<< Chapter < Page Chapter >> Page >

Butler, finegan, and siefried (1998).

The obvious first step is to find and print a copy of the article by Butler, Finegan, and Siefried. In fact, do not proceed any further in reading this module until you have read the article. We will discuss in class what the authors do in the paper and how clearly they present their conclusions. In this first pass at the article you are to pay attention to how convincing you find their arguments to be. Since everyone in the class has completed an intermediate microeconomics course, your discussion of their conclusions should reflect your own experiences. Also, you need to be able to discuss in class the estimation strategy they use in the paper. In particular, you will need to be able to identify what the source of the data is and what equations did they estimate. Also, try to determine how the estimations in the "first" stage are used in the estimations of the "second" stage. Why did the authors use a two-stage estimation strategy?

Also, what do you think the authors mean in their description of their estimation strategy by their statement about the estimation methods they use:

Estimation Methods and Expectations
To cope with the selection bias problem, we use a two-stage estimation procedure. The first stage employs an ordered probit model to predict the highest level of calculus attained by each student prior to taking each intermediate economic theory course.... In the second stage, the student's grade in MICRO-2 ... (the `outcome') is regressed on the actual level of calculus attained, the grade earned in that calculus course, the predicted residual in the grade equation that we would expect on the basis of the actual level of calculus attained, and a roster of control variables reflecting ability and motivation. Individuals are the unit of observation. Ordinary least squares estimation is used because there are twelve categories of grades which are commonly interpreted as cardinal measures of performance (as is implied by the calculation of `grade point averages'). (Butler, Finegan, and Siegfried, 1998: 188)

The ordered-probit model

In what follows you are to “replicate” the equations the authors estimate in the paper for the intermediate microeconomics course. In order to complete this assignment you will need to figure out several things including (1) what an ordered-probit model is and (2) how to use Stata to estimate an ordered-probit model. In this section of the module we introduce the ordered-probit model. I strongly encourage you to consult Greene (1990: 703-706) for an excellent and clear discussion of the ordered-probit model. The discussion here follows Greene closely.

It is common for surveys to have questions that require the responder to choose one of several categories that have an innate order to them. For instance, most course evaluations ask the respondent to choose an answer to a question that reflects their agreement with a statement about the course. For instance, the question might read, "The Professor was interested in the material taught in the class" where the student completing the evaluation would choose a number from 1 to 9 where a 1 indicates complete disagreement with the statement and a 9 reflects complete agreement with the statement. Thus, there is an order to the potential answers. Using a logit, probit, or multilogit model would completely ignore this order. A linear regression is inappropriate because OLS treats the difference between answers of 1 and 2 as being the same as the difference between a 7 and and 8, when in fact the numbers only provide a ranking.

Get Jobilize Job Search Mobile App in your pocket Now!

Get it on Google Play Download on the App Store Now




Source:  OpenStax, Econometrics for honors students. OpenStax CNX. Jul 20, 2010 Download for free at http://cnx.org/content/col11208/1.2
Google Play and the Google Play logo are trademarks of Google Inc.

Notification Switch

Would you like to follow the 'Econometrics for honors students' conversation and receive update notifications?

Ask