Question 1

When a variable is top coded, its value is known only up to a certain threshold.

Accepted Answer

A) True 
 B)False  True

Question 2

The nominal distribution for count data is the:

Accepted Answer

A) binomial distribution. 
B) normal distribution. 
C) Poisson distribution. 
D) Bernoulli distribution. 
A) binomial distribution. 
B) normal distribution. 
C) Poisson distribution. 
D) Bernoulli distribution. C

Question 3

The model: G(z) = [exp(z)]/[1 + exp(z)], where G is between zero and one for all real numbers 'z', represents a:

Accepted Answer

A) logit model. 
B) probit model. 
C) Tobit model. 
D) linear probability model. 
A) logit model. 
B) probit model. 
C) Tobit model. 
D) linear probability model. A

Question 4

Which of the following tests can be used to test hypotheses with multiple restrictions under a Tobit model?

Accepted Answer

A) White test 
B) Wald test 
C) Dickey Fuller test 
D) Durbin Watson test 
A) White test 
B) Wald test 
C) Dickey Fuller test 
D) Durbin Watson test

Question 5

The _____ model is designed to model corner solution dependent variables.

Accepted Answer

A) linear probability 
B) logit 
C) probit 
D) Tobit 
A) linear probability 
B) logit 
C) probit 
D) Tobit

Question 6

In case of endogenous sample selection, OLS is unbiased but consistent.

Accepted Answer

A) True 
 B)False

Question 7

Which of the following statements is true?

Accepted Answer

A) OLS estimates in censored regression models are consistent estimators of the population coefficients. 
B) In a truncated regression model, the samples are not included randomly from an underlying population but are based on a given rule. 
C) In a censored regression model, units in the sample are taken from a particular subset of the population. 
D) Maximum likelihood estimators are consistent in truncated regression models even if there is nonnormality or heteroskedasticity in the error terms. 
A) OLS estimates in censored regression models are consistent estimators of the population coefficients. 
B) In a truncated regression model, the samples are not included randomly from an underlying population but are based on a given rule. 
C) In a censored regression model, units in the sample are taken from a particular subset of the population. 
D) Maximum likelihood estimators are consistent in truncated regression models even if there is nonnormality or heteroskedasticity in the error terms.

Question 8

The model: y* =   0​ + x   + u, given u|x ˜ Normal(0,   2) and y = max(0, y*) represents a:

Accepted Answer

A) ARCH model. 
B) GARCH model 
C) Tobit model 
D) logit model 
A) ARCH model. 
B) GARCH model 
C) Tobit model 
D) logit model

Question 9

Which of the following statements is true?

Accepted Answer

A) A probit or logit model should be used for corner solution outcomes, and a Poisson regression model should be used for a binary response. 
B) A Poisson regression model should be used for corner solution outcomes, and a probit or logit model should be used for a binary response. 
C) A probit or logit model should be used for count variables, and a Poisson regression model should be used for a binary response. 
D) A Poisson regression model should be used for count variables, and a probit or logit model should be used for a binary response. 
A) A probit or logit model should be used for corner solution outcomes, and a Poisson regression model should be used for a binary response. 
B) A Poisson regression model should be used for corner solution outcomes, and a probit or logit model should be used for a binary response. 
C) A probit or logit model should be used for count variables, and a Poisson regression model should be used for a binary response. 
D) A Poisson regression model should be used for count variables, and a probit or logit model should be used for a binary response.

Question 10

Which of the following is an example of a binary response model?

Accepted Answer

A) MA model 
B) ARCH model 
C) GARCH model 
D) Logit model 
A) MA model 
B) ARCH model 
C) GARCH model 
D) Logit model

Question 11

In the probit model, G is the:​

Accepted Answer

A) ​standard normal cumulative distribution function. 
B) ​cumulative distribution of normal distribution function. 
C) ​standard normal probability distribution function. 
D) ​normal probability distribution function. 
A) ​standard normal cumulative distribution function. 
B) ​cumulative distribution of normal distribution function. 
C) ​standard normal probability distribution function. 
D) ​normal probability distribution function.

