Syllabus

Time Series Econometrics
W&M ECON 408, Spring 2026
Section 01: TR 12:30-1:50pm
Room: Chancellors 114

Contact Info¶

Professor Throckmorton
E-mail: nat@wm.edu
Office Hours:

• Wednesday, 3:30-5:00pm, Chancellors 433

• Thursday, 3:30-5:00pm, Chancellors 433

• Appointment (please request at least one day in advance)

Summary¶

Time Series Econometrics (ECON 408) is an elective for

• Economics (Major or Minor)

• Computational & Applied Mathematics & Statistics (Major Only)

• Data Science (Minor Only)

This course is an introduction to the econometric analysis of time-series data. It builds on the statistical theory from ECON 307 (or its equivalents), the linear regression model from ECON 308, and linear algebra (to be reviewed as necessary throughout the semester) to examine time series models, forecasting, analysis of nonstationary series, unit root tests, co-integration, and the principles of time-series modeling.

Resources¶

Books¶

I will provide my own slides and notes for the class. The first recommended book is free, and the second is $20. A used copy of the optional book is not that expensive.

Recommended

• Diebold, 2024: F.X. Diebold. Forecasting in Economics, Business, Finance and Beyond. Department of Economics, University of Pennsylvania, 2024. https://www.sas.upenn.edu/~fdiebold/Teaching221/Forecasting.pdf

• Huang & Petukhina, 2022: Huang and Petukhina. Applied time series analysis and forecasting with Python. Springer, 2022. Huang & Petukhina (2022)

Optional

• Hamilton, 1994: James D Hamilton. Time series analysis. Princeton university press, 1994.

Software¶

Required

• Course materials are available at https://nathrock.github.io/time-series/

• We will do examples and assignments in Jupyter notebooks with Python. Here’s how to get started with that: https://nathrock.github.io/jupyter-and-python/.

Recommended

• For everyday note taking, https://obsidian.md/ is a nonlinear note taking app that displays markdown in real time. You can embed screenshots and math written in $\LaTeX$, just as in a Jupyter notebook. You can include code snippets; however, they cannot run like in a Jupyter notebook.

Grades¶

Exams¶

• Exam 1: Thurs, Mar 5

• Exam 2: Thurs, Apr 16

• Exam 3 (Final): Tues, May 12, 9-11am

Please note that anything discussed in class or any topic in the assigned reading from the textbook is “fair game”‘’" for the exams. There may be material presented in class that is not in your textbook, so make sure that you have a full set of notes.

Assignments¶

There are 3 problem sets (one due before each exam) each worth 60 points. There is also a replication exercise worth 70 points, which should take a similar amount of time as a problem set, and it will be due by the end of the semester.

• These assignments must be submitted as a Jupyter Notebook and all data analysis must be done in Python.

• I encourage you to work together, and you may work in groups of 3 people or less.

• I will not assign groups nor will I police them; you may change groups throughout the semester.

The class presentation is worth 50 points where you will overview a research paper that uses time series methods in about 8 minutes.

All assignments must be turned in by the due date and time. Late work will not be graded.

Final Grade¶

There are 1000 total points available in this class. Please note that it is possible to miss the next highest grade by only a few points. This may happen, so be aware of this possibility. If you want to appeal any grading, you must contact me no later than one week from the date I post your score. The following table indicate the minimum number of points needed to guarantee a certain grade.

Important Dates¶

Attendance¶

I expect you to attend all classes and take all exams. If you are unable to attend class or take an exam, please let me know as soon as you can. (You do not need to explain why unless you want to.) If you are unable to attend class, I will send a link shortly before class and you may attend remotely if you are able. I will not record lectures. In some cases, I will upload slides or take pictures of anything I write on the whiteboard. In other cases, you will need to obtain notes from a classmate. If I am unable to attend, I will teach remotely. If I am unable to teach remotely, then class may be canceled. I will schedule a catch up and review day before each exam for flexibility.

Student Accessibility Services¶

William & Mary accommodates students with disabilities in accordance with federal laws and university policy. Any student who feels they may need an accommodation based on the impact of a learning, psychiatric, physical, or chronic health diagnosis should contact Student Accessibility Services staff at 757-221-2512 or at sas@wm.edu to determine if accommodations are warranted and to obtain an official letter of accommodation. For more information, please see www.wm.edu/sas.

Honor Code¶

I expect everyone to follow the Honor Code. Please see your student handbook for details. “As a member of the William and Mary community, I pledge on my honor not to lie, cheat, or steal, either in my academic or personal life. I understand that such acts violate the Honor Code and undermine the community of trust, of which we are all stewards.” Financial and economic crises are precipitated by breeches of trust, so you must understand this is not only very important to me but also to our entire society. I will not hesitate to punish violators of the Honor Code.

Artificial Intelligence¶

GenAI tools can be used in this course, but only for specific tasks and with the instructor’s permission. Generally, you may utilize GenAI as an editor, translator, idea generator, data visualization tool, or tutor. For instance, GenAI might be permitted for brainstorming, troubleshooting, or editing, but not for drafting entire solutions or answers to questions on assignments.

On problem sets, I expect that you will analytical exercises without the assistance of GenAI unless otherwise specified in the assignment. Analytical questions on problem sets are intended as practice for the exams, where GenAI is not available. If you were to use GenAI on the problem sets, then you would be underprepared for the exams.

On data questions, GenAI (e.g., ChatGPT and GitHub Copilot) is a useful assistant for troubleshooting errors in programs or getting started on a program in an unfamiliar language. It is OK to use GenAI for those purposes. It is also OK to use GenAI to brainstorm ideas on how to interpret the output (e.g., numbers and figures) of a program. However, you should not use GenAI to write your entire program or write entire summaries and interpretations of your program’s outputs.

Mental and Physical Well-Being¶

I recognize that students juggle different responsibilities and can face challenges that make learning difficult. There are many resources available at W&M to help you navigate emotional/psychological, physical/medical, material/accessibility concerns, including

• The W&M Counseling Center, 757-221-3620 (services are free and confidential)

• The W&M Health Center, 757-221-4386

• To seek assistance for interpersonal, academic, and wellness challenges, please contact Care Support Services at wm.edu/care (care@wm.edu).

• For additional resources, visit https://www.wm.edu/offices/wellness/resources/.

Guidelines for Religious Accommodations¶

https://www.wm.edu/offices/ce/policies/audit-risk-and-compliance/religious-accommodations.php

Inclusive Academic Community¶

William & Mary is a community that fosters free expression of ideas. We work to create an educational environment that draws on diverse backgrounds and perspectives. Creating this kind of learning environment requires deliberation, and is a responsibility shared by faculty and students alike. One of our responsibilities is a shared commitment to treat all participants in this course with respect. Our conversations may at times be challenging and difficult: we are here to learn, and learning is not always comfortable. I welcome your authentic feedback as we engage with the ideas represented here. If you have any concerns or questions, please feel free to approach me; or if you prefer, you can report concerns at https://www.wm.edu/report/student/.