Question 1

Logit and probit models are more appropriate than linear probability models because:

Accepted Answer

Logit and probit models are designed to produce estimated probabilities that are bounded between 0 and 1, addressing the limitation of linear probability models which can produce probabilities outside this range.

Question 2

Appropriate modelling of limited dependent variables that are assigned numerical values having a natural ordering can be done using:
(I) Probit models
(II) Logit models
(III) Ordered probit models
(IV) Ordered logit models

Accepted Answer

Ordered probit models and ordered logit models are specifically designed for handling dependent variables that are categorical with a natural ordering, making them the appropriate choice for such data.

Question 3

Running a cross-sectional regression on the time-averaged values of the variables is known as a:

Accepted Answer

The between estimator is used in panel data analysis and involves running a regression on the time-averaged values of the variables, focusing on the variation between entities (e.g., individuals, firms, countries) over the entire period under study.

Question 4

Which of the following is a mathematical expression of a time-fixed effects model?

Accepted Answer

The answer of Which of the following is a mathematical...

Question 5

Entity fixed effects models

Accepted Answer

Entity fixed effects models allow for the intercept to vary across entities (e.g., individuals, firms, countries) to account for unobserved heterogeneity, while keeping the slope coefficients constant across entities and over time.

Question 6

The acronym LSDV in panel model estimation stands for

Accepted Answer

LSDV stands for Least Squares Dummy Variable, a method used in panel data analysis to control for individual (or group) effects by introducing a dummy variable for each individual (or group) in the dataset.

Question 7

Which of these is a type of panel estimator approach?
(I) Fixed effects
(II) Random effects
(III) Seemingly unrelated regression effects
(IV) Time-varying effects

Accepted Answer

Fixed effects and random effects are both types of panel estimator approaches used in econometrics to analyze panel data, which consists of observations over time for the same entities. Seemingly unrelated regression is a different econometric technique that deals with multiple equations with correlated error terms, and time-varying effects refer to models where parameters change over time but are not specifically a type of panel estimator approach.

Question 8

Which of these are advantages of using panel data?
(I) We can address a broader range of issues and tackle more complex problems than would be possible with pure time-series or pure cross-sectional data alone
(II) It allows us to increase the number of degrees of freedom
(III) It allows us to increase the power of the tests
(IV) We can remove the impact of certain forms of omitted variables bias in regression results

Accepted Answer

Panel data, which combines time-series and cross-sectional data, offers several advantages: it enables the study of more complex issues, increases degrees of freedom and the power of statistical tests, and can mitigate omitted variable bias by controlling for variables that vary across entities but not over time.

Question 9

Which of the following statements about logit and probit models is true?
(I) They cannot be estimated by ordinary least squares
(II) They can be estimated using maximum likelihood
(III) They can be estimated using non-linear least squares
(IV) They can be estimated using instrumental variables

Accepted Answer

The answer of Which of the following statements about logit...

Question 10

What of the following is a mathematical expression of a random effects model?

Accepted Answer

The answer of What of the following is a mathematical...

Question 11

If the maximised value of the log-likelihood function for a logit model is 34.55 and for a restricted model where all of the slope parameters are set to zero is 30.67, what is the pseudo-R²?

Accepted Answer

The answer of If the maximised value of the log-likelihood...

Question 12

To test for unit roots in panel data, Levin, Lin and Chu (2002) develop a test based on the equation . What is the appropriate null hypothesis for this test?

Accepted Answer

The answer of To test for unit roots in panel...

Quiz 11: Panel Data and Limited Dependent Variable Models

Logit and probit models are more appropriate than linear probability models because:

Appropriate modelling of limited dependent variables that are assigned numerical values having a natural ordering can be done using: (I) Probit models (II) Logit models (III) Ordered probit models (IV) Ordered logit models