ECON 708: Econometrics III
Syllabus
Course Information
Semester: Fall 2024
Delivery: In Person, Wednesday 06:00 PM - 08:40 PM (Constant Hall, 2134)
Office Hours: Wednesday 03:00 PM - 05:00 PM (or by appointment)
Course Description
The purpose of this course is to discuss some econometric methods used in making causal inference. As an organizing principle, the course will focus on research design and modern econometric methods for evaluating cause and effect. Issues in cross-section and panel data, focus on problems such as endogeneity, heterogeneity, unobserved heterogeneity, treatment effects, etc. Panel data does often have an explicit time component; nonetheless, this class will not deal with time-series econometrics.
One way to think about the course is that it will provide you with a toolbox and working knowledge of cross-sectional and panel data methods for use in empirical research. The course will not go into great depth in regard to any particular applied econometric method, but will instead aim to provide you with enough knowledge about each one to know when, and when not, to use it in your empirical research.
Pre- or corequisites: ECON 706 or equivalent.
Course Delivery
The semester is comprised of fifteen weeks (fourteen after accounting for Thanksgiving break). I have identified seven broad topics I believe to be both important and logical in sequence. Therefore, each topic will be covered over the course of two weeks generally in the following fashion. The first week will include lecture and programming exercises. The second week will consist of a “flipped” classroom, where each student will present twice. First, students will pitch a project idea from their “imagination” exercises. Other students will then give feedback about the research design, etc. Second, each student will give a short (10-15 minute) conference-style presentation of a published (or working) paper that uses the method being studied. Students will have to identify the strengths and weaknesses of the papers they present, and a class discussion will follow.
Limitations
Time limitations impose certain restrictions on what we can accomplish in a one-semester course. For example, we will not cover all of the methods you might need or should know. We also will not cover each method in excruciating detail. Arguably, you could build an entire course (research agenda) around each method.
Textbooks and Other Materials
Required Software
As this course focuses on the learning and application of econometric techniques, a computer or laptop with R and RStudio installed is required. Students can obtain the latest version of R from r-project.org. Students can obtain a free version of R-studio from posit.co. While students can directly code in R, it is recommended that student use RStudio to facilitate interactions with the R language. Students will also install numerous open source packages throughout the course.
Course Learning Objectives
- Categorize settings in which different causal inference strategies may be applied.
- Evaluate the strengths and weakness of different causal inference strategies.
- Apply different causal inference methods to appropriate research settings.
- Interpret estimates generated by causal inference methods.
- Critique claims of causality in analyses using observational data without random assignment.
Course Schedule
Below is a schedule for course topics with corresponding assignments. See Grading Policy for due dates.
\(*\) indicates student-led classes.
Grading Policy
The evaluation for this course consists of the following elements: homework assignments, imagination exercises, and a final project (in addition to checkpoints throughout the semester). The final grade is comprised of the following elements:
Grades will be determined by the sum of points earned, and then converted using this table:
| Letter | Minimum | Maximum |
|---|---|---|
| A | 467 | 500 |
| A- | 450 | 466 |
| B+ | 433 | 449 |
| B | 417 | 432 |
| B- | 400 | 416 |
| C+ | 383 | 399 |
| C | 367 | 382 |
| C- | 350 | 366 |
| D+ | 333 | 349 |
| D | 317 | 332 |
| D- | 300 | 316 |
| F | 0 | 299 |
Except for grades of “Incomplete”, all grades are considered final when reported by a faculty member at the end of a semester. A change in grade may only be requested when a calculation, clerical, administrative, or recording error is discovered in the original assignment of a course grade or when a decision is made by the faculty member to change the course grade because of the disputed academic evaluation procedures.
Grade changes necessitated by a calculation, administrative, or recording error must be reported within a period of six months from the time the grade is awarded. No grade may be changed as the result of a re-evaluation of a student’s work or the submission of supplemental work following the close of a semester.
Homework
The homework assignments will focus on applying each causal inference method covered in the module to a different data set in a different context from the material presented in the text. The final product must be an html document rendered by Quarto in RStudio. It must contain comments describing the code and appropriate variable names. It must generate regression output in table form and contain descriptions of the causal inference methods, data, and full interpretation of the results. Each assignment will come with an associated template.
Note: It is likely that students will have to venture out onto the internet by themselves to find solutions to homework questions.
