Syllabus
Course Info
| Day | Time | Location | |
|---|---|---|---|
| Lectures | Wed | 2:00 pm - 4:45 pm | ENF 304 |
| Office hours | Mon | 2:00 pm - 4:00 pm | ENF284 |
Prerequisites: A basic knowledge of statistics and coding in either R or Python.
Description: ENCI 707 is graduate-level course covering the estimation and application of econometric models. This course deals with the quantitative analysis and modeling of demand for civil engineering planning and policy analysis. Students will gain an understanding of the theories and models of demand based on basic microeconomic concepts of consumer behaviour. The theory covered in this course is applicable to transportation demand, environmental resource valuation, and any other consumer behaviour context. An overview will be given of data challenges and methods of survey design. The course will focus on two main topic areas: (1) econometric model theory and estimation and (2) experimental design for policy analysis.
Credit Hours: 3
Instructor:
Dr. Jason Hawkins
ENF284
Email me through the course D2L messenger system
Learning objectives
Students will be able to: 1. Explain the economic theory underlying disaggregate demand models. 2. Analyze the validity and limitations of survey and other datasets for use in engineering and planning demand and policy analysis. 3. Perform basic demand model estimation using packages in either Python or R. 4. Construct causal experiments for use in engineering and planning policy analysis. 5. Value diverse perspectives on the valuation of engineering policy outcomes.
Required Materials
No textbook is required for this course. Students will require access to a computer capable of running Python or R.
Available Resources
While there is no official textbook for the course, there are many excellent references (I have a physical or digital copy of most of these books and can loan them to students for the term). These sources provide different levels of detail and use various mathematical notation. I leave it up to each of you which resource best suits you.
Discrete choice modeling
- “Discrete Choice Methods with Simulation” by Train (pdf freely available at https://eml.berkeley.edu/books/choice2.html) provides a good coverage of discrete choice methods.
- “Discrete Choice Analysis” by Ben-Akiva and Lerman provides a technical and in-depth treatment of fundamental discrete choice theory.
- “A Self Instructing Course in Mode Choice Modeling: Multinomial and Nested Logit Models” (pdf freely available at https://www.caee.utexas.edu/prof/bhat/COURSES/LM_Draft_060131Final-060630.pdf) by Koppelman and Bhat provides a good overview of discrete choice models for the practitioner.
- “Modelling Transport” by Ortuzar and Willumsen covers discrete choice models in chapters 7-9. It also gives a good overview of activity-based models and other features of transportation planning.
- Some chapters of “Statistical and Econometric Methods for Transportation Data Analysis” by Washington, Karlaftis, Mannering, an Anastasopoulos.
- “Applied Choice Analysis: A Primer” by Hensher, Rose, and Greene.
Statistics
- Some chapters of “Statistical and Econometric Methods for Transportation Data Analysis” by Washington, Karlaftis, Mannering, an Anastasopoulos.
- “Econometric Analysis” by Greene gives a technical treatment of statistics and econometrics.
- “Regression and Other Stories” by Gelman, Hill, and Vehtari covers statistics and causal inference.
- “Geographic Data Science” by Rey, Arribas-Bel, and Wolf covers geographic data science and spatial econometrics - https://geographicdata.science/book/intro.html
Survey methods
- “Sampling: Design and Analysis” by Lohr is a classic textbook on this topic.
Course Website
I find course management software inflexible and painful tools. As such, aside from announcements and assignment submissions, all course content will be made available on my research website: https://hawkins-tech-lab.github.io/teaching/ENCI707/
Lectures
The goal of lectures is for them to be as interactive as possible. My role as instructor is to introduce you to new theories, tools, and techniques, but it is up to you to take them and make use of them. Some of what you do in this course will involve writing code, and coding is a skill that is best learned by doing. Therefore, as much as possible, you will be working on a variety of tasks and activities during lecture. You are expected to attend all lecture sessions and meaningfully contribute to in-class exercises and discussions. Additionally, some lectures will feature application exercises that will be graded.
You are expected to bring a laptop to each class so that you can take part in the in-class exercises. Please make sure your laptop is fully charged before you come to class as the number of outlets in the classroom will not be sufficient to accommodate everyone.
Assessment
The main deliverables for this class comprise a set of assignments designed to walk students through the process of setting up a demand or policy analysis study. Students will not carry out their study to completion. Additional details are provided on the course website for each component. Students will also be required to complete three short group assignments.
