Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge

Exercise 10

Suppose that, for one semester, you can collect the following data on a random sample of college juniors and seniors for each class taken: a standardized final exam score, percentage of lectures attended, a dummy variable indicating whether the class is within the student's major, cumulative grade point average prior to the start of the semester, and SAT score.

(i) Why would you classify this data set as a cluster sample? Roughly, how many observations would you expect for the typical student?

(ii) Write a model, similar to equation, that explains final exam performance in terms of attendance and the other characteristics. Use s to subscript student and c to subscript class. Which variables do not change within a student?

(iii) If you pool all of the data and use OLS, what are you assuming about unobserved student characteristics that affect performance and attendance rate? What roles do SAT score and prior GPA play in this regard?

(iv) If you think SAT score and prior GPA do not adequately capture student ability, how would you estimate the effect of attendance on final exam performance?

Equation

Step 1 of 5

(i)

The data on the random sample of college juniors and seniors when taken for each class for one semester relating to a standardized final exam score, percentage of lectures attended, a dummy variable indicating whether the class is within the student’s major, CPA prior to start of the semester and SAT score, it would be classified as a cluster example because data pertains to class (a cluster group) and the students are sampled as per the number of class in the study

Roughly, given the variables observed for each sample students across different class, it is expected that for the typical student there would be four observations. However, this would depend on the number of classes attended by the sample students.