Syllabus

Course Info

Day Time Location
Lectures Tue, Thu 2:00 pm - 3:15 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: jfhawkin@ucalgary.ca (please include “ENCI 707” in the subject line) or message 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. Formulate basic demand models using packages in either Python or R.
  4. Construct experimental design for use in engineering and planning policy analysis.
  5. Investigate a choice econometrics problem of moderate to high complexity.

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. You are expected to attend all lecture sessions and meaningfully contribute to discussions. 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. Prior to most lectures, you will be asked to review a set of readings and/or videos and complete a short pre-class quiz on D2L; lectures will assume you have completed this preparation.

If for any reason you are unable to attend lecture in-person, please provide notice at least 24 hours prior to lecture and an online option will be made available for the week.

Assessment

The main deliverable for this course is a term paper, which is a culmination of the skills gained throughout the course. I will make myself available on a regular basis to provide input on papers, and I strongly encourage you to take advantage of these opportunities. Additional details for all assessments are provided on the course website. Students will also be required to complete three group assignments.

The final course grade will be calculated as follows:

Category Percentage
Pre-class quizzes 5%
Group assignments 15% (5% x 3)
Paper proposal 5%
Midterm exam 20%
Term paper 55%

The final letter grade will be determined based on the following thresholds:

Letter Grade Final Course Grade
A+ 97 - 100
A 92 - 96.9
A- 88 - 91.9
B+ 83 - 88.9
B 78 - 82.9
B- 73 - 78.9
C+ 68 - 72.9
C 63 - 68.9
C- 58 - 62.9
D 52 - 57.9
F < 51.9

All grades of “C+” or lower are indicative of failure at the graduate level and cannot be counted toward Faculty of Graduate Studies course requirements. Individual programs may require a higher passing grade. Additional information on the grading system is available in the University Calendar under F.1.2 Graduate Studies Grading System.

Group Assignments

Assignments should be completed in groups of 2-3 students. The purpose of these assignments is to apply the skills gained in the course; they should not be time-consuming exercises. Evaluation will be holistic and based on completion rather than correctness.

The assignments are as follows:

  • Assignment 1 (due Sept. 24 at 11:59 PM): Aggregate demand model estimation
  • Assignment 2 (due Oct. 22 at 11:59 PM): Stated preference experimental design
  • Assignment 3 (due Nov. 12 at 11:59 PM): Disaggregate demand model estimation

Pre-class quizzes

Prior to each lecture, you will be asked to review a set of videos or readings. A corresponding quiz must be completed on D2L for completion only.

Paper proposal

Due Sept. 17. The purpose of the project proposal is to help you think about your analysis strategy early and receive feedback. The more effort and detail you demonstrate in the proposal, the more complete feedback you will receive from me.

Term paper

Due Dec. 15. The term paper is a culmination of the skills gained throughout the course.

Midterm exam

The midterm exam will be held in-person on Nov. 05 during the lecture period, in ENF304. This will be a closed book, closed notes, long-answer written exam. During the exam, you may use any hand-held calculator; laptops, tablets, personal digital assistants, cellular phones, or any other electronic devices are not allowed.

Students who miss the midterm exam will be assigned a grade of zero on the exam. If you have a valid reason for missing the midterm, you must contact me within 48 hours of the midterm explaining the reason for the missed assessment and include supporting documentation (see University Calendar, M.1) that best suits your situation. If circumstances prevent you from contacting me within 48 hours (e.g., hospitalization or emergency), please do so as soon as reasonably possible. If approved, the weight of the missed exam will be shifted to the term paper, which will then be worth 75% of the course grade. If not approved, the grade on the exam will remain zero.

Use of AI tools

The use of AI tools is encouraged as part of your workflow in this course. You are expected to use AI critically and responsibly to enhance your work. Assessment will focus on your ability to interpret, evaluate, and build upon AI-generated outputs. You must document how AI was used and demonstrate your understanding of the submitted content.

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:

  1. Complete all the preparation work before class.
  2. 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 term paper, ask. If you hear something on the news that sounds related to what we discussed, ask. If the reading is confusing, ask.
  3. Do the readings.
  4. Contribute to the group assignments.
  5. 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 Calgary 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 the University of Calgary. 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.

Academic Misconduct refers to student behavior which compromises proper assessment of a student’s academic activities and includes cheating; fabrication; falsification; plagiarism; unauthorized assistance; failure to comply with an instructor’s expectations regarding conduct required of students completing academic assessments in their courses; and failure to comply with exam regulations applied by the Registrar. For information on the University of Calgary Student Academic Misconduct Policy and Procedure and the SSE Academic Misconduct Operating Standard, please visit the Schulich policies page. Additional information is available on the Academic Integrity Website.

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.

Students needing an accommodation because of a disability or medical concerns should communicate this need to Student Accessibility Services (SAS) in accordance with the Procedure for Accommodations for Students with Disabilities.