The final course grade will be calculated as follows:
| Category | Percentage |
|---|---|
| Application exercises | 10% |
| Group assignments | 15% (5% x 3) |
| Project proposal | 15% |
| Project literature review | 15% |
| Draft project data and experimental design plan | 15% |
| Final project data and experimental design plan | 30% |
The final letter grade will be determined based on the following thresholds:
| Letter Grade | Final Course Grade |
|---|---|
| A+ | >= 97 |
| A | 93 - 96.99 |
| A- | 90 - 92.99 |
| B+ | 87 - 89.99 |
| B | 83 - 86.99 |
| B- | 80 - 82.99 |
| C+ | 77 - 79.99 |
| C | 73 - 76.99 |
| C- | 70 - 72.99 |
| D+ | 67 - 69.99 |
| D | 63 - 66.99 |
| D- | 60 - 62.99 |
| F | < 60 |
Group Assignments
You will be assigned to groups at the beginning of the semester to complete several assignments. All group members are expected to contribute equally to the completion of the assignments and you will be asked to evaluate your group members throughout the semester. Failure to adequately contribute to an assignment will result in a penalty to your mark relative to the team’s overall mark. However, equal contribution does not necessarily mean that all group members must complete the same tasks. Please feel free to distribute work based on interests and experience. However, you are also encouraged to challenge yourselves to learn new tasks and support each other in this learning.
Application exercises
Parts of some lectures will be dedicated to working on Application Exercises (AEs). These exercises which give you an opportunity to practice applying the transportation planning concepts and code introduced in the readings and lectures. These AEs are due by midnight on the day of the corresponding lecture period. These exercises are marked as complete/incomplete.
Pre-lecture content
Prior to most lectures, you will be asked to complete a set of readings and/or videos. Reviewing these resources will help you come prepared to lecture.
Exams
There is no final exam for this course.
Five tips for success
Your success in this course depends very much on you and the effort you put into it. The course has been organized so that the burden of learning is on you. I will help you by providing you with materials and answering questions and setting a pace, but for this to work you must do the following:
- Complete all the preparation work before class.
- Ask questions. As often as you can. In class, out of class. Ask me, ask your friends, ask the person sitting next to you. This will help you more than anything else. If you get a question wrong on an assessment, ask me why. If you’re not sure about the assignments or project, ask. If you hear something on the news that sounds related to what we discussed, ask. If the reading is confusing, ask.
- Do the readings.
- Contribute to the group assignments.
- Don’t procrastinate. If something is confusing to you in Week 2, Week 3 will become more confusing, Week 4 even worse, and eventually you won’t know where to begin asking questions. Don’t let the week end with unanswered questions. But if you find yourself falling behind and not knowing where to begin asking, come to office hours, and let me help you identify a good (re)starting point.
Diversity and Inclusion
It is my intent that students from all diverse backgrounds and perspectives be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength and benefit. I would like to create a learning environment for my students that supports thoughts, perspectives, and experiences, and honors your identities (including gender, sexuality, disability, age, socioeconomic status, ethnicity, race, nationality, religion, culture, etc.). To help accomplish this: - If you have a name and/or set of pronouns that differ from those that appear in your official University of Nebraska records, please let me know! - If you feel like your performance in the class is being impacted by your experiences outside of class, please don’t hesitate to come and talk with me. I want to be a resource for you. Remember that you can also submit anonymous feedback (which will lead to me making a general announcement to the class, if necessary to address your concerns). If you prefer to speak with someone outside of the course, there are many resources available on-campus (e.g. CAPS). - I (like many people) am still in the process of learning about diverse perspectives and identities. If something was said in class (by anyone) that made you feel uncomfortable, please talk to me about it. (Again, anonymous feedback is always an option). Your suggestions are encouraged and appreciated.
Land Acknowledgement
The University of Calgary, located in the heart of Southern Alberta, both acknowledges and pays tribute to the traditional territories of the peoples of Treaty 7, which include the Blackfoot Confederacy (comprised of the Siksika, the Piikani, and the Kainai First Nations), the Tsuut’ina First Nation, and the Stoney Nakoda (including Chiniki, Bearspaw, and Goodstoney First Nations). The City of Calgary is also home to the Métis Nation of Alberta (Districts 5 and 6).
Course Policies
TL;DR: Don’t cheat!
