Question 1

The procedure of comparing different instrumental variables estimates of the same parameter is an example of testing _____.

Accepted Answer

A) overidentifying restrictions 
B) endogeneity 
C) heteroskedasticity 
D) serial correlation 
A) overidentifying restrictions 
B) endogeneity 
C) heteroskedasticity 
D) serial correlation A

Question 2

Consider the following simple regression model: y = β0+ β1x1+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument exogeneity?

Accepted Answer

A) Cov(z,u)> 0 
B) Cov(z,x)> 0 
C) Cov(z,u)= 0 
D) Cov(z,x)= 0 
A) Cov(z,u)> 0 
B) Cov(z,x)> 0 
C) Cov(z,u)= 0 
D) Cov(z,x)= 0 C

Question 3

The sampling variance for the instrumental variables (IV)estimator is larger than the variance for the ordinary least square estimators (OLS)because _____.

Accepted Answer

A) R?2 >1 B) R?2 2 =1 D) R?2 <1 A) R?2 >1 B) R?2 2 =1 D) R?2 <1 D

Question 4

Consider the following simple regression model y=β0 + β1x1 + u.The variable z is a poor instrument for x if _____.

Accepted Answer

A) there is a high correlation between z and x 
B) there is a low correlation between z and x 
C) there is a high correlation between z and u 
D) there is a low correlation between z and u 
A) there is a high correlation between z and x 
B) there is a low correlation between z and x 
C) there is a high correlation between z and u 
D) there is a low correlation between z and u

Question 5

Increasing the number of overidentifying restrictions can cause severe biases in two stage least squares estimators.

Accepted Answer

A) True 
 B)False

Question 6

If the instrumental variable estimator has an upward bias,the ordinary least square estimator always has a downward bias.

Accepted Answer

A) True 
 B)False

Question 7

Which of the following is true of two stage least squares estimators?

Accepted Answer

A) The two stage least squares estimator is equal to the instrumental variable estimator if R2 is equal to 1. 
B) The two stage least squares estimators are biased if the regression model exhibits multicollinearity. 
C) The two stage least squares estimators have lower variance than the ordinary least squares estimators. 
D) The two stage least squares estimators have large standard errors when R2 lies close to 0. 
A) The two stage least squares estimator is equal to the instrumental variable estimator if R2 is equal to 1. 
B) The two stage least squares estimators are biased if the regression model exhibits multicollinearity. 
C) The two stage least squares estimators have lower variance than the ordinary least squares estimators. 
D) The two stage least squares estimators have large standard errors when R2 lies close to 0.

Question 8

The two stage least squares estimator is less efficient than the ordinary least squares estimator when the explanatory variables are exogenous.

Accepted Answer

A) True 
 B)False

Question 9

Which of the following assumptions is known as exclusion restrictions?

Accepted Answer

A) The assumption that an instrumental variable is excluded from a regression model and is correlated with the error term 
B) The assumption that an instrumental variable is excluded from a regression model and correlated with an exogenous explanatory variable 
C) The assumption that an exogenous explanatory variable is excluded from a regression model and is uncorrelated with the error term 
D) The assumption that an endogenous explanatory variable excluded from a regression model and is uncorrelated with the error term 
A) The assumption that an instrumental variable is excluded from a regression model and is correlated with the error term 
B) The assumption that an instrumental variable is excluded from a regression model and correlated with an exogenous explanatory variable 
C) The assumption that an exogenous explanatory variable is excluded from a regression model and is uncorrelated with the error term 
D) The assumption that an endogenous explanatory variable excluded from a regression model and is uncorrelated with the error term

Question 10

Consider the following simple regression model y=β0+ β1x1+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument relevance?

Accepted Answer

A) Cov(z,u)> 0 B) Cov(z,u)< 0 C) Cov(z,x)≠ 0 D) Cov(z,x)=0 A) Cov(z,u)> 0 B) Cov(z,u)< 0 C) Cov(z,x)≠ 0 D) Cov(z,x)=0

Question 11

Two stage least squares estimation cannot be applied to a panel data set.

Accepted Answer

A) True 
 B)False

Question 12

The test for overidentifying restrictions is valid if _____.