Imagination Exercises
One of the class learning objectives is “Apply different causal inference methods to appropriate research settings.” There are many ways to apply these methods. One is to imagine how you might apply each method covered in class to a case that is salient to you. These exercises focus on that idea.
The imagination exercises require no data analysis or R coding. These exercises get you thinking about research design, the methods covered in the course, and why they apply to specific situations, using an example that has meaning to you personally. Examples include papers read in other classes that did not use causal inference methods, economic news items of personal interest, questions related to your work, or economic policy issues you find interesting. You must complete the imagination exercises using Quarto in RStudio and submit a rendered HTML document. Students will also need to give an informal presentation of their idea in class.
Final Project
The goal of the final project is to write an empirical paper using the tools covered in this course. The focus of the paper should be on the identification strategy and data analysis. See the Final Project’s page for more information.
It should be noted that, including the checkpoints, the final project is 28% of your final grade. Therefore, it’s important to keep up with the checkpoints and be in communication with me about your project throughout the course.
Your project will be uploaded to, or embedded within, your ePortfolio by the end of the course.
ePortfolio
In an effort to help students reflect on and synthesize their learning experiences, as well as demonstrate their skills to potential employers, certain courses taught by faculty in the Economics department will require the creation of, or addition to, an ePortfolio. Given the status of this course as the capstone of the Economics major, this course will contain an ePortfolio component.
Final projects will be submitted via Canvas and uploaded to each student’s ePortfolio. The extent to which students use their ePortfolio is ultimately up to them, but having their capstone project online and visible should differentiate them from competing job seekers. As a note, all material generated in this course will be portable .html files that can easily be uploaded to ePortfolios.
Online ePortfolio resources for ODU students can be found at odu.edu/asis/eportfolio.
Disclaimer: this course incorporates various online software and other technologies. Some technologies require you to either create an account on an external site or develop assignment content using them. The content, as well as your name/username or other personally identifying information may be publicly available as a result. While the purpose of these assignments is to engage with technology as a means for representing the content we are covering in class, please see me for an alternative activity if you object to potentially sharing your account, name, or other content you create in these technologies.
Incomplete Grades
A grade of “I” indicates assigned work yet to be completed in a given course, or absence from the final examination, and is assigned only upon instructor approval of a student request. The “I” grade may be awarded only in exceptional circumstances beyond the student’s control. The “I” grade becomes an “F” if not removed by the day grades are due for following term based on specific criteria: Incomplete, Withdraws and Z grades.
Course Policies
Communication
Students should feel welcome to contact me via email (acardazz@odu.edu) or drop by my office. I have an ‘open door’ policy for student questions and strongly encourage students to communicate with me. I respond to well-crafted emails within 48 business hours.
Students should take the time to craft complete, professional emails. The more information that you can provide about a question or problem, the more likely that my response will be helpful. Avoid non-professional language and practice communicating in the corporate workplace. Emails that are unprofessional will be returned with no action. There are many guides on how to compose a professional email which you can easily find online.
Attendance and Participation
There is no formal attendance policy for this course, but missing class will make it difficult to succeed. On days where the class is flipped, however, students are required to both present their imagination exercise and a published/working paper using the method we’re studying. If students are absent from class during these days, no points will be awarded for their imagination exercise (unless excused beforehand).
Late Assignments
All due dates are firm. Late submissions of any assignment will receive a score of zero unless discussed at least forty-eight hours prior to the deadline. Special circumstances that are communicated in advanced will be handled on a case by case basis.
Plagiarism
Plagiarism and turning in work that is not yours is grounds for being assigned a zero on an assignment, is a violation of the University Honor Code, and could result in failure in the course and/or academic action by the university.
Artificial Intelligence
The use of artificial intelligence (AI), or other online resources not explicitly authorized, must be done carefully, if at all. You may use AI tools like ChatGPT to help you brainstorm and outline, but never as submitted material (with or without attribution). If I see code that is not presented in the format I use in the class notes, it will be taken to be plagiarism and awarded zero points unless accompanied by very detailed, convincing articulation. In other words, students must provide 1) reasons for why they are choosing to deviate from the code taught in class as well as 2) explanations of the alternate code. I reserve the right to request that students orally explain their code, line by line, and failure to do so will result in zero points for the assignment.
Course Disclaimer
The course schedule and activities are subject to change. Changes will be posted as Announcements in Canvas. All instructional materials and homework assignments can be found here.
