It’s nearly impossible to overstate the value that economists ascribe to cleverness. Like most obsessions, this one is not altogether healthy.
My general philosophy in life is never to rely on being clever; instead I want to rely on being thorough and having a justifiable workflow.
A theoretical statistician knows all about measure theory but has never seen a measurement whereas the actual use of measure theory by the applied statistician is a set of measure zero.
This is the course website for Core Empirical Research Methods (core ERM), a 1st-year MPhil course in the Economics Department at the University of Oxford. Core ERM will help you develop the basic skills you’ll need to carry out applied economic research. It will cover a mix of applied econometrics, programming/computing, and research skills. The prerequisites are basic familiarity with programming in some language, not necessarily R, and an introductory course in econometrics at the masters level. If you are interested in auditing this course see Auditing Core ERM below.
Because Core ERM is about doing applied economics, it will not be a traditional lecture course. Students should bring their laptops to lectures so that they can follow along with live demos and work on examples in small groups. While there will still be some lecture-style material, the overall format will be closer to a “lab” in the natural sciences. As such attendance is mandatory if you are taking this course for credit. Please see Attendance below for more details. GTAs (Graduate Teaching Assistants) will attend each lecture to help give you individualized help if you get stuck while working through in-class exercises. See Required Software for details on how to configure your machine for core ERM.
Lecturer: Francis J. DiTraglia
Teaching Assistants (GTAs)
We will not use canvas for core ERM. Instead, all course materials will be posted on the course website and all other communication will take place on ed. Please register for the discussion board by following this link. I have enabled self sign-up for all email addresses that end in @ox.ac.uk or @*.ox.ac.uk so either your college or departmental email address should work. Please do not send email messages to your GTAs or the course instructor; we ask that you use the discussion board instead. If you have a post about course content, we kindly request that you post it publicly–you are free to remain anonymous when posting publicly–so that our answer can benefit the other students in the course. Your classmates may also know the answer and be able to help you faster than we can, so there’s both a private and public benefit to this approach. For personal issues or questions specific to your mini-project please can send us a private message on the discussion board. Keeping all course communication in one place will allow us to spend more time helping you learn and less time on course admin.
All class meetings will take place in the Manor Road Building (MRB)
Weeks 1-8 of Trinity Term, MRB Lecture Theatre. Lecture attendance is required if you are taking this course for credit. (See Attendance for details.)
Weeks 2-9 of Trinity Term in MRB Seminar Room D. Attendance is optional but strongly recommended. These sessions are particularly valuable for troubleshooting code problems for problem sets, getting feedback on your mini-project, and deepening your understanding of challenging concepts.
In this course we will use the R programming language via a front-end called RStudio. Both are freely available on all major platforms. To install them follow these instructions. To smooth out the inevitable start-of-term kinks, during weeks 1 and 2 we will work with RStudio via Posit Cloud. Please sign up for a free account here. This will allow you to get right to work at the start of term even if you encounter problems installing R. Eventually you will need to get R and RStudio working on your own machine, however. The week 3 drop-in surgery is an excellent place to get help with installation issues.
Because core ERM is an interactive, lab-based course, lecture attendance is mandatory. It is also in your best interest. A major part of your assessment is based on problem set. We will work through many of these together during lectures, but recordings will not be made available during the term. Because the material in core ERM is highly cumulative–each week builds on the last–regular attendance is the easiest and most reliable way to ensure that you gain the skills you will need to pass the course.
Moreover, while I would prefer to rely on the carrot rather than the stick, I will keep track of attendance at lectures in TT 2025. Students who miss more than five lectures without prior authorization will be contacted by the director of graduate studies and the senior tutor of their college. If you are in the UK on a student visa, it is particularly important that you attend regularly, as the government requires me to certify that you have been actively engaged with your course of study during the term. While it would never be my goal to try to get anyone into trouble, I am legally and ethically bound to report your attendance accurately when it is formally requested of me.
This course is pass/fail and will be assessed entirely on the basis of coursework assignments. Before we go any further: yes it is possible to fail core ERM. See Re-sits for more details. All assignