Cross Section Econometrics Syllabus [ECON 407]

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Fall 2020

Instructor: Rob Hicks
E-mail: [note, this differs from the email address posted on my website]
Class Time: TR 3:30-4:50pm [this is only relevant for when our final exam is scheduled]

Covid19 Considerations

Due to family health issues, I am unable to offer this class in person. This class is being taught as "Remote Asynchronous". This means, I will be recording lectures per lecture day where you can watch them on your schedule. Office hours (and a first day "live" zoom session) will occur over video conference at appointed times.

Course Summary

In this course we will explore econometric techniques for testing microeconomic theories at the individual or firm level. With the advent of computers and associated data on economic behavior, the past few decades has seen an explosion of applied economic research using a wide range of techniques for this type of data- termed cross section data and cross section econometrics. In this course, you will learn about these techniques, will learn to be an educated consumer of econometric research, and will apply these techniques to real data. We will also derive many of the properties of the statistical techniques used in this course, but primarily at the end of the course you will

  • Understand the strengths and weaknesses of cross section techniques
  • Know how to test the validity of modeling assumptions
  • Know the proper econometric technique for a wide variety of Cross-Section settings

Important Dates

Item Date
First day of class August 20
Last day to add/drop August 28
Mid-Term 1 September 101
Last day to withdraw October 12
Fall Break No Fall Break this Semester
Mid-Term 2 October 15
Thanksgiving No Applicable this Semester
Last day of this class November 12
Final Exam November 20 (2:00 - 5:00pm)


  • Asking Questions: Substantive questions about course material or coding in Stata must be submitted to the Cross Section issue tracker at Before using the issue tracker, you must create an account on gitlab (free). Use your William and Mary email address so that I can add you to the user list. Part of Problem Set 1 requires you to file an issue at this site, so create your account ASAP once you receive an invite from me. Do not post proofs or code on the gitlab site that effectively answers an exam or problem set question. Use email for these types of questions.
  • Email Policy : For other types of questions like setting up meetings, grade questions, logistical issues, etc., I will respond to emails but only if they contain the tag [ECON407] in the subject line or you use the email exactly as specified above. If not, the google will likely delete your email. Substantive questions about course material/coding should be posted to gitlab unless you feel that the code or information you provide in the issue tracker will answer the question.
  • Grades: Your grade will be based on five exercises (1 @ 2% and 4 @ 7% each), mid-terms (2 @ 22% each), a final exam (26%).
    • The problem sets will consist of a mix of theoretical and practical econometrics and should be considered serious time-consuming undertakings. In each (after the first one), you will be given a dataset and will need to conduct an econometric analysis thinking critically about which technique to employ as well as key tests that should be run. Your document should include clear interpretations of your results, tables with clear variable names, and be well-formatted with code, tables, and writeup combined in a convenient (for me) way. You will be responsible for posting to the blackboard assignment a markstat file that completely generates your analysis: a flowing narrative containing code, writeup, and results. For any part of the problem sets requiring hand-written math excercises, you can turn those in with your pdf but the response must be clearly marked for the question and must be in proper order. Early on in class, I will demo how this works for stata. The handout for reproducible research can be found here and is produced by this stata source code in stata using markstat. Also, a markstat demo is provided for showing the workflow that I demonstrated in class. Note the special considerations for Mac users at the end of the video.
    • Grades will be awarded based on standard grading scales after a curve is applied (if necessary):

      Letter grade Percentage of points after curve
      A 93–100%
      A− 90–92%
      B+ 87–89%
      B 83–86%
      B− 80–82%
      C+ 77–79%
      C 73–76%
      C- 70–72%
      D+ 67–69%
      D 63–66%
      D- 60–62%
      F 0–59%

      For a typical class year, the points required for an "A" in the course before the curve is applied is approximately 84-85% of the total available points.

  • The mid-terms are scheduled for September 10 and October 15. Unfortunately these times are fixed and can't be rescheduled. Furthermore, by university policy I am unable to change the final exam time. If these exam times don't work for you please drop the course.

Policy on Late Assignments

  • Final Exam: University policy will not allow me to reschedule the final exam (see the Dean of Students for exceptions).
  • Course assignments must be turned in on time. Late work will be accepted for up to two additional days (with Saturday and Sunday counting as 1 day in total) with a letter grade deduction for each late day. After two days, late assignments will not be accepted. See below for some examples:

    Due Date Turned in Your Grade Your Grade after Penalty
    Tuesday Thursday A C
    Thursday Saturday or Sunday A C
    Tuesday Friday A F (not accepted)
    Thursday Monday A F (not accepted)

Turning in your work

No hardcopies of any assignments will be accepted this semester. Items slipped under my door or placed in my mailbox will not be retrieved or graded and will not count towards successful and timely completion of course assignments. All assignments must be submitted via the appropriate assignment in blackboard by the time stipulated in the blackboard assignment item.

