multicollinearity in a linear regression model. 
B) The White test cannot detect forms of heteroskedasticity that invalidate the usual Ordinary Least Squares standard errors. 
C) The White test can detect the presence of heteroskedasticty in a linear regression model even if the functional form is misspecified. 
D) The White test assumes that the square of the error term in a regression model is uncorrelated with all the independent variables,their squares and cross products. 
A) The White test is used to detect the presence of multicollinearity in a linear regression model. 
B) The White test cannot detect forms of heteroskedasticity that invalidate the usual Ordinary Least Squares standard errors. 
C) The White test can detect the presence of heteroskedasticty in a linear regression model even if the functional form is misspecified. 
D) The White test assumes that the square of the error term in a regression model is uncorrelated with all the independent variables,their squares and cross products.

Question 11

Which of the following tests is used to compare the Ordinary Least Squares (OLS)estimates and the Weighted Least Squares (WLS)estimates?

Accepted Answer

A) The White test 
B) The Hausman test 
C) The Durbin-Watson test 
D) The Breusch-Godfrey test 
A) The White test 
B) The Hausman test 
C) The Durbin-Watson test 
D) The Breusch-Godfrey test

Question 12

The linear probability model contains heteroskedasticity unless _____.

Accepted Answer

A) the intercept parameter is zero 
B) all the slope parameters are positive 
C) all the slope parameters are zero 
D) the independent variables are binary 
A) the intercept parameter is zero 
B) all the slope parameters are positive 
C) all the slope parameters are zero 
D) the independent variables are binary

Question 13

Which of the following is true of the OLS t statistics?

Accepted Answer

A) The heteroskedasticity-robust t statistics are justified only if the sample size is large. 
B) The heteroskedasticty-robust t statistics are justified only if the sample size is small. 
C) The usual t statistics do not have exact t distributions if the sample size is large. 
D) In the presence of homoscedasticity,the usual t statistics do not have exact t distributions if the sample size is small. 
A) The heteroskedasticity-robust t statistics are justified only if the sample size is large. 
B) The heteroskedasticty-robust t statistics are justified only if the sample size is small. 
C) The usual t statistics do not have exact t distributions if the sample size is large. 
D) In the presence of homoscedasticity,the usual t statistics do not have exact t distributions if the sample size is small.

Question 14

The interpretation of goodness-of-fit measures changes in the presence of heteroskedasticity.

Accepted Answer

A) True 
 B)False

Question 15

Consider the following regression equation:   .Which of the following indicates a functional form misspecification in E(y|x)?

Accepted Answer

A) Ordinary Least Squares estimates equal Weighted Least Squares estimates. 
B) Ordinary Least Squares estimates exceed Weighted Least Squares estimates by a small magnitude. 
C) Weighted Least Squares estimates exceed Ordinary Least Squares estimates by a small magnitude. 
D) Ordinary Least Square estimates are positive while Weighted Least Squares estimates are negative. 
A) Ordinary Least Squares estimates equal Weighted Least Squares estimates. 
B) Ordinary Least Squares estimates exceed Weighted Least Squares estimates by a small magnitude. 
C) Weighted Least Squares estimates exceed Ordinary Least Squares estimates by a small magnitude. 
D) Ordinary Least Square estimates are positive while Weighted Least Squares estimates are negative.

Question 16

What will you conclude about a regression model if the Breusch-Pagan test results in a small p-value?

Accepted Answer

A) The model contains homoskedasticty. 
B) The model contains heteroskedasticty. 
C) The model contains dummy variables. 
D) The model omits some important explanatory factors. 
A) The model contains homoskedasticty. 
B) The model contains heteroskedasticty. 
C) The model contains dummy variables. 
D) The model omits some important explanatory factors.

Question 17

Consider the following regression model: yi=β0+β1 xi+ui.If the first four Gauss-Markov assumptions hold true,and the error term contains heteroskedasticity,then _____.

Accepted Answer

Question 18

A test for heteroskedasticty can be significant if _____.

Accepted Answer

A) the Breusch-Pagan test results in a large p-value 
B) the White test results in a large p-value 
C) the functional form of the regression model is misspecified 
D) the regression model includes too many independent variables 
A) the Breusch-Pagan test results in a large p-value 
B) the White test results in a large p-value 
C) the functional form of the regression model is misspecified 
D) the regression model includes too many independent variables

Question 19

Which of the following is true of heteroskedasticity?

