Exam 14: Advanced Panel Data Methods

The value of the estimated transformation parameter in generalized least square estimation that eliminates serial correlation in error terms indicates whether the estimates are likely to be closer to the pooled OLS or the fixed effects estimates.

The random effects estimate is identical to the fixed effects estimate if the estimated transformation parameter , ,in generalized least squares estimation that eliminates serial correlation between error terms is,_____.

The estimator obtained through regression on quasi-demeaned data is called the _____.

A pooled OLS estimator that is based on the time-demeaned variables is called the _____.

Which of the following assumptions is required for obtaining unbiased fixed effect estimators?

Which of the following types of variables cannot be included in a fixed effects model?

A data set is called an unbalanced panel if it has missing years for at least some cross-sectional units in the sample.

Which of the following is a reason for using the correlated random effects approach?

Which of the following assumptions is required for obtaining unbiased random effect estimators?

Which of the following statements is true?

The random effects approach _____.

Which of the following is true of the correlated random effects approach (CRE)?

The correlated random effects approach cannot be applied to models with many time-varying explanatory variables.

In a random effects model,we assume that the unobserved effect is correlated with each explanatory variable.

Pooled ordinary least squares estimation is commonly applied to cluster samples when eliminating a cluster effect via fixed effects is infeasible or undesirable.

An economist wants to study the effect of income on savings.He collected data on 120 identical twins.Which of the following methods of estimation is the most suitable method,if income is correlated with the unobserved family effect?

In the correlated random effects approach,the regression model includes _____.

Which of the following is a property of dummy variable regression?

Which of the following is a difference between a fixed effects estimator and a first-difference estimator?

What should be the degrees of freedom (df)for fixed effects estimation if the data set includes 'N' cross sectional units over 'T' time periods and the regression model has 'k' independent variables?