Question 1

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L > B the model is

Accepted Answer

A) just identified 
B) over identified 
C) under identified 
D) perfectly identified 
A) just identified 
B) over identified 
C) under identified 
D) perfectly identified B

Question 2

When an exogenous instrument is used,IV estimators are

Accepted Answer

A) consistent and approximately normally distributed in large samples 
B) unbiased and BLUE in all sample sizes 
C) consistent if z is normally distributed 
D) normally distributed in all sample sizes and consistent in large sample sizes 
A) consistent and approximately normally distributed in large samples 
B) unbiased and BLUE in all sample sizes 
C) consistent if z is normally distributed 
D) normally distributed in all sample sizes and consistent in large sample sizes A

Question 3

What does it mean for a variable to be endogenous?

Accepted Answer

A) it is determined within the system or model 
B) it is measured after all other variables are observed 
C) it is determined outside the system or model 
D) it is measured before all other variables are observed 
A) it is determined within the system or model 
B) it is measured after all other variables are observed 
C) it is determined outside the system or model 
D) it is measured before all other variables are observed A

Question 4

Which of the following is not a desirable characteristic in an instrumental variable,z,to be used in IV/2SLS estimation?

Accepted Answer

A) cov (z,e)= 0 
B) z is unrelated to y 
C) high correlation between z & x 
D) normally distributed z 
A) cov (z,e)= 0 
B) z is unrelated to y 
C) high correlation between z & x 
D) normally distributed z

Question 5

What is the null hypothesis when performing an F-test to test the strength of an instrument?

Accepted Answer

A) the instrument is weak,with no $\theta$ different from 0. 
B) it is a strong instrument with all $\theta$significantly different from 0. 
C) the instrument is sufficiently strong with at least 1 $\theta$significantly different from 0. 
D) the instrument is weak with all $\theta$different from 0. 
A) the instrument is weak,with no $\theta$ different from 0. 
B) it is a strong instrument with all $\theta$significantly different from 0. 
C) the instrument is sufficiently strong with at least 1 $\theta$significantly different from 0. 
D) the instrument is weak with all $\theta$different from 0.

Question 6

In 2SLS,how should the strength of an instrument be measured?

Accepted Answer

A) an F-test on the first stage regression equation 
B) the p-value of the instrument's coefficient in the second stage regression 
C) the R2 in the first stage regression equation 
D) an F-test on the second stage regression equation 
A) an F-test on the first stage regression equation 
B) the p-value of the instrument's coefficient in the second stage regression 
C) the R2 in the first stage regression equation 
D) an F-test on the second stage regression equation

Question 7

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L < B the model is

Accepted Answer

A) just identified 
B) over identified 
C) under identified 
D) perfectly identified 
A) just identified 
B) over identified 
C) under identified 
D) perfectly identified

Question 8

Which of the following is not a common cause of endogeneity?

Accepted Answer

A) measurement error 
B) simultaneous equations 
C) omitted variables 
D) continuous variables 
A) measurement error 
B) simultaneous equations 
C) omitted variables 
D) continuous variables

Question 9

Which of the following statements is true regarding var when estimated by IV using z as an instrument for x?

Accepted Answer

A) instrumental variable estimation leads to larger variance of estimates compared to OLS 
B) instrumental variable estimation leads to smaller variance estimates compared to OLS 
C) the variance of the IV estimates can be larger or smaller than OLS,depending on r2xz 
D) there is no way to know which estimator leads to estimates with a larger variance,it depends on the data 
A) instrumental variable estimation leads to larger variance of estimates compared to OLS 
B) instrumental variable estimation leads to smaller variance estimates compared to OLS 
C) the variance of the IV estimates can be larger or smaller than OLS,depending on r2xz 
D) there is no way to know which estimator leads to estimates with a larger variance,it depends on the data

Question 10

Which assumption must be true when E(e|x)= 0?

Accepted Answer

A) E(e)= 0 and var(e)= $\sigma$2 
B) e = 0 
C) E(e)= 0 and cov(x,e)= 0. 
D) E(e)= e|x if x≠0 
A) E(e)= 0 and var(e)= $\sigma$2 
B) e = 0 
C) E(e)= 0 and cov(x,e)= 0. 
D) E(e)= e|x if x≠0

Question 11

If the assumption E(e)= 0 and cov(x,e)= 0 holds,what are the implications of least squares estimators?

Accepted Answer

A) still BLUE for all sample sizes 
B) consistent and normally distributed in very large sample sizes 
C) unbiased,but not BLUE for small samples 
D) inconsistent and parameter estimates do not converge to true values regardless of sample size. 
A) still BLUE for all sample sizes 
B) consistent and normally distributed in very large sample sizes 
C) unbiased,but not BLUE for small samples 
D) inconsistent and parameter estimates do not converge to true values regardless of sample size.

Question 12

If you reject the null hypothesis when performing a Hausman test,what should you conclude?

Accepted Answer

A) at least one of the explanatory variables is endogenous 
B) there are no endogenous variables 
C) the 2SLS estimation has corrected the endogeneity in the initial model 
D) the 2SLS second stage equation still has endogenous variables 
A) at least one of the explanatory variables is endogenous 
B) there are no endogenous variables 
C) the 2SLS estimation has corrected the endogeneity in the initial model 
D) the 2SLS second stage equation still has endogenous variables

Question 13

If you are estimating y = $\beta$1 + $\beta$2x + e
And realize x and y are both random variables,what condition must be true for simple regression estimators to be BLUE?