Problem sets require

  1. The markstat (stmd) file that produces your dynamic document. If this file fails to accurately produce the pdf of your dynamic document, there will be an automatic two letter grade reduction. A stata do file is not required and won't be graded.
  2. A pdf of your dynamic document. Word documents won't be graded.
  3. Additional materials such as handwritten equations for written work can be inserted in your pdf but it is imperative they are inserted in order and clearly labeled for matching to the question you are trying to answer

Exams require

  1. A pdf of your completed exam (LEGIBLE handwritten responses are expected) with responses in the provided spaces (so print the exam pdf from blackboard assignments and by hand complete it). Word or other types of documents won't be graded. Only a scanned pdf's of your responses will be accepted.
  2. Supplementary or additional responses can be provided in the space provided in the exam, or additional pages can be added to the end of your pdf if necessary. These supplementary materials must be included as part of your pdf and not as an additional document. If more than 1 pdf is submitted, I will only look at the first one.

Grade Discrepancies and Grade Questions

I am happy to discuss questions you have about your grade on class assignments. Any questions you have regarding a potential grade change on an assignment must be cleared up within 1 week of receiving your work back from me. The only exception to this policy is if I made an arithmetic or data entry error in adding your score up and entering it into blackboard. I will not entertain grade questions at the beginning of or following a class. These need to be handled in my office.

Course Materials

All course materials are available on my website for this course at the links listed below. I will only be using blackboard for posting grades and problem set solutions.

Syllabus (this document)
Lecture Notes
Presentations, Handwritten Notes at the Course Google Drive Site
Data Found at


I am no longer requiring any books for this class. However, there are two I highly recommend particularly if you plan on attending graduate school in Economics or Political Science. First is Greene's Econometric Analysis. Second is this one by Wooldridge which is recommended but not required. Both of these books are expensive and you can find older editions at less than half the price. For your convenience, beside each topic is the relevant parts of Greene and Wooldridge although these readings are not required.

The order of topics in the reading list below does not necessarily reflect the order topics will be covered in class.

Topic Summary & Notes Book
Introduction Linear Algebra Intro/ Review Green Appendix
  Stata Intro/Review Supplemental Notes
  Review of Regression Greene 3,4
  Review of Endogeneity Green 12,13.5,13.5.5
Panel Data Fixed Effects Green 9-9.7
  Random Effects Wooldridge 10
Maximum Likelihood Intro to Maximum Likelihood Green 16
Discrete Dependent Variables Binomial Logit and Probit Green 23
Truncation & Censoring Tobit and Heckman Green 24
Simulation and Bootstrap Simulating standard errors TBA
Other Maximum Likelihood Multinomial Logit and Probit  
models (as time allows) Negative Binomial and Poisson Green 25

Computing, Computers, and the Class

We will make extensive use of Stata. You may want to buy your own copy of the software (through the Grad Plan at and the cost is around $100. Alternatively, a College-owned version can be run remotely on a Unix machine ( from your laptop through X11 or other means. If you decide to go this route, know that the setup is time consuming and you will likely need assistance from IT. If you plan on using, please deal with these logistics during the first week of class. Additionally, there are computer labs around campus (e.g. Morton 240) where stata is accessible.

We will make some use of the main computer in the classroom for much of what we do together in class. The data for course examples and problem sets will be available on the web for the duration of the course, but you should have archival copies and working backups of all of the programs you have written to take the data from raw to final form. All computer work you do in this class must self-generate the full analysis and write-up using markstat as described on the first day of class.

Acceptable Collaboration and Automatic Plagiarism Scanning

Finally, I want to define acceptable collaboration. In this course, I want you to think for yourself in applying these techniques. Using resources outside of class and properly citing it, is perfectly with-in bounds. Taking .do or .stmd files from your fellow classmates or off of the web and treating them as your own work is not acceptable. Receiving assistance at every critical modeling step is also not acceptable. Asking a classmate about clarification of stata syntax (e.g.- I forgot how to ask for robust standard errors, could you help me with that?), is fine.

Be aware that all assignments submitted to blackboard are automatically scanned by Turnitin and are compared against the assignments for all current and past Cross Section classes as well against information from the web.



Corrections: this video incorrectly describes Midterm 1 as being on September 12 (a Saturday). It is on the September 10th (a Thursday) as shown in the most recent version of the syllabus.


Most students will be using markstat rather than jupyter and therefore do not need to watch the jupyter demo video. Only those very comfortable with python, have a working anaconda or miniconda environment, and have a working latex install should attempt the jupyter method of producing dynamic documents.