Accepted Answer

A) the regression model exhibits heteroskedasticity 
B) the regression model exhibits homoskedasticity 
C) the number of instrumental variables are less than the number of endogenous explanatory variables 
D) the number of instrumental variables are just enough for obtaining consistent estimators. 
A) the regression model exhibits heteroskedasticity 
B) the regression model exhibits homoskedasticity 
C) the number of instrumental variables are less than the number of endogenous explanatory variables 
D) the number of instrumental variables are just enough for obtaining consistent estimators.

Question 13

Consider the following simple regression model y=β0+ β1x1+ u.Suppose z is an instrument for x. Which of the following statements is true?

Accepted Answer

A) The condition Cov(z,u)= 0 can be tested statistically. 
B) The condition Cov(z,x)≠ 0 cannot be tested statistically. 
C) The instrumental variables estimator is always biased if Cov(x,u)≠0. 
D) The ordinary least squares estimator is unbiased if Cov(x,u)≠0. 
A) The condition Cov(z,u)= 0 can be tested statistically. 
B) The condition Cov(z,x)≠ 0 cannot be tested statistically. 
C) The instrumental variables estimator is always biased if Cov(x,u)≠0. 
D) The ordinary least squares estimator is unbiased if Cov(x,u)≠0.

Question 14

Instrumental variables cannot be used for estimating a regression equation if the regression model suffers from the measurement error problem.

Accepted Answer

A) True 
 B)False

Question 15

The order condition for identification of an equation requires that there should be _____.

Accepted Answer

A) at least one exogenous explanatory variable in a structural equation 
B) at least as many excluded exogenous explanatory variables as there are included endogenous explanatory variables 
C) at least as many dummy variables in an equation as there are exogenous explanatory variables 
D) as many lagged independent variables in an equation as there are exogenous explanatory variables 
A) at least one exogenous explanatory variable in a structural equation 
B) at least as many excluded exogenous explanatory variables as there are included endogenous explanatory variables 
C) at least as many dummy variables in an equation as there are exogenous explanatory variables 
D) as many lagged independent variables in an equation as there are exogenous explanatory variables

Question 16

The necessary condition for identification of an equation is called the _____.

Accepted Answer

A) order condition 
B) rank condition 
C) condition of instrumental exogeneity 
D) the condition of instrumental relevance. 
A) order condition 
B) rank condition 
C) condition of instrumental exogeneity 
D) the condition of instrumental relevance.

Question 17

Consider the following simple regression model: y = β0+ β1x1+ u.In order to obtain consistent estimators of β0and β1,when x and u are correlated,a new variable z is introduced into the model which satisfies the following two conditions: Cov(z,x)≠0 and Cov (z,u)=0.The variable z is called a(n)_____ variable.

Accepted Answer

A) dummy 
B) instrumental 
C) lagged dependent variable 
D) random 
A) dummy 
B) instrumental 
C) lagged dependent variable 
D) random

Question 18

Which of the following assumptions is required for two stage least squares estimation with time series data but not required for two-stage least squares estimation with cross sectional data?

Accepted Answer

A) The conditional mean of the error term is zero. 
B) The error term has constant conditional variance. 
C) The model includes at least one dummy variable. 
D) The error terms are not serially correlated. 
A) The conditional mean of the error term is zero. 
B) The error term has constant conditional variance. 
C) The model includes at least one dummy variable. 
D) The error terms are not serially correlated.

Question 19

Which of the following assumptions is required for two-stage least squares estimation method?

Accepted Answer

A) There are perfect linear relationships among the instrumental variables. 
B) There is strong correlation between each instrumental variable and the error term. 
C) The conditional variance of the error term depends on an exogenous explanatory variable. 
D) The error term has zero mean. 
A) There are perfect linear relationships among the instrumental variables. 
B) There is strong correlation between each instrumental variable and the error term. 
C) The conditional variance of the error term depends on an exogenous explanatory variable. 
D) The error term has zero mean.

Question 20

Consider the following simple regression model y=β0 + β1x1 + u.Suppose z is an instrument for x.if Cov(z,u)= 0 and Cov(z,x)≠ 0,the value of β1in terms of population covariances is _____.

Accepted Answer

A)    
B)    
C) Cov(z,u) 
D) Cov(z,x) 
A)    
B)    
C) Cov(z,u) 
D) Cov(z,x)

The procedure of comparing different instrumental variables estimates of the same parameter is an example of testing _____.

