This is an intensive course where 16 weeks of econometrics material is compressed into 4 weeks. The entire course is completed online with online video lectures, online quizzes, online homework assignments, online discussions, and online exams. Completing the exams away from campus requires the use of remote proctoring software and a webcam. This course moves very fast with multiple assignments due every week. Student will need to have enough time available to watch several hours of lecture videos, read 2 or 3 chapters of the text book, and complete 4 to 6 assignments every week. I do not recommend taking this course if you are will not have at least 5 hours available to spend learning econometrics every day for the 4-week period.

 

Many students have told me this was the most difficult course they have ever taken. You may have heard that this is a difficult course from other students. I want to emphasize that it is the challenging material that makes this course difficult, not the professor. I will put great effort into helping you develop a solid understanding of econometrics. One reason many students find the course to be challenging is because econometrics is cumulative with each lesson building on comprehension of the material that came before. My advice is that you should read the textbook, watch all the videos, take notes while you are watching the videos, and keep up on your homework and quizzes. This isn’t the kind of course that you can let slide until just before an exam.

This course provides an introduction to econometrics where you will learn the tools that will enable you to conduct empirical analysis using economic data. The course examines the statistical techniques used in testing economic theories, estimating causal effects, and making predictions. Emphasis is placed on estimating a single equation and the problems associated with such estimation. As part of the course, students will estimate equations using STATA, a statistical software package.

To test for discriminatio in the mortgage loan market, a linear probability model can be used:

 

approve = Beta0 + Beta'white' + other factors

 

a) Regress approve on white. What is interpretation of the estimated coefficient on white? IS it statistically significant? Is it economically siginficant (practically large)?

 

b) As controls, add the variables hrat, obrat, loanprc, unem, male, married, dep, sch, cosign, pubrec, martlat1, mortlaat2, and vr. What happens to the coefficient on white? Is there still evidence of race discirmination?