Exam 11: Panel Data and Limited Dependent Variable Models

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

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

The acronym LSDV in panel model estimation stands for

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

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

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

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

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

Entity fixed effects models

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

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?

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?