Economics 120B
Econometrics, Winter 2025
Description: This course prepares students for empirical analysis in an academic or business setting. It covers the fundamentals of regression, including estimation and hypothesis testing in a univariate and multivariate framework. It presents ideas using the “potential outcomes” framework and makes the important distinction between prediction and causality. The course discusses reasons why estimators may be biased or inconsistent, and how both randomized experiments and natural experiments can be used to obtain causal estimates.
The material can be difficult and the workload substantial, particularly for those who find math courses challenging. However, your payoff for all this work is a set of skills, analytical tools, and ways of thinking about data that are extremely useful and in high demand in the marketplace.
Important Dates and Times:
Class: Tuesdays and Thursdays, 9:30 – 10:50 am (location: MOS 0113)
Midterm: Tuesday, February 11 in class
Final: Saturday, March 15, 3:00 – 6:00 pm
Class: Tuesdays and Thursdays, 11:00 – 12:20 pm (location: PODEM 1A20)
Midterm: Tuesday, February 11 in class
Final: Saturday, March 15, 3:00 – 6:00 pm
Class will be held in person and attendance is strongly encouraged. Class lectures will not be recorded; if you miss a class, the best option is to find a classmate who can share notes and fill you in on what you missed and/or to visit a TA during office hours for extra help. We will also have some in-class “bonus” quizzes which can only be completed by attending class.
Instructor: Gordon Dahl
Office hours: Tuesdays, 12:30 – 1:30 pm
Location: Atkinson Hall 6320 email: eco120b@gmail.com
(please do not use the email built into canvas, as I do not monitor it)
Feel free to stop by in person so that I can get to know you. As these are large classes, I will prioritize speaking with students about things which the TAs cannot help with, such as strategies to do better in the course, unusual circumstances, graduate school options, etc. In other words, while I am happy to talk about homework, if there are any students needing to talk about other things, then they will jump to the front of the queue.
Graduate Teaching Assistants: Maddison Erbabian, Kurtis Gilliat, Alec Hoover, Haoyu Wei Undergraduate Instructional Assistants: Varun Naik, Ryan Zhao
The graduate TAs are a valuable resource, and I encourage you to take advantage of their help during their office hours. This is an excellent resource for help in understanding course content, homework assignments, and the Stata programming package. If you have a general question about the class, rather than a specific question about content, homework, or Stata (which you should ask about during TA office hours), please use the class email eco120b@gmail.com. A graduate TA will monitor this email, and forward anything which they cannot answer to me.
Please do not use the email built into canvas, as it will not be monitored.
The undergraduate assistants are also a great resource. They will also be holding office hours and I encourage you to take advantage of their help. They have recently taken the class, and so have a first-hand perspective about the types of questions you might have and are well-prepared to answer homework and class questions.
Details on the office hours of the TAs and UIAs will be announced in Canvas. The current plan is to have at least some, and perhaps all, office hours via zoom. TA and UIA office hours will start on week two of the quarter unless otherwise noted.
Review Sessions: There will be review sessions each week which will be conducted by a graduate TA.
The weekly review sessions will normally focus on helping students get started on the homework, but will also occasionally review topics covered in class and help prepare for exams. You are welcome to attend any of the review sessions, regardless of which one you are registered for. Further details on review sessions will be provided during the first week of class and announced on Canvas.
Class Web Site: canvas.ucsd.edu
The class web site contains the syllabus, lecture notes, homework assignments, and class announcements. You should check it regularly as you are responsible for any information posted there in addition to any announcements made in class.
Text and Online Videos: For this course we will be using both a textbook and online videos. The two
are not always substitutes for each other. For some class topics the videos are the better resource, while for others the textbook is better. I will make sure to point students to the most appropriate resource during class lectures.
Text: The textbook is the Pearson eBook Introduction to Econometrics, 4th Edition by Stock and
Watson. The eBook access for the course is being delivered through Follett’s BryteWave RedShelf as a link on Canvas.
The UCSD Bookstore has not provided information this year on specific details on how to opt out of purchasing this ebook. If you have any questions about billing, etc., you can try contacting
textbooks@ucsd.edu.