Accepted Answer

A) Heteroskedasticty causes inconsistency in the Ordinary Least Squares estimators. 
B) Population R2 is affected by the presence of heteroskedasticty. 
C) The Ordinary Least Square estimators are not the best linear unbiased estimators if heteroskedasticity is present. 
D) It is not possible to obtain F statistics that are robust to heteroskedasticity of an unknown form. 
A) Heteroskedasticty causes inconsistency in the Ordinary Least Squares estimators. 
B) Population R2 is affected by the presence of heteroskedasticty. 
C) The Ordinary Least Square estimators are not the best linear unbiased estimators if heteroskedasticity is present. 
D) It is not possible to obtain F statistics that are robust to heteroskedasticity of an unknown form.

Question 20

Which of the following is true?

Accepted Answer

A) In ordinary least squares estimation,each observation is given a different weight. 
B) In weighted least squares estimation,each observation is given an identical weight. 
C) In weighted least squares estimation,less weight is given to observations with a higher error variance. 
D) In ordinary least squares estimation,less weight is given to observations with a lower error variance. 
A) In ordinary least squares estimation,each observation is given a different weight. 
B) In weighted least squares estimation,each observation is given an identical weight. 
C) In weighted least squares estimation,less weight is given to observations with a higher error variance. 
D) In ordinary least squares estimation,less weight is given to observations with a lower error variance.

The linear probability model always contains heteroskedasticity when the dependent variable is a binary variable unless all of the slope parameters are zero.

The heteroskedasticity-robust _____ is also called the heteroskedastcity-robust Wald statistic.

Which of the following tests helps in the detection of heteroskedasticity?

Which of the following is a difference between the White test and the Breusch-Pagan test?

Multicollinearity among the independent variables in a linear regression model causes the heteroskedasticity-robust standard errors to be large.

The generalized least square estimators for correcting heteroskedasticity are called weighed least squares estimators.

If the Breusch-Pagan Test for heteroskedasticity results in a large p-value,the null hypothesis of homoskedasticty is rejected.

Weighted least squares estimation is used only when _____.

The general form of the t statistic is _____.

Which of the following is true of the White test?

Which of the following tests is used to compare the Ordinary Least Squares (OLS)estimates and the Weighted Least Squares (WLS)estimates?

The linear probability model contains heteroskedasticity unless _____.

Which of the following is true of the OLS t statistics?

The interpretation of goodness-of-fit measures changes in the presence of heteroskedasticity.

Consider the following regression equation: .Which of the following indicates a functional form misspecification in E(y|x)?

What will you conclude about a regression model if the Breusch-Pagan test results in a small p-value?

Consider the following regression model: y_i=β₀+β₁ x_i+u_i.If the first four Gauss-Markov assumptions hold true,and the error term contains heteroskedasticity,then _____.

A test for heteroskedasticty can be significant if _____.

Which of the following is true of heteroskedasticity?

Which of the following is true?

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

Multiple Regression Analysis: Ols Asymptotics

Multiple Regression Analysis: Further Issues

Multiple Regression Analysis With Qualitative Information: Binary or Dummy Variables

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time: Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Stage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Exam 8: Heteroskedasticity

The linear probability model always contains heteroskedasticity when the dependent variable is a binary variable unless all of the slope parameters are zero.

The heteroskedasticity-robust _____ is also called the heteroskedastcity-robust Wald statistic.

Which of the following tests helps in the detection of heteroskedasticity?

Which of the following is a difference between the White test and the Breusch-Pagan test?

Multicollinearity among the independent variables in a linear regression model causes the heteroskedasticity-robust standard errors to be large.

The generalized least square estimators for correcting heteroskedasticity are called weighed least squares estimators.

If the Breusch-Pagan Test for heteroskedasticity results in a large p-value,the null hypothesis of homoskedasticty is rejected.

Weighted least squares estimation is used only when _____.

The general form of the t statistic is _____.

Which of the following is true of the White test?

Which of the following tests is used to compare the Ordinary Least Squares (OLS)estimates and the Weighted Least Squares (WLS)estimates?

The linear probability model contains heteroskedasticity unless _____.

Which of the following is true of the OLS t statistics?

The interpretation of goodness-of-fit measures changes in the presence of heteroskedasticity.

Consider the following regression equation: .Which of the following indicates a functional form misspecification in E(y|x)?

What will you conclude about a regression model if the Breusch-Pagan test results in a small p-value?

Consider the following regression model: yi=β0+β1 xi+ui.If the first four Gauss-Markov assumptions hold true,and the error term contains heteroskedasticity,then _____.

A test for heteroskedasticty can be significant if _____.

Which of the following is true of heteroskedasticity?

Which of the following is true?

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

Multiple Regression Analysis: Ols Asymptotics

Multiple Regression Analysis: Further Issues

Multiple Regression Analysis With Qualitative Information: Binary or Dummy Variables

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time: Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Stage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Consider the following regression model: y_i=β₀+β₁ x_i+u_i.If the first four Gauss-Markov assumptions hold true,and the error term contains heteroskedasticity,then _____.