Quantitative Economics Analysis

Economics 370

Location and Time
Lecture 166  MacLean Hall MWF 11:30

Instructor
Gregory Stutes
Office: 380 K MacLean Hall
Telephone: 477-4027

E-mail: stutes@mnstate.edu
Office Hours: MW 1:30-4:30 & TR 9:00-11:00

Textbook:

Introduction to Econometrics, 2^nd edition, by James H. Stock and Mark W. Watson.

The first edition will be acceptable to use in most cases, and is cheaper. Lectures, examples, and homework problems will all be from the second edition.

Software:

Econometrics is by nature a “hands on” class, and we will be working extensively with data. In this class I will be working with Excel, Stata, and E-views. Software today is very easy to use (point-and-click for most things). An added advantage is that all of the data sets and replication programs from the textbook are available for immediate use. The bookstore has the text bundled with the student version of e-views; I am indifferent about which econometrics program you use.  You will need a program more sophisticated than Excel, but there are many options available.  Some are free.  A recent grad just e-mailed and suggested that you should learn SAS if you want a competitive advantage in the business word.

Course Description

Decision making for planning, policy, and management relies heavily on the collection, analysis, and interpretation of quantitative data.  These tasks are performed through statistical reasoning and model building.  Quant methods is designed to help you build those skills.  Traditionally the class was exclusively econometric theory and applications.  A majority of the class will continue to present those topics, but my class will included economic nuggets.  Economics and finance use a variety of quantitative methods and I would be limiting you academic career if I did not at least introduce some of these topics.  Expect daily diversions into these nuggets.

Expected outcomes:

After successfully completing this class, I expect you to be able to:

• Identify types of problems that lend themselves to quantitative analysis, be able to ask researchable questions, and formulate hypotheses.
• Identify the procedures to test hypotheses and be able to clearly describe the intuition behind those procedures
• Carry out sample regression analysis, understand the meaning of the results, and their implications.
• Be able to apply tests to assess the statistical significance of estimated effects and the specification of your model.
• Be able to apply the knowledge acquired to a research project of your choice.
• Be able to apply the knowledge attained in your previous writing and English classes so that you are able to a research paper.

Assessment and grading:

Your grade in this class will be based on a combination of problem sets (20%), three exams (20% each) and a termpaper (20%).

You may work in groups to complete the problem sets, but each of you must write up and submit your answers separately. Include the names of all your group members when submitting your answers. 

The exams will be open book and open notes, and you will need a calculator.

I will excuse absences only in cases where you can provide documented evidence of a ‘valid’ absence on the original day. Some examples of ‘valid’ absences are: family emergency, medical conditions, religious observances, or representing MSUM at external events (conferences, ‘away’ games, etc.). If you miss an exam for an excused, documented reason, see me as soon as possible to arrange a makeup exam. Missing an exam for any other reason will result in a grade of 0. If you think you have a valid reason for missing class, it is your responsibility to discuss it with me as far in advance (or as soon after the fact) as possible, and to provide objective documentation.

Special arrangements:

Any student who, because of a disability, may require special arrangements in order to meet the course requirements should contact me as soon as possible to make any necessary arrangements. Students should present appropriate verification from Student Disability Services during the instructor’s office hours.

John Kane's List of Data Sites

Course outline: