Question 1

Which of the following is a difference between least absolute deviations (LAD)and ordinary least squares (OLS)estimation?

Accepted Answer

A) OLS is more computationally intensive than LAD. 
B) OLS is more sensitive to outlying observations than LAD. 
C) OLS is justified for very large sample sizes while LAD is justified for smaller sample sizes. 
D) OLS is designed to estimate the conditional median of the dependent variable while LAD is designed to estimate the conditional mean. 
A) OLS is more computationally intensive than LAD. 
B) OLS is more sensitive to outlying observations than LAD. 
C) OLS is justified for very large sample sizes while LAD is justified for smaller sample sizes. 
D) OLS is designed to estimate the conditional median of the dependent variable while LAD is designed to estimate the conditional mean. B

Question 2

Which of the following is true?

Accepted Answer

A) A functional form misspecification can occur if the level of a variable is used when the logarithm is more appropriate. 
B) A functional form misspecification occurs only if a key variable is uncorrelated with the error term.. 
C) A functional form misspecification does not lead to biasedness in the ordinary least squares estimators. 
D) A functional form misspecification does not lead to inconsistency in the ordinary least squares estimators. 
A) A functional form misspecification can occur if the level of a variable is used when the logarithm is more appropriate. 
B) A functional form misspecification occurs only if a key variable is uncorrelated with the error term.. 
C) A functional form misspecification does not lead to biasedness in the ordinary least squares estimators. 
D) A functional form misspecification does not lead to inconsistency in the ordinary least squares estimators. A

Question 3

The Least Absolute Deviations (LAD)estimators in a linear model minimize the sum of squared residuals.

Accepted Answer

A) True 
 B)False  False

Question 4

Studentized residuals are obtained from the original OLS residuals by dividing them by an estimate of their standard deviation.

Accepted Answer

A) True 
 B)False

Question 5

Which of the following is true of Regression Specification Error Test (RESET)?

Accepted Answer

A) It tests if the functional form of a regression model is misspecified. 
B) It detects the presence of dummy variables in a regression model. 
C) It helps in the detection of heteroskedasticity when the functional form of the model is correctly specified. 
D) It helps in the detection of multicollinearity among the independent variables in a regression model. 
A) It tests if the functional form of a regression model is misspecified. 
B) It detects the presence of dummy variables in a regression model. 
C) It helps in the detection of heteroskedasticity when the functional form of the model is correctly specified. 
D) It helps in the detection of multicollinearity among the independent variables in a regression model.

Question 6

Sample selection based on the dependent variable is called _____.

Accepted Answer

A) random sample selection 
B) endogenous sample selection 
C) exogenous sample selection 
D) stratified sample selection 
A) random sample selection 
B) endogenous sample selection 
C) exogenous sample selection 
D) stratified sample selection

Question 7

A proxy variable _____.

Accepted Answer

A) increases the error variance of a regression model 
B) cannot contain binary information 
C) is used when data on a key independent variable is unavailable 
D) is detected by running the Davidson-MacKinnon test 
A) increases the error variance of a regression model 
B) cannot contain binary information 
C) is used when data on a key independent variable is unavailable 
D) is detected by running the Davidson-MacKinnon test

Question 8

Which of the following is a drawback of including proxy variables in a regression model?

Accepted Answer

A) It leads to misspecification analysis. 
B) It reduces the error variance. 
C) It increases the error variance. 
D) It exacerbates multicollinearity. 
A) It leads to misspecification analysis. 
B) It reduces the error variance. 
C) It increases the error variance. 
D) It exacerbates multicollinearity.

Question 9

Consider the following regression model: log(y)= β0+ β1x1+ β2x12 + β3x3+ u.This model will suffer from functional form misspecification if _____.