Consider the following simple regression model: y = β₀+ β₁x₁+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument exogeneity?

The sampling variance for the instrumental variables (IV)estimator is larger than the variance for the ordinary least square estimators (OLS)because _____.

Consider the following simple regression model y=β₀ + β₁x₁ + u.The variable z is a poor instrument for x if _____.

Increasing the number of overidentifying restrictions can cause severe biases in two stage least squares estimators.

If the instrumental variable estimator has an upward bias,the ordinary least square estimator always has a downward bias.

Which of the following is true of two stage least squares estimators?

The two stage least squares estimator is less efficient than the ordinary least squares estimator when the explanatory variables are exogenous.

Which of the following assumptions is known as exclusion restrictions?

Consider the following simple regression model y=β₀+ β₁x₁+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument relevance?

Two stage least squares estimation cannot be applied to a panel data set.

The test for overidentifying restrictions is valid if _____.

Consider the following simple regression model y=β₀+ β₁x₁+ u.Suppose z is an instrument for x. Which of the following statements is true?

Instrumental variables cannot be used for estimating a regression equation if the regression model suffers from the measurement error problem.

The order condition for identification of an equation requires that there should be _____.

The necessary condition for identification of an equation is called the _____.

Which of the following assumptions is required for two stage least squares estimation with time series data but not required for two-stage least squares estimation with cross sectional data?

Which of the following assumptions is required for two-stage least squares estimation method?

Consider the following simple regression model y=β₀ + β₁x₁ + u.Suppose z is an instrument for x.if Cov(z,u)= 0 and Cov(z,x)≠ 0,the value of β₁in terms of population covariances is _____.

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

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

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Exam 15: Instrumental Variables Estimation and Two Stage Least Squares

The procedure of comparing different instrumental variables estimates of the same parameter is an example of testing _____.

Consider the following simple regression model: y = β0+ β1x1+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument exogeneity?

The sampling variance for the instrumental variables (IV)estimator is larger than the variance for the ordinary least square estimators (OLS)because _____.

Consider the following simple regression model y=β0 + β1x1 + u.The variable z is a poor instrument for x if _____.

Increasing the number of overidentifying restrictions can cause severe biases in two stage least squares estimators.

If the instrumental variable estimator has an upward bias,the ordinary least square estimator always has a downward bias.

Which of the following is true of two stage least squares estimators?

The two stage least squares estimator is less efficient than the ordinary least squares estimator when the explanatory variables are exogenous.

Which of the following assumptions is known as exclusion restrictions?

Consider the following simple regression model y=β0+ β1x1+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument relevance?

Two stage least squares estimation cannot be applied to a panel data set.

The test for overidentifying restrictions is valid if _____.

Consider the following simple regression model y=β0+ β1x1+ u.Suppose z is an instrument for x. Which of the following statements is true?

Instrumental variables cannot be used for estimating a regression equation if the regression model suffers from the measurement error problem.

The order condition for identification of an equation requires that there should be _____.

The necessary condition for identification of an equation is called the _____.

Which of the following assumptions is required for two stage least squares estimation with time series data but not required for two-stage least squares estimation with cross sectional data?

Which of the following assumptions is required for two-stage least squares estimation method?

Consider the following simple regression model y=β0 + β1x1 + u.Suppose z is an instrument for x.if Cov(z,u)= 0 and Cov(z,x)≠ 0,the value of β1in terms of population covariances is _____.

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

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

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Consider the following simple regression model: y = β₀+ β₁x₁+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument exogeneity?

Consider the following simple regression model y=β₀ + β₁x₁ + u.The variable z is a poor instrument for x if _____.

Consider the following simple regression model y=β₀+ β₁x₁+ u.Suppose z is an instrument for x.Which of the following conditions denotes instrument relevance?

Consider the following simple regression model y=β₀+ β₁x₁+ u.Suppose z is an instrument for x. Which of the following statements is true?

Consider the following simple regression model y=β₀ + β₁x₁ + u.Suppose z is an instrument for x.if Cov(z,u)= 0 and Cov(z,x)≠ 0,the value of β₁in terms of population covariances is _____.