University Policies
Code of Student Conduct and Academic Integrity
The Office of Student Conduct & Academic Integrity (OSCAI) oversees the administration of the student conduct system, as outlined in the Code of Student Conduct. Old Dominion University is committed to fostering an environment that is: safe and secure, inclusive, and conducive to academic integrity, student engagement, and student success. The University expects students and student organizations/groups to uphold and abide by standards included in the Code of Student Conduct. These standards are embodied within a set of core values that include personal and academic integrity, fairness, respect, community, and responsibility.
Honor Pledge
By attending Old Dominion University, you have accepted the responsibility to abide by the Honor Pledge:
I pledge to support the Honor System of Old Dominion University. I will refrain from any form of academic dishonesty or deception, such as cheating or plagiarism. I am aware that as a member of the academic community it is my responsibility to turn in all suspected violations of the Honor Code. I will report to a hearing if summoned.
Discrimination Policy
The purpose of this policy is to establish uniform guidelines to promote a work and education environment that is free from harassment and discrimination, as defined below, and to affirm the University’s commitment to foster an environment that emphasizes the dignity and worth of every member of the Old Dominion University community. The Discrimination Policy details the process to address complaints or reports of retaliation, as defined by this policy.
Diversity and Inclusion
The Division of Student Engagement & Enrollment Services values the uniqueness of our Monarch community. The word “engagement” reflects our commitment to embrace the differences in our cultural backgrounds, perceptions, beliefs, traditions, world views, socio-economic status, cognitive and physical abilities.
We will strive to serve as the pre-eminent model for engaging every student to achieve their own success. Our core values are fueled by our responsibility and actions toward community development and engagement, cultural competence and understanding, physical and mental wellness and inclusion for every member of ODU. We will embrace our greatest strength - the diverse composition of our student body and workforce. For more information regarding diversity and inclusion, please visit the Office of Intercultural Relations.
Educational Accessibility and Accommodations
Old Dominion University is committed to ensuring equal access to all qualified students with disabilities in accordance with the Americans with Disabilities Act. The Office of Educational Accessibility (OEA) is the campus office that works with students who have disabilities to provide and/or arrange reasonable accommodations.
The Accommodations for Students with Disabilities define the procedures used to accommodate student with disabilities. Students are encouraged to self-disclose disabilities that the Office of Educational Accessibility has verified by providing Accommodation Letters to their instructors early in the semester in order to start receiving accommodations. Accommodations will not be made until the Accommodation Letters are provided to instructors each semester
University Email Policy
With the increasing reliance and acceptance of electronic communication, email is considered an official means for University communication. Old Dominion University provides each student an email account for the purposes of teaching and learning, research, administration, and service. It is the responsibility of every eligible student to activate MIDAS, the Monarch Identification and Authorization System, to obtain email access. It is important that all students are aware of the expectations associated with email use as outlined in the Student Email Standard. The email account provided by the University is considered to be an official point of contact for correspondence. Students are expected to check their official e-mail account on a frequent and consistent basis in order to stay current with University communications. Mail sent to the ODU email address may include notification of University-related actions, including academic, financial, and disciplinary actions. For more information about student email, please visit Student Computing.
Withdrawal
A syllabus constitutes an agreement between the student and the course instructor about course requirements. Participation in this course indicates your acceptance of its teaching focus, requirements, and policies. Please review the syllabus and the course requirements as soon as possible. If you believe that the nature of this course does not meet your interests, needs or expectations, if you are not prepared for the amount of work involved – or if you anticipate assignment deadlines or abiding by the course policies will constitute an unacceptable hardship for you – you should drop the course by the drop/add deadline, which is listed in the ODU Schedule of Classes. For more information, please visit the Office of the University Registrar.
Privacy of Student Information
Old Dominion University recognizes its duty to uphold the public’s trust and confidence, not only in following laws and regulations, but in following high standards of ethical behavior. Members of the Old Dominion University community are responsible for maintaining the highest ethical standards and principles of integrity. The Code of Ethics is a set of values-based statements that demonstrate the University’s commitment to this goal. The Privacy of Student Information details Family Educational Rights & Privacy Act (FERPA), along with other information regarding privacy.
Other Academic Policies
Please see the following link for other academic policies at the university level: https://catalog.odu.edu/undergraduate/policies/academic-policies/