Econ 671 Syllabus, Fall 2013

This class has three goals. You are going to study and learn some fundamental techniques in econometrics and statistics so that you can use them in your future research. You are also going to learn some of the basic theoretical concepts in econometrics so that you can understand new techniques when you encounter them in future classes and later in your career. Finally, you’re going to learn how to use a computer to do statistical and econometric analysis.

Contact information

If you have questions about the course material, the best times to address them are in the scheduled lectures or during office hours. We can probably resolve questions or concerns about the course administration over email, but if you have urgent questions please call me or stop by my office.

Gray Calhoun, instructor:

Shufen Chen, TA:

Scheduling and grading

The class will meet twice a week for almost two hours. The next table lists the most important times and dates. If you have any conflicts please let me know as soon as possible.

Your final grade will be based on homework and a take-home final exam; each counts for 50% of your grade.

The weekly review session will be used primarily for discussion of the homework and practice questions, but will also be used to present new material that supplements the regular lecture.

Software

You need to learn how to program a computer to do statistical and econometric analysis. We’re going to use the programming language R in this class—it is a specialized programming language that is designed for sophisticated data analysis. It has three advantages over other statistical packages: it is very extensible, so designing and using new estimators is easy; the graphics it produces are excellent; and it is free (other packages have their own advantages as well, obviously). Also, I use R in my own research so my advice on programming is more likely to be useful than if we were to use another language. You can download the latest version of R from the website http://www.r-project.org. There are free manuals at the same website.

Reading

The required textbooks are Gal97, CB02, Gre12, and KZ08. Gal97 is an excellent overview of probability and asymptotic theory. CB02 gives a good explanation of basic statistics. Gre12 will be a useful reference later in your career and covers many econometric estimators. KZ08 is relatively cheap and is also available online through the library (we have an institutional subscription to SpringerLink, which is the publisher’s website for e-books). You may want to save pdf versions of its chapters to your computer instead of purchasing the book from the bookstore. You should also download and install the R package that accompanies this book, called the AER package.

Required texts

Freedman (2009) covers the intuition behind regression, is less technically demanding than the textbooks, and is exceptionally well written and insightful. Miller (2005) explains how to write up and present empirical research. Miller has written another book (2004, The Chicago Guide to Writing about Numbers) but all of its material is contained in Miller (2005). Tufte (1990, 2001) discusses effective statistical graphics and maps for displaying data. Polya (1945) discusses mathematical problem solving.

You’ll be required to buy Hayashi (2000) next semester, so you may want to buy it now as another source of material (it uses Generalized Method of Moments as an organizing principle for this material). Bruce Hansen has a free Econometrics textbook on his website. I’m also in the process of converting my lecture notes into a textbook, but it is quite disorganized now and is unlikely to be much help; source code and pdfs are available on GitHub (also see http://www.econometricslibrary.org).

I am going to assume that you’ve taken undergraduate Econometrics when I teach the class. If you haven’t, or if it’s rusty, you may want to consult an undergraduate textbook for a less technical introduction to some of the material. Wooldridge (2012) is a good option. If you have not taken even an introductory statistics class (covering basic probability, sample averages, t-tests, etc.) you should buy and read Freedman, Pisani, and Purves (2007) ASAP (you can read it this weekend). You may want to purchase older editions of these books since they are somewhat expensive.

This would also be a good time for you to begin reading the Journal of Economic Literature and paying attention to working papers in your field announced at http://nep.repec.org.

Other reading

You should try to understand many different approaches to data analysis and modeling. These books span several different philosophies and make excellent vacation reading (many of these authors have other books that I’d also recommend, but it’s a long list as is). In alphabetical order:

Course Material

I’ll assign specific readings before each lecture during the semester. This is a tentative and optimistic plan:

Probability, lectures 1–4

This section’s material is covered in: Gal97 chapters 1–3; CB02 chapters 1, 2, and 4; and Gre12 appendix B.

Point estimation, lectures 5–11

Covered in: CB02 chapters 3, 5–7, and 9; and Gre12 chapters 2 and 4 and appendix C.

Inference, lectures 12–16

Covered in: CB02 chapters 8 and 9; and Gre12 chapters 5 and 16 and appendix C.

Asymptotic statistics, lectures 17–23

Covered in: Gal97 chapter 4, CB02 chapters 5 and 10, and Gre12 chapter 4 and appendix D

Understanding linear regression

Read Fis26, Fre91, and Ros05 for general background (over Thanksgiving break, if not earlier) and Gre12 chapters 1–10 (some chapters are tied to specific lectures, some are not) as well as the following papers.

Additional references

University policies

The following policies apply to every course at Iowa State University. They are listed here for your convenience and reference.

Academic dishonesty

The class will follow Iowa State University’s policy on academic dishonesty. Anyone suspected of academic dishonesty will be reported to the Dean of Students Office, http://www.dso.iastate.edu/ja/academic/misconduct.html.

Disability accommodation

This material can be provided to you in alternative format. Anyone who anticipates difficulties with the content or format of the course due to a physical or learning disability should see me immediately in order to work out a plan. You may also want to contact the Disability Resources (DR) office, located on the main floor of the Student Services Building, Room 1076 or call them at 515-294-7220.

Dead week

For academic programs, the last week of classes is considered to be a normal week in the semester except that in developing their syllabi faculty shall consider the following guidelines:

Harassment and discrimination

Iowa State University strives to maintain our campus as a place of work and study for faculty, staff, and students that is free of all forms of prohibited discrimination and harassment based upon race, ethnicity, sex (including sexual assault), pregnancy, color, religion, national origin, physical or mental disability, age, marital status, sexual orientation, gender identity, genetic information, or status as a U.S. veteran. Any student who has concerns about such behavior should contact his/her instructor, Student Assistance at 515-294-1020, or the Office of Equal Opportunity and Compliance at 515-294-7612.

Religious accommodation

If an academic or work requirement conflicts with your religious practices and/or observances, you may request reasonable accommodations. Your request must be in writing, and your instructor or supervisor will review the request. You or your instructor may also seek assistance from the Dean of Students Office or the Office of Equal Opportunity and Compliance.

Contact information

If you feel that any of your rights as a student have been violated, please email academicissues@iastate.edu.

This syllabus is in the public domain. You may copy and reuse it as you see fit

To the extent possible under law, Gray Calhoun (the author) has waived all copyright and related or neighboring rights to this work.

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