Deck 17: Qualitative and Limited Dependent Variable Models

Question 1

Which of the following is not a problem with the linear probability model?

A)assumes constant marginal effects
B)generates predictions outside the (0,1)interval
C)heteroskedastic error term
D)coefficient estimates are biased

Answer 1

D

Question 2

For which type of model does the researcher have to assume independence of irrelevant alternatives?

A)probit
B)multinomial logit
C)linear probability
D)latent variable model

Answer 2

B

Question 3

Which model requires the assumption of independence of irrelevant alternatives?

A)conditional logit
B)nested logit
C)multinomial probit
D)mixed logit

Answer 3

A

Question 4

For what dependent variable should a Poisson regression model be considered?

A)satisfaction with job
B)GPA (grade point average)
C)number of mobile phones owned by a household
D)level of education completed

Question 5

Unobservable variables that enter into decisions are called

A)latent variables
B)endogenous variables
C)heterogeneity
D)count data

Question 6

What is the difference between count data and ordered data?

A)there is no difference,they are two names for the same thing
B)in count data the dependent variable is an integer that represent a measurement,in ordered data it represents a rank
C)ordered data can be continuous while count data are discrete
D)count data indicate ranking while ordered data are categorical

Question 7

When a substantial proportion of the observations for a dependent variable take on a limiting value,such as zero,the data are said to be

A)truncated
B)qualitative
C)categorical
D)censored

Question 8

When should a probit model be used?

A)when you need a binary choice model that allows for varying marginal effects
B)when you need to model the heteroskedasticity in the linear probability model
C)to allow for endogenous regressors in a binary choice model
D)to allow for multiple explanatory variables in a binary choice model

Question 9

When a decision maker has to choose between two mutually exclusive outcomes an econometrician may choose to use a(n)

A)binary choice model
B)ECM
C)random effects model
D)fixed effects model

Question 10

What is the primary difference between ordered probit and ordered logit?

A)ordered logit requires assumption of independence of irrelevant alternatives,ordered probit does not
B)they make different assumptions about the distribution of coefficient estimates
C)ordered logit allows variables to vary by choice,ordered probit does not
D)they make different assumptions about the distribution of the error term

Question 11

When testing hypotheses of probit or logit coefficients,what 2 statistical tests are generally used?

A)Wald and Likelihood Ratio
B)z-test and t-test
C)LM and Hausman
D)F-test and R²

Question 12

When should a Heckit model be used?

A)when the sample was not randomly selected
B)when the sample is small and error terms are not normally distributed
C)as the alternative model to run a Hausman test on a Tobit model
D)to minimize the variance of the error term when the sample selection process is suspect

Question 13

How are logit and probit models different?

A)probit is estimated by least squares,logit by maximum likelihood
B)probit uses the cumulative density function (cdf)of the standard normal distribution and logit uses the cdf of the logistic function
C)logit is for binary choice models and probit is used when there are two or more choices
D)probit allows for endogenous regressors,logit does not

Question 14

For which distribution is the mean equal to the variance?

A)standard normal
B)binomial
C)Poisson
D)chi-square

Question 15

Which of the following statements is not true regarding a logit model?

A)it allows for marginal effects that vary with explanatory variables
B)it is estimated by maximum likelihood
C)it can be adjusted to accommodate more than 2 choice options
D)it always generates larger marginal effects than a probit model

Question 16

When is a Tobit model used?

A)when you have censored data
B)for categorical data with a normally distributed error term
C)when you want to combine a probit and multinomial logit
D)to estimate varying marginal effects in a binary choice model

Question 17

When using least squares to estimate a model with a censored dependent variable,the results are

A)biased and inconsistent
B)unbiased,but not minimum variance
C)unbiased and consistent
D)biased but consistent

Question 18

What is the difference between multinomial logit and conditional logit?

A)conditional logit allows for variables to vary by individual and choice while multinomial logit only allows them to vary by individual
B)multinomial logit allow for 3+ choices,conditional logit only accommodates 2
C)multinomial logit is estimated with least squares,conditional logit by maximum likelihood
D)multinomial logit has different coefficients for each choice equation,conditional logit has equal coefficients across choice equations on common variables

Question 19

What is accomplished by using a Tobit model rather than the least squares estimator?

A)it generate unbiased and consistent estimates on censored data
B)it corrects sample selection bias
C)it allows for choice models to be estimated using GLS
D)it generates the same unbiased coefficient estimates,but with smaller variances

Question 20

How is the average marginal effect calculated for a probit or logit model?

A)taking the marginal effect at the mean of the sample
B)mean marginal effects are always .5 in a binary choice model
C)calculate the marginal effects for each observation,then take the mean
D)take the mean of the marginal effects at the 5^th and 95^th percentile

Question 21

What type of model consists of a two stage process where the first stage is a binary choice model of sample selection and the second stage is the linear model of interest?

A)Tobit
B)Heckit
C)multinomial logit
D)probit