Question 1

In which model are coefficient estimates determined by variation within individuals rather than variation across individuals?

Accepted Answer

A) pooled model 
B) fixed effects 
C) random effects 
D) none of these 
A) pooled model 
B) fixed effects 
C) random effects 
D) none of these B

Question 2

Which of the following is not an estimation technique utilizing panel data?

Accepted Answer

A) a pooled model 
B) fixed effects 
C) random effects 
D) probit 
A) a pooled model 
B) fixed effects 
C) random effects 
D) probit D

Question 3

Which type of model has coefficients that vary with i,but are constant with t?

Accepted Answer

A) pooled model 
B) fixed effects 
C) random effects 
D) none of these 
A) pooled model 
B) fixed effects 
C) random effects 
D) none of these B

Question 4

If N is the number of individuals observed in each of T time periods,what is generally true of a "long,narrow" panel?

Accepted Answer

A) T > N 
B) N > T 
C) N = T 
D) N1/2 2 
A) T > N 
B) N > T 
C) N = T 
D) N1/2 2

Question 5

Which of these assumptions means all error terms are uncorrelated?

Accepted Answer

A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it) 
A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it)

Question 6

For a random effects model the least squares estimator is unbiased and consistent.The errors can be corrected for potential heterogeneity using _________________,but the estimator with minimum variance is _______________.

Accepted Answer

A) cluster-robust standard errors,GLS 
B) White's correction,ML 
C) 2SLS,fixed effects 
D) cluster-robust standard errors,pooled 
A) cluster-robust standard errors,GLS 
B) White's correction,ML 
C) 2SLS,fixed effects 
D) cluster-robust standard errors,pooled

Question 7

Which of the following is not a reason random effects (RE)results may be preferred to fixed effects (FE)?

Accepted Answer

A) RE accounts for the random sampling process that generated the data 
B) RE is a GLS estimator so in large samples it has a smaller variance than FE which is a least squares estimator 
C) RE produces a coefficient for race,gender,or other individual characteristics that are constant over time 
D) RE estimates are more robust in the case of endogenous regressors 
A) RE accounts for the random sampling process that generated the data 
B) RE is a GLS estimator so in large samples it has a smaller variance than FE which is a least squares estimator 
C) RE produces a coefficient for race,gender,or other individual characteristics that are constant over time 
D) RE estimates are more robust in the case of endogenous regressors

Question 8

Which of the following assumptions must be made in order to use the pooled least squares estimator,but is relaxed in the cluster robust model?

Accepted Answer

A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it) 
A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it)

Question 9

When should the Hausman-Taylor estimator be used?

Accepted Answer

A) when a RE model has some endogenous regressors 
B) when FE is statistically insignificant 
C) when you do not have any information as to which regressors are endogenous 
D) when you want to estimate RE on a long,narrow data set 
A) when a RE model has some endogenous regressors 
B) when FE is statistically insignificant 
C) when you do not have any information as to which regressors are endogenous 
D) when you want to estimate RE on a long,narrow data set

Question 10

Which of these assumptions means the errors are uncorrelated with all x's?

Accepted Answer

A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it) 
A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it)

Question 11

Which of these assumptions indicates homoskedasticity?

Accepted Answer

A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it) 
A) E(eit)= 0 
B) var(eit)= E(e2it)= $\sigma$ 2 
C) cov(eit,ejs)= E(eit,ejs)= 0 for i j or t s 
D) cov(eit,x2it)= 0,cov(eit,x3it)

Question 12

Which model is also called an error components model?

Accepted Answer

A) pooled model 
B) fixed effects 
C) random effects 
D) none of these 
A) pooled model 
B) fixed effects 
C) random effects 
D) none of these

Question 13

What is the difference between balanced and unbalanced panels?

Accepted Answer

A) unbalanced panels have some observations missing,balanced do not B) balanced panels are demographically representative of the population being studied,unbalanced are not C) balanced panels have an equal number of observations above and below the mean of the dependent variable,unbalanced panels are skewed D) a balanced panel has T = N,an unbalanced panel has N>T or NT or N

Question 14

Suppose you have a long,narrow panel of data and estimate a single equation with indicator variables and interaction terms for the individuals.In doing this what assumption from the pooled model have you relaxed?

Accepted Answer

A) coefficients on variables are equal across individuals 
B) errors are uncorrelated with any x's 
C) expected value of errors are zero 
D) variances of error terms are equal across individuals 
A) coefficients on variables are equal across individuals 
B) errors are uncorrelated with any x's 
C) expected value of errors are zero 
D) variances of error terms are equal across individuals

Question 15

If N is the number of individuals observed in each of T time periods,what is generally true of a "short,wide" panel?

Accepted Answer

A) T > N 
B) N > T 
C) N = T 
D) N1/2 2 
A) T > N 
B) N > T 
C) N = T 
D) N1/2 2

Question 16

What is the primary advantage of using panel data rather than a large cross- section data set collected over time?

Accepted Answer

A) it allow you to control for individual heterogeneity 
B) it allows the effects of legislation to be estimated 
C) it gives you more degrees of freedom 
D) it allow coefficients to vary over time 
A) it allow you to control for individual heterogeneity 
B) it allows the effects of legislation to be estimated 
C) it gives you more degrees of freedom 
D) it allow coefficients to vary over time

Question 17

Which type of model has coefficients that vary with i and t?