Question 12

The likelihood ratio statistic is given by:

Accepted Answer

A) LR = (log-likelihoodunrestricted + log-likelihoodrestricted) 
B) LR = 2 × (log-likelihoodunrestricted + log-likelihoodrestricted) 
C) LR = (log-likelihoodunrestricted - log-likelihoodrestricted) 
D) LR = 2 × (log-likelihoodunrestricted - log-likelihoodrestricted) 
A) LR = (log-likelihoodunrestricted + log-likelihoodrestricted) 
B) LR = 2 × (log-likelihoodunrestricted + log-likelihoodrestricted) 
C) LR = (log-likelihoodunrestricted - log-likelihoodrestricted) 
D) LR = 2 × (log-likelihoodunrestricted - log-likelihoodrestricted)

Question 13

A count variable refers to a dependent variable that can take on:

Accepted Answer

A) nonnegative integer values. 
B) nonnegative fractional values. 
C) negative fractional values. 
D) negative integer values. 
A) nonnegative integer values. 
B) nonnegative fractional values. 
C) negative fractional values. 
D) negative integer values.

Question 14

In the Poisson regression model, the probability distribution is given by P(y = h|x) = exp[-exp(xâ)][exp(xâ)]h/h!, h = 0, 1, …..

Accepted Answer

A) True 
 B)False

Question 15

​The difference between the LPM model and the logit and probit models is that:

Accepted Answer

A) ​the LPM assumes constant marginal effects for all the independent variables, while the logit and probit models imply diminishing magnitudes of the partial effects. 
B) ​the LPM assumes constant marginal effects for some of the independent variables, while the logit and probit models imply diminishing magnitudes of the partial effects. 
C) ​the LPM assumes constant marginal effects for the dependent variable, while the logit and probit models imply diminishing magnitudes of the partial effects. 
D) ​the LPM assumes different marginal effects for all independent variables, while the logit and probit models imply diminishing magnitudes of the marginal effects. 
A) ​the LPM assumes constant marginal effects for all the independent variables, while the logit and probit models imply diminishing magnitudes of the partial effects. 
B) ​the LPM assumes constant marginal effects for some of the independent variables, while the logit and probit models imply diminishing magnitudes of the partial effects. 
C) ​the LPM assumes constant marginal effects for the dependent variable, while the logit and probit models imply diminishing magnitudes of the partial effects. 
D) ​the LPM assumes different marginal effects for all independent variables, while the logit and probit models imply diminishing magnitudes of the marginal effects.

Question 16

The model: G(z) =   , where   (z) = (2   )-1/2exp(-z2/2) represents a:

Accepted Answer

A) Tobit model. 
B) logit model. 
C) probit model. 
D) linear probability model. 
A) Tobit model. 
B) logit model. 
C) probit model. 
D) linear probability model.

Question 17

Which of the following statements is true?

Accepted Answer

A) Taking logarithmic of a count variable is a suitable way to model it. 
B) All standard count data distributions exhibit heteroskedasticity. 
C) The nonlinear least squares estimation aims at maximizing R2. 
D) Count variables cannot take on the value zero. 
A) Taking logarithmic of a count variable is a suitable way to model it. 
B) All standard count data distributions exhibit heteroskedasticity. 
C) The nonlinear least squares estimation aims at maximizing R2. 
D) Count variables cannot take on the value zero.

Question 18

Which of the following statements is true?

Accepted Answer

A) A truncated regression is a special case of a random sample selection. 
B) Nonrandom sample selection can arise in cases of cross-sectional and time series data, but not in the case of panel data. 
C) The Tobit regression model is based on endogenous sample selection. 
D) The censored regression model is based on nonrandom sample selection. 
A) A truncated regression is a special case of a random sample selection. 
B) Nonrandom sample selection can arise in cases of cross-sectional and time series data, but not in the case of panel data. 
C) The Tobit regression model is based on endogenous sample selection. 
D) The censored regression model is based on nonrandom sample selection.