EVH Videos: We will also be using the Econometrics Video Handbook (EVH), a series of videos developed and maintained by by Professors Brendan Beare, Eli Berman, Graham Elliot, Gordon Dahl, Yixiao Sun, Kaspar Wuthrich, Joel Watson, and Melissa Famulari of the University of
California San Diego, in conjunction with IT Services Educational Technology at UC San Diego
and funded by an Innovative Learning Technology Initiative grant from the Office of the President of the University of California (Melissa Famulari and Joel Watson, Co-Principal Investigators).
You can access the EVH as a module on the class web page. There is no charge to access these videos as part of this course. Some of these videos are useful to review concepts you learned in ECON 120A, and some are useful for the material in ECON 120B.
Software: Part of the course involves learning to use a software package called Stata. Stata is essential for problem sets, so you need to be able to access Stata.
UCSD maintains a site license so that students can download and install Stata on their own computer for free. We will provide details on how to do this as a separate announcement on Canvas as soon as possible.
You can also lease a copy of Stata to install on your own computer for a small fee (but there is no particular reason to do this since UCSD has a free site license):
https://www.stata.com/order/new/edu/profplus/student-pricing/
If you would like a book to help you learn Stata, a good suggestion is A Gentle Introduction to
Stata, Revised Sixth Edition, by Acock. However, this book is not required for the course. There are also many online sites devoted to helping individuals learn Stata. For a list, see:
https://www.stata.com/links/resources-for-learning-stata/
Homework: Homework is an integral part of this course, because the best way to learn econometrics is to do it. I will periodically assign problem sets throughout the quarter. These assignments will be posted on the web, and it is your responsibility to check the class web page regularly.
Homework assignments will generally be due about 6 days later.
Your homework needs to be turned in on Canvas before midnight (i.e., by 11:59 pm) on the due date. Neither late nor emailed homework will not be accepted. You must scan your answers into a single pdf file and upload the file to Canvas.
You are allowed to miss one homework without penalty, as I will drop the lowest score before calculating the homework portion of your grade. The tradeoff for this benefit is that I will be strict about not accepting late homework.
Homework will be graded on a two-point scale. A score of 1 will be given to homework which has made substantial progress, but is incomplete. A score of 2 will be given to homework which attempts to answer all of the assigned problems, including any Stata questions.
Students can work together on problem sets, although solutions must be written up and handed in separately (including any Stata output, which should part of the pdf file you upload onto Canvas when turning in your homework). It is a good idea to attempt the problems on your own before meeting with a group. While you can collaborate with others, any homework you turn in must represent your own work.
Solution keys to the homework will be posted on the class web page. It is a good idea to check your answers versus the solution key so that you can figure out which questions you need to understand better.
Tests: There will be a midterm and a final exam. You must take both the midterm and the final exam at the scheduled time for the class you are registered for (see dates and times listed earlier in the syllabus). There will be no make-up exams, and any conflicts or emergencies should be approved by me in advance of the exams. In case of illness or accident at the time of the midterm – with proper documentation from, for example, a doctor – the final will be weighted 90%. Details on the administration of the exams will be discussed in class.
Bonus Quizzes: There will be between 5 to 7 “bonus” quizzes spread throughout the quarter. The dates of these quizzes will not be announced in advance. These are short quizzes, where you will get full credit for taking the quiz, even if you do not get the answer correct. You will need to bring your phone to class to complete the quiz, and you must be physically present in the class you are registered for to take the quiz. There are no make-up bonus quizzes. The way these bonus quizzes work is that for every bonus quiz you complete, your final exam will count for 1% less, and instead you will get a full 1% towards your course grade.
Grades: The following weights will be used to determine your course grade: Homework: 15%
Midterm exam: 40%
Final exam: 38 to 45% (depending on how many bonus quizzes are completed) Bonus quizzes: 0 to 7% (depending on how many bonus quizzes are completed)
Grading Policy: If you think a mistake was made in grading your exam, you may ask for a regrade. You should submit your regrade request via Canvas within 7 days after exam scores are posted. Note that unless your answer is fully correct, the assignment of partial credit is a matter of judgment, and we are unlikely to change your grade since we want to treat all class members fairly. From past experience, most regrade requests do not result in a grade change.