Accepted Answer

A) β0 is omitted from the model 
B) u is heteroskedastic 
C) x12 is omitted from the model 
D) x3 is a binary variable 
A) β0 is omitted from the model 
B) u is heteroskedastic 
C) x12 is omitted from the model 
D) x3 is a binary variable

Question 10

The classical errors-in-variables (CEV)assumption is that _____.

Accepted Answer

A) the error term in a regression model is correlated with all observed explanatory variables 
B) the error term in a regression model is uncorrelated with all observed explanatory variables 
C) the measurement error is correlated with the unobserved explanatory variable 
D) the measurement error is uncorrelated with the unobserved explanatory variable 
A) the error term in a regression model is correlated with all observed explanatory variables 
B) the error term in a regression model is uncorrelated with all observed explanatory variables 
C) the measurement error is correlated with the unobserved explanatory variable 
D) the measurement error is uncorrelated with the unobserved explanatory variable

Question 11

A regression model suffers from functional form misspecification if _____.

Accepted Answer

A) a key variable is binary. 
B) the dependent variable is binary. 
C) an interaction term is omitted. 
D) the coefficient of a key variable is zero. 
A) a key variable is binary. 
B) the dependent variable is binary. 
C) an interaction term is omitted. 
D) the coefficient of a key variable is zero.

Question 12

The measurement error is the difference between the actual value of a variable and its reported value.

Accepted Answer

A) True 
 B)False

Question 13

The method of data collection in which the population is divided into nonoverlapping,exhaustive groups is called _____.

Accepted Answer

A) random sampling 
B) stratified sampling 
C) endogenous sampling 
D) exogenous sampling 
A) random sampling 
B) stratified sampling 
C) endogenous sampling 
D) exogenous sampling

Question 14

Which of the following is true of measurement error?

Accepted Answer

A) If measurement error in a dependent variable has zero mean,the ordinary least squares estimators for the intercept are biased and inconsistent. 
B) If measurement error in an independent variable is uncorrelated with the variable,the ordinary least squares estimators are unbiased. 
C) If measurement error in an independent variable is uncorrelated with other independent variables,all estimators are biased. 
D) If measurement error in a dependent variable is correlated with the independent variables,the ordinary least squares estimators are unbiased. 
A) If measurement error in a dependent variable has zero mean,the ordinary least squares estimators for the intercept are biased and inconsistent. 
B) If measurement error in an independent variable is uncorrelated with the variable,the ordinary least squares estimators are unbiased. 
C) If measurement error in an independent variable is uncorrelated with other independent variables,all estimators are biased. 
D) If measurement error in a dependent variable is correlated with the independent variables,the ordinary least squares estimators are unbiased.

Question 15

Which of the following types of sampling always causes bias or inconsistency in the ordinary least squares estimators?

Accepted Answer

A) Random sampling 
B) Exogenous sampling 
C) Endogenous sampling 
D) Stratified sampling 
A) Random sampling 
B) Exogenous sampling 
C) Endogenous sampling 
D) Stratified sampling

Question 16

An explanatory variable is called exogenous if it is correlated with the error term.

Accepted Answer

A) True 
 B)False

Question 17

A measurement error occurs in a regression model when _____.

Accepted Answer

A) the observed value of a variable used in the model differs from its actual value 
B) the dependent variable is binary 
C) the partial effect of an independent variable depends on unobserved factors 
D) the model includes more than two independent variables 
A) the observed value of a variable used in the model differs from its actual value 
B) the dependent variable is binary 
C) the partial effect of an independent variable depends on unobserved factors 
D) the model includes more than two independent variables

Question 18

A multiple regression model suffers from functional form misspecification when it does not properly account for the relationship between the dependent and the observed explanatory
variables.

Accepted Answer

A) True 
 B)False

Question 19

Which of the following assumptions is needed for the plug-in solution to the omitted variables problem to provide consistent estimators?