Accepted Answer

A) the data have been collected via random sampling 
B) the data are time series data 
C) e is normally distributed 
D) x is normally distributed 
A) the data have been collected via random sampling 
B) the data are time series data 
C) e is normally distributed 
D) x is normally distributed

Question 14

If,for estimator it is true that p then is

Accepted Answer

A) efficient 
B) consistent 
C) accurate 
D) independent 
A) efficient 
B) consistent 
C) accurate 
D) independent

Question 15

What is the 4th moment of random variable x?

Accepted Answer

A) E(x)4 
B) $\Sigma$ x / 4 
C) E(x4) 
D) (E(x4)-x4)/N 
A) E(x)4 
B) $\Sigma$ x / 4 
C) E(x4) 
D) (E(x4)-x4)/N

Question 16

What is the null hypothesis for a Hausman test for endogeneity?

Accepted Answer

A) cov (z,x)> 0 
B) cov(x,e)> 0 
C) cov(x,e)= 0 
D) e is normally distributed 
A) cov (z,x)> 0 
B) cov(x,e)> 0 
C) cov(x,e)= 0 
D) e is normally distributed

Question 17

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L = B the model is

Accepted Answer

A) just identified 
B) over identified 
C) under identified 
D) precisely identified 
A) just identified 
B) over identified 
C) under identified 
D) precisely identified

Question 18

What should you conclude if you get an F-statistic of 8.3 when testing the strength of an instrument?

Accepted Answer

A) it depends on the degrees of freedom and critical value of F 
B) do not reject H0;conclude that the instrument is weak and should not be used in 2SLS. 
C) reject H0;conclude the instrument is strong and proceed with 2SLS 
D) do not reject H0;conclude the instrument is strong and use it in 2SLS 
A) it depends on the degrees of freedom and critical value of F 
B) do not reject H0;conclude that the instrument is weak and should not be used in 2SLS. 
C) reject H0;conclude the instrument is strong and proceed with 2SLS 
D) do not reject H0;conclude the instrument is strong and use it in 2SLS

Question 19

If the assumption that cov(x,e)= 0 is not true,what are the implications of least squares estimators?

Accepted Answer

A) still BLUE for all sample sizes 
B) consistent and normally distributed in very large sample sizes 
C) unbiased,but not BLUE for small samples 
D) inconsistent;parameter estimates do not converge to true values regardless of sample size. 
A) still BLUE for all sample sizes 
B) consistent and normally distributed in very large sample sizes 
C) unbiased,but not BLUE for small samples 
D) inconsistent;parameter estimates do not converge to true values regardless of sample size.

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L > B the model is

When an exogenous instrument is used,IV estimators are

What does it mean for a variable to be endogenous?

Which of the following is not a desirable characteristic in an instrumental variable,z,to be used in IV/2SLS estimation?

What is the null hypothesis when performing an F-test to test the strength of an instrument?

In 2SLS,how should the strength of an instrument be measured?

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L < B the model is

Which of the following is not a common cause of endogeneity?

Which of the following statements is true regarding var when estimated by IV using z as an instrument for x?

Which assumption must be true when E(e|x)= 0?

If the assumption E(e)= 0 and cov(x,e)= 0 holds,what are the implications of least squares estimators?

If you reject the null hypothesis when performing a Hausman test,what should you conclude?

If you are estimating y = $\beta$ ₁ + $\beta$ ₂x + e And realize x and y are both random variables,what condition must be true for simple regression estimators to be BLUE?

If,for estimator it is true that p then is

What is the 4^th moment of random variable x?

What is the null hypothesis for a Hausman test for endogeneity?

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L = B the model is

What should you conclude if you get an F-statistic of 8.3 when testing the strength of an instrument?

If the assumption that cov(x,e)= 0 is not true,what are the implications of least squares estimators?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

Prediction, Goodness-Of-Fit and Modeling Issues

The Multiple Regression Model

Further Inference in the Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Regression With Time Series Data: Stationary Variables

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters

Exam 11: Random Regressors and Moment Based Estimation

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L > B the model is

When an exogenous instrument is used,IV estimators are

What does it mean for a variable to be endogenous?

Which of the following is not a desirable characteristic in an instrumental variable,z,to be used in IV/2SLS estimation?

What is the null hypothesis when performing an F-test to test the strength of an instrument?

In 2SLS,how should the strength of an instrument be measured?

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L < B the model is

Which of the following is not a common cause of endogeneity?

Which of the following statements is true regarding var when estimated by IV using z as an instrument for x?

Which assumption must be true when E(e|x)= 0?

If the assumption E(e)= 0 and cov(x,e)= 0 holds,what are the implications of least squares estimators?

If you reject the null hypothesis when performing a Hausman test,what should you conclude?

If you are estimating y = β\betaβ 1 + β\betaβ 2x + e And realize x and y are both random variables,what condition must be true for simple regression estimators to be BLUE?

If,for estimator it is true that p then is

What is the 4th moment of random variable x?

What is the null hypothesis for a Hausman test for endogeneity?

If L is the number of exogenous instruments and B is the number of endogenous regressors in the model,when L = B the model is

What should you conclude if you get an F-statistic of 8.3 when testing the strength of an instrument?

If the assumption that cov(x,e)= 0 is not true,what are the implications of least squares estimators?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

Prediction, Goodness-Of-Fit and Modeling Issues

The Multiple Regression Model

Further Inference in the Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Regression With Time Series Data: Stationary Variables

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters

If you are estimating y = $\beta$ ₁ + $\beta$ ₂x + e And realize x and y are both random variables,what condition must be true for simple regression estimators to be BLUE?

What is the 4^th moment of random variable x?