Theory and Practice of Econometrics
Spring 2020
Course Information
Course Content
Class Format
Prerequisites
Office Hours
Exams and Other Assignments
Grading
Texts and Software
Course Content
Econometrics is the application of statistical techniques to the analysis of economic data. It has its basis in pure applied statistics, but has developed as a distinct branch of the parent subject in order to serve particular data-analysis needs often faced by economists. All econometric techniques are statistical, but not all statistical techniques would be considered econometrics. The best (perhaps the only) way to learn econometrics is to do econometrics. This course will emphasize hands-on application of econometric techniques with natural data, not textbook proofs of statistical theorems. The principal mission (learning objective) of this course is to provide students with a set of econometric tools that can be applied as needed in economic research, including thesis work.
Class Format
This class meets from 11:00 to 11:50 on Mondays, Wednesdays, Thursdays, and Fridays in PAB104. Most classes will be a lecture/conference session that will examine econometric techniques and their applications. The purpose of having four class sessions per week to to provide sufficient time to discuss assignments and applications during class time.
Prerequisites
Economics: The only economics prerequisite is Econ 201. In practice, the more economics you have taken, the more applications of econometrics you will recognize as we proceed through the course.
Mathematics: Math 141 or equivalent background in statistical analysis is an important prerequisite. Students will be expected to have a working understanding of basic statistics, including the concepts of probability distributions, expected value and variance, estimators, unbiasedness, hypothesis tests, and confidence intervals. A very brief review of these topics is conducted January 22-24 for those whose background in statistics may be limited or rusty. Matrix and vector notation will also be used in class at times. For those with no background, a session covering basic matrix methods such as addition, multiplication, transposition, and using matrix inverses will be offered early in the semester. The main textbook has appendices covering probability, statistics, and matrix methods. You should review these sections to make sure that you have a basic understanding of these topics.
Office Hours
The instructor will hold office hours in Vollum 229 on Mondays from 12:30 to 2:00 and Tuesdays from 10-11:30. Students for whom these hours are inconvenient may make appointments at other times by contacting the instructor at extension 7308 or by email to parker@reed.edu.
Exams and Other Assignments
Exams: There will be a mid-term exam and a comprehensive final exam. Both exams may have in-class and/or take-home parts. There will be no term paper or term project for the course.
Daily problems: There will be one or a few short questions or problems related to each day's class topic. Your answers should be submitted at the beginning of class. The intent of these assignments is to help us use class time more efficiently by focusing students' attention on an important point that we will cover. In most cases, these assignments should take only a few minutes once you have done the day's reading. If it's taking you more than a half-hour or so to do this work, then you should submit what you have done and ask related questions in class. These assignments will be not be formally graded as right or wrong (although it's always better to get them right), but rather assessed on the basis of meaningful engagement and preparation. It is not expected that every students will complete every daily assignment, but missing on a regular basis is not acceptable. Late submissions will not be accepted because the whole purpose of these assignments is class preparation.
Weekly econometric projects: An applied project using statistical software to estimate models will be assigned most weeks of the semester. Detailed information about assignments will be posted weekly on the Assignments page of the Web site. The weekly econometric projects will usually be done by teams of two students, who jointly submit a single collaborative report. Guidelines for collaboration on the projects and a sample report are posted on the Web site. The instructor will assign teams; you will work with a different partner each week. Reports are to be submitted by electronic mail no later than 11:59 Monday night. The instructor will read the reports and send email comments to each student prior to Wednesday's class session. We will usually devote some time during the Wednesday class to discussion of the projects. Because of the short turnaround time between the submission deadline and the class discussion, late work will be severely penalized. Projects received between midnight Monday and midnight Tuesday will receive half credit. Projects more than 24 hours late will not be accepted.
Grading
Grades will be based on all information the instructor has about your level of understanding of econometrics. This includes evidence from exams, homework, projects, class participation, and individual discussions.
Texts and Software
Text: The main text for this course is the 7th edition of Jeffrey M. Wooldridge's text Introductory Econometrics: A Modern Approach. This is a modern text that covers recent developments in econometrics more effectively than alternative texts. It has extensive examples of applications and good problems, both theoretical and applied. Students will be expected to have unlimited access to this book, which is available in the Reed Bookstore. A couple of copies will be on reserve.
Other Texts: There are several econometrics textbooks on reserve. Some of these are less advanced than Wooldridge; others are more rigorous. Most sections of the reading list have references to relevant sections of these texts that cover the same topic. There will be some required reading assignments from these alternative texts, but most of the time you are simply encouraged to explore these texts if you find that our presentation is inappropriately easy or difficult.
Software: Students will use the statistical package Stata 16 (or an earlier version) for most course assignments. This software is available on the student-access computers in the IRCs and the Library. If you are interested in having your own copy of Stata for either PC or Mac, you may purchase a student license to Intercooled Stata 16 from the Stata Web site. A 6-month version costs $48, a one-year license is $94, and a perpetual license to Stata 16 is $225 at https://www.stata.com/order/new/edu/gradplans/student-pricing/. The full printed documentation for Stata is available in pdf form from within Stata, so printed manuals should be unnecessary.