Question 19

​A common form of sample selection that does not observe the dependent variable because of the outcome of another variable is called _____.

Accepted Answer

A) ​nonrandom sample selection 
B) ​exogenous sample selection 
C) ​incidental truncation 
D) ​endogenous sample selection 
A) ​nonrandom sample selection 
B) ​exogenous sample selection 
C) ​incidental truncation 
D) ​endogenous sample selection

Question 20

​The maximum likelihood estimates for Tobit models can be more easily obtained than the OLS estimates of a linear model.

Accepted Answer

A) True 
 B)False

When a variable is top coded, its value is known only up to a certain threshold.

The nominal distribution for count data is the:

The model: G(z) = [exp(z)]/[1 + exp(z)], where G is between zero and one for all real numbers 'z', represents a:

Which of the following tests can be used to test hypotheses with multiple restrictions under a Tobit model?

The _____ model is designed to model corner solution dependent variables.

In case of endogenous sample selection, OLS is unbiased but consistent.

Which of the following statements is true?

The model: y* = ₀ + x + u, given u|x ˜ Normal(0, ²) and y = max(0, y*) represents a:

Which of the following statements is true?

Which of the following is an example of a binary response model?

In the probit model, G is the:

The likelihood ratio statistic is given by:

A count variable refers to a dependent variable that can take on:

In the Poisson regression model, the probability distribution is given by P(y = h|x) = exp[-exp(xâ)][exp(xâ)]h/h!, h = 0, 1, …..

The difference between the LPM model and the logit and probit models is that:

The model: G(z) = , where (z) = (2 )^-1/2exp(-z²/2) represents a:

Which of the following statements is true?

Which of the following statements is true?

A common form of sample selection that does not observe the dependent variable because of the outcome of another variable is called _____.

The maximum likelihood estimates for Tobit models can be more easily obtained than the OLS estimates of a linear model.

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

Heteroskedasticity

More on Specification and Data Issues

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Sries 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 Strage Least Squares

Simultaneous Equations Models

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Exam 17: Limited Dependent Variable Models and Sample Selection Correctons

When a variable is top coded, its value is known only up to a certain threshold.

The nominal distribution for count data is the:

The model: G(z) = [exp(z)]/[1 + exp(z)], where G is between zero and one for all real numbers 'z', represents a:

Which of the following tests can be used to test hypotheses with multiple restrictions under a Tobit model?

The _____ model is designed to model corner solution dependent variables.

In case of endogenous sample selection, OLS is unbiased but consistent.

Which of the following statements is true?

The model: y* = 0​ + x + u, given u|x ˜ Normal(0, 2) and y = max(0, y*) represents a:

Which of the following statements is true?

Which of the following is an example of a binary response model?

In the probit model, G is the:​

The likelihood ratio statistic is given by:

A count variable refers to a dependent variable that can take on:

In the Poisson regression model, the probability distribution is given by P(y = h|x) = exp[-exp(xâ)][exp(xâ)]h/h!, h = 0, 1, …..

​The difference between the LPM model and the logit and probit models is that:

The model: G(z) = , where (z) = (2 )-1/2exp(-z2/2) represents a:

Which of the following statements is true?

Which of the following statements is true?

​A common form of sample selection that does not observe the dependent variable because of the outcome of another variable is called _____.

​The maximum likelihood estimates for Tobit models can be more easily obtained than the OLS estimates of a linear model.

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

Heteroskedasticity

More on Specification and Data Issues

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Sries 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 Strage Least Squares

Simultaneous Equations Models

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

The model: y* = ₀ + x + u, given u|x ˜ Normal(0, ²) and y = max(0, y*) represents a:

In the probit model, G is the:

The difference between the LPM model and the logit and probit models is that:

The model: G(z) = , where (z) = (2 )^-1/2exp(-z²/2) represents a:

A common form of sample selection that does not observe the dependent variable because of the outcome of another variable is called _____.

The maximum likelihood estimates for Tobit models can be more easily obtained than the OLS estimates of a linear model.