Accepted Answer

A) The error term in the regression model exhibits heteroskedasticity. 
B) The error term in the regression model is uncorrelated with all the independent variables. 
C) The proxy variable is uncorrelated with the dependent variable. 
D) The proxy variable has zero conditional mean. 
A) The error term in the regression model exhibits heteroskedasticity. 
B) The error term in the regression model is uncorrelated with all the independent variables. 
C) The proxy variable is uncorrelated with the dependent variable. 
D) The proxy variable has zero conditional mean.

Question 20

Consider the following equation for household consumption expenditure: Consmptn= β0+ β1Inc + β2Consmptn-1+ u
Where 'Consmptn' measures the monthly consumption expenditure of a household,'Inc' measures household income and 'Consmptn-1' is the consumption expenditure in the previous month.Consmptn-1 is a _____ variable.

Accepted Answer

A) exogenous 
B) binary variable 
C) lagged dependent 
D) proxy variable 
A) exogenous 
B) binary variable 
C) lagged dependent 
D) proxy variable

Which of the following is a difference between least absolute deviations (LAD)and ordinary least squares (OLS)estimation?

Which of the following is true?

The Least Absolute Deviations (LAD)estimators in a linear model minimize the sum of squared residuals.

Studentized residuals are obtained from the original OLS residuals by dividing them by an estimate of their standard deviation.

Which of the following is true of Regression Specification Error Test (RESET)?

Sample selection based on the dependent variable is called _____.

A proxy variable _____.

Which of the following is a drawback of including proxy variables in a regression model?

Consider the following regression model: log(y)= β₀+ β₁x₁+ β₂x₁²+ β₃x₃+ u.This model will suffer from functional form misspecification if _____.

The classical errors-in-variables (CEV)assumption is that _____.

A regression model suffers from functional form misspecification if _____.

The measurement error is the difference between the actual value of a variable and its reported value.

The method of data collection in which the population is divided into nonoverlapping,exhaustive groups is called _____.

Which of the following is true of measurement error?

Which of the following types of sampling always causes bias or inconsistency in the ordinary least squares estimators?

An explanatory variable is called exogenous if it is correlated with the error term.

A measurement error occurs in a regression model when _____.

A multiple regression model suffers from functional form misspecification when it does not properly account for the relationship between the dependent and the observed explanatory variables.

Which of the following assumptions is needed for the plug-in solution to the omitted variables problem to provide consistent estimators?

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

Heteroskedasticity

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 9: More on Specification and Data Problems

Which of the following is a difference between least absolute deviations (LAD)and ordinary least squares (OLS)estimation?

Which of the following is true?

The Least Absolute Deviations (LAD)estimators in a linear model minimize the sum of squared residuals.

Studentized residuals are obtained from the original OLS residuals by dividing them by an estimate of their standard deviation.

Which of the following is true of Regression Specification Error Test (RESET)?

Sample selection based on the dependent variable is called _____.

A proxy variable _____.

Which of the following is a drawback of including proxy variables in a regression model?

Consider the following regression model: log(y)= β0+ β1x1+ β2x12 + β3x3+ u.This model will suffer from functional form misspecification if _____.

The classical errors-in-variables (CEV)assumption is that _____.

A regression model suffers from functional form misspecification if _____.

The measurement error is the difference between the actual value of a variable and its reported value.

The method of data collection in which the population is divided into nonoverlapping,exhaustive groups is called _____.

Which of the following is true of measurement error?

Which of the following types of sampling always causes bias or inconsistency in the ordinary least squares estimators?

An explanatory variable is called exogenous if it is correlated with the error term.

A measurement error occurs in a regression model when _____.

A multiple regression model suffers from functional form misspecification when it does not properly account for the relationship between the dependent and the observed explanatory variables.

Which of the following assumptions is needed for the plug-in solution to the omitted variables problem to provide consistent estimators?

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

Heteroskedasticity

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: log(y)= β₀+ β₁x₁+ β₂x₁²+ β₃x₃+ u.This model will suffer from functional form misspecification if _____.