Accepted Answer

A) pooled model 
B) fixed effects 
C) random effects 
D) none of these 
A) pooled model 
B) fixed effects 
C) random effects 
D) none of these

Question 18

How do you test for endogenous regressors,or correlation between the error term and any regressor in a random effects model?

Accepted Answer

A) estimate coefficients with RE and FE,then perform a Hausman test of equality 
B) estimate the model capturing estimated residuals,then regress residuals on all regressors and perform an F-test 
C) estimate RE model capturing estimated residuals,then estimate coefficients of correlation with each regressor 
D) estimate RE and FE models and perform an F test on each model individually.If the difference between the F statistics is significant,conclude endogeneity. 
A) estimate coefficients with RE and FE,then perform a Hausman test of equality 
B) estimate the model capturing estimated residuals,then regress residuals on all regressors and perform an F-test 
C) estimate RE model capturing estimated residuals,then estimate coefficients of correlation with each regressor 
D) estimate RE and FE models and perform an F test on each model individually.If the difference between the F statistics is significant,conclude endogeneity.

Question 19

If you perform a Hausman test on a random effects model and have a test statistic that exceeds your critical value,which of the following is not correct?

Accepted Answer

A) at least one of the regressors in the RE model is endogenous 
B) none of the common coefficient estimates in the RE model will be significantly different in the FE model 
C) FE may be the preferred estimation technique 
D) this model may be better estimated using the Hausman-Taylor estimator 
A) at least one of the regressors in the RE model is endogenous 
B) none of the common coefficient estimates in the RE model will be significantly different in the FE model 
C) FE may be the preferred estimation technique 
D) this model may be better estimated using the Hausman-Taylor estimator

Question 20

Which type of model does not have a coefficient that varies with t or i ?

Accepted Answer

A) a pooled model 
B) fixed effects 
C) random effects 
D) none of these 
A) a pooled model 
B) fixed effects 
C) random effects 
D) none of these

In which model are coefficient estimates determined by variation within individuals rather than variation across individuals?

Which of the following is not an estimation technique utilizing panel data?

Which type of model has coefficients that vary with i,but are constant with t?

If N is the number of individuals observed in each of T time periods,what is generally true of a "long,narrow" panel?

Which of these assumptions means all error terms are uncorrelated?

For a random effects model the least squares estimator is unbiased and consistent.The errors can be corrected for potential heterogeneity using ___,but the estimator with minimum variance is _.

Which of the following is not a reason random effects (RE)results may be preferred to fixed effects (FE)?

Which of the following assumptions must be made in order to use the pooled least squares estimator,but is relaxed in the cluster robust model?

When should the Hausman-Taylor estimator be used?

Which of these assumptions means the errors are uncorrelated with all x's?

Which of these assumptions indicates homoskedasticity?

Which model is also called an error components model?

What is the difference between balanced and unbalanced panels?

Suppose you have a long,narrow panel of data and estimate a single equation with indicator variables and interaction terms for the individuals.In doing this what assumption from the pooled model have you relaxed?

If N is the number of individuals observed in each of T time periods,what is generally true of a "short,wide" panel?

What is the primary advantage of using panel data rather than a large cross- section data set collected over time?

Which type of model has coefficients that vary with i and t?

How do you test for endogenous regressors,or correlation between the error term and any regressor in a random effects model?

If you perform a Hausman test on a random effects model and have a test statistic that exceeds your critical value,which of the following is not correct?

Which type of model does not have a coefficient that varies with t or i ?

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

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Qualitative and Limited Dependent Variable Models

Filters

Exam 16: Panel Data Models

In which model are coefficient estimates determined by variation within individuals rather than variation across individuals?

Which of the following is not an estimation technique utilizing panel data?

Which type of model has coefficients that vary with i,but are constant with t?

If N is the number of individuals observed in each of T time periods,what is generally true of a "long,narrow" panel?

Which of these assumptions means all error terms are uncorrelated?

For a random effects model the least squares estimator is unbiased and consistent.The errors can be corrected for potential heterogeneity using _________________,but the estimator with minimum variance is _______________.

Which of the following is not a reason random effects (RE)results may be preferred to fixed effects (FE)?

Which of the following assumptions must be made in order to use the pooled least squares estimator,but is relaxed in the cluster robust model?

When should the Hausman-Taylor estimator be used?

Which of these assumptions means the errors are uncorrelated with all x's?

Which of these assumptions indicates homoskedasticity?

Which model is also called an error components model?

What is the difference between balanced and unbalanced panels?

Suppose you have a long,narrow panel of data and estimate a single equation with indicator variables and interaction terms for the individuals.In doing this what assumption from the pooled model have you relaxed?

If N is the number of individuals observed in each of T time periods,what is generally true of a "short,wide" panel?

What is the primary advantage of using panel data rather than a large cross- section data set collected over time?

Which type of model has coefficients that vary with i and t?

How do you test for endogenous regressors,or correlation between the error term and any regressor in a random effects model?

If you perform a Hausman test on a random effects model and have a test statistic that exceeds your critical value,which of the following is not correct?

Which type of model does not have a coefficient that varies with t or i ?

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

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Qualitative and Limited Dependent Variable Models

Filters

For a random effects model the least squares estimator is unbiased and consistent.The errors can be corrected for potential heterogeneity using ___,but the estimator with minimum variance is _.