Academic honesty policy
Academic integrity is of the utmost importance at Nebraska. Be sure you understand expectations of you and your academic work. For more information, please visit https://www.ucalgary.ca/legal-services/university-policies-procedures/student-academic-misconduct-policy. If you are unsure what counts as academic dishonesty in this course, please visit me to. The first instance of academic dishonesty will result in a score of zero for the assignment. The second incidence of academic dishonesty will result in a failing grade for the course.
Accommodations for students with disabilities policy
It is my goal that this class be an accessible and welcoming experience for all students. Reasonable accommodations are provided for students who are registered with Student Accessibility Services make their requests sufficiently in advance. For more information, contact Student Accessibility Services
Resource for students seeking mental health help
The University offers a variety of options to students to aid them in dealing with stress and adversity. There is a multidisciplinary team of experts that works collaboratively with Calgary students to help them explore their feelings and thoughts and learn helpful ways to improve their mental, psychological and emotional well-being when issues arise. More details are available from Mental Health Services.
Communication
All lecture notes, assignment instructions, an up-to-date schedule, and other course materials may be found on the course website (https://unl-hawkins-lab.github.io/Hawkinslab/teaching/ENCI707/ENCI707.html).
I will regularly send course announcements via email and D2L - make sure to check one or the other of these regularly. If an announcement is sent Monday through Thursday, I will assume that you have read the announcement by the next day. If an announcement is sent on a Friday or over the weekend, I will assume that you have read it by Monday.
Where to get help
- If you have a question during lecture, feel free to ask it! There are likely other students with the same question, so by asking you will create a learning opportunity for everyone.
- I am here to help you be successful in the course. You are encouraged to attend office hours to ask questions about the course content and assignments. Many questions are most effectively answered as you discuss them with others, so office hours are a valuable resource. Please use them!
- Emails should be reserved for questions not appropriate for the public forum. If you email me, please include “ENCI 707” in the subject line. Barring extenuating circumstances, I will respond to ENCI 707 emails within 48 hours Monday - Friday. Response time may be slower for emails sent Friday evening - Sunday.
Policy on sharing and reusing code
I am well aware that a huge volume of code is available on the web to solve any number of problems. Unless I explicitly tell you not to use something, the course’s policy is that you may make use of any online resources (e.g. StackOverflow, ChatGPT) but you must explicitly cite where you obtained any code you directly use (or use as inspiration). Any recycled code that is discovered and is not explicitly cited will be treated as plagiarism.
Late work policy
The due dates for assignments are there to help you keep up with the course material and to ensure I can provide feedback within a timely manner. I understand that things come up periodically that could make it difficult to submit an assignment by the deadline.
Assignments may be submitted up to 3 days late. There will be a 5% deduction for each 24-hour period the assignment is late.
There is no late work accepted for application exercises, since these are designed to help you prepare for assignments.
The late work policy holds for both group assignments and individual project deliverables.
Waiver for extenuating circumstances
If there are circumstances that prevent you from completing a homework assignment by the stated due date, you may email Dr. Jason Hawkins before the deadline to waive the late penalty. In your email, you only need to request the waiver; you do not need to provide explanation. This waiver may only be used once in the semester, so only use it for a truly extenuating circumstance.
Regrade request policy
Regrade requests must be submitted by D2L within a week of when an assignment is returned. Regrade requests will be considered if there was an error in the grade calculation or if you feel a correct answer was mistakenly marked as incorrect. Requests to dispute the number of points deducted for an incorrect response will not be considered. Note that by submitting a regrade request, the entire question will be graded which could potentially result in losing points.
No grades will be changed after the final project deadline.
Attendance policy
Responsibility for class attendance rests with individual students. Since regular and punctual class attendance is expected, students must accept the consequences of failure to attend.
However, there may be many reasons why you cannot be in class on a given day. If you miss a lecture, make sure to communicate with your project team about how you can make up your contribution. Given the technologies we use in the course, this is straightforward to do asynchronously. Overall these policies are put in place to ensure communication between team members, respect for each others’ time, and also to give you a safety net in the case of illness or other reasons that keep you away from attending class.
Inclement weather policy
In the event of inclement weather or other connectivity-related events that prohibit class attendance, I will notify you how we will make up missed course content and work. This might entail holding the class on Zoom synchronously or watching a recording of the class.
Cell phone use and professional behaviour
When you come to class, your cell phone must be turned off or silenced and put away where it is not a distraction to you or anyone else. The instructor’s expectations for classroom behaviour are based on the norms of the engineering profession. Questions and discussion related to class material are welcome and encouraged but respect for the instructor and fellow classmates is required at all times.