Students needing an accommodation in relation to their coursework or to fulfill requirements for a degree, based on a Protected Ground other than Disability, should communicate this need by submitting the SSE Request for Academic Accommodation Form to the Associate Head (Undergraduate Studies) of the department offering the course, within 10 business days prior to the class, test, exam, or assignment at issue.

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.

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.

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 pre-class quizzes, since these are designed to help you prepare for lecture.

  • The late work policy holds for both group assignments and individual project deliverables (paper proposal and term paper). It does not apply to the midterm exam - see the Midterm exam section above for the missed-assessment policy that applies instead.

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.

Reappraisal (regrade request) policy

For reappraisals of graded term work or academic assessments (including final grades), please refer to the SSE Reappraisal of Graded Term Work and Academic Assessments Policy. Reappraisal requests must be based on an alleged grading error and follow the procedures and deadlines specified in the policy. For graded term work, students must first discuss their concerns with me within 10 business days of receiving or viewing the graded work. Reappraisal outcomes may result in a grade increase, decrease, or no change. Forms are available on the Engineering Student Center D2L site.

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.

As members of an engineering program, students are also expected to begin developing the professional behaviours and ethical judgment expected of engineers. Throughout this course, students should demonstrate integrity, accountability, respect for others, and a commitment to public safety and responsible engineering practice. Students are encouraged to familiarize themselves with the APEGA Ethical Practice guideline.

Use of electronic communication devices in class

The use of laptop and mobile devices in class is acceptable when used in a manner appropriate to the course and classroom activities. Please refrain from accessing websites and resources that may be distracting to you or for other learners during class time. Students are responsible for being aware of the University’s Internet and email use policy.

Expectations for writing

All written assignments (including, to a lesser extent, written exam responses) will be assessed at least partly on writing skills. Writing skills include not only surface correctness (grammar, punctuation, sentence structure, etc.) but also general clarity and organization. Sources used in research papers must be properly documented. If you need help with your writing, you may use the Writing Support at the Chancellor Cuthbertson Student Success Centre. For further information, please refer to the University Calendar, Academic Regulations, E.2: Writing Across the Curriculum.

Guidelines for recording sessions

For more information about recording classes in any learning environment see the Media Recording of Students in Learning Spaces policy.

Students who wish to audio record lectures for personal study purposes need to follow the guidelines outlined in Section E.6 of the University Calendar. Unless the audio recording of lectures is part of a student accessibility requirement, permission must be sought from me to audio record lectures.

I may use media recordings to capture the delivery of a lecture for lecture-capture purposes only; recordings will be posted on D2L and normally deleted at the end of term. Turn off your camera and/or microphone if you do not wish to be recorded. I may also use media recordings as part of the assessment of student learning (e.g. presentations); these recordings are used for assessment purposes only and will be destroyed as specified by Retention Rule 2000.01. Finally, I may use media recordings as a tool for self-assessment of my own teaching practices; although the recording device will be fixed on me, student participation may be inadvertently captured, and these recordings will be destroyed as specified by Retention Rule 90.0011.

Research ethics

Students are advised that any research with human participants - including any interviewing (even with friends and family), opinion polling, or unobtrusive observation - must have the approval of the Conjoint Faculties Research Ethics Board or the Conjoint Health Research Ethics Board. In completing course requirements, students must not undertake any human subjects research without discussing their plans with me first, to determine if ethics approval is required. For further information see Section E.5 Ethics of Human Studies of the University Calendar.

Instructor intellectual property

Course materials created by me (including presentations and posted notes, labs, case studies, assignments and exams) remain my intellectual property. These materials may NOT be reproduced, redistributed or copied without my explicit consent. The posting of course materials to third party websites such as note-sharing sites without permission is prohibited. Sharing of extracts of course materials with other students enrolled in the course at the same time may be allowed under fair dealing.

UCalgary notice of collection

The University of Calgary respects your privacy and is committed to ensuring the privacy of all students, staff, and community members. Your personal information is collected under the authority of section 4(c) of the Protection of Privacy Act (POPA) and is collected, used and disclosed for the purposes outlined in UCalgary’s Notice of Collection, Use and Disclosure of Personal Information, managed in accordance with UCalgary’s Privacy Management Program. Your personal information may be input into automated systems to generate content or make decisions, recommendations, or predictions. Assignments can only be returned to the student and will be accessible only to authorized faculty and staff. Questions can be directed to accessandprivacy@ucalgary.ca.

Sexual and gender-based violence policy

The University recognizes that all members of the University Community should be able to learn, work, teach and live in an environment where they are free from harassment, discrimination, and violence. The University of Calgary’s sexual violence policy guides us in how we respond to incidents of sexual violence, including supports available to those who have experienced or witnessed sexual violence, or those who are alleged to have committed sexual violence. Please see the policy for details.

Additional support and resources

For important information on Wellness and Mental Health Resources, Student Success, the Student Ombuds Office, Student Union (SU) Information, Graduate Students’ Association (GSA) Information, Emergency Evacuation/Assembly Points, and Safewalk, please visit the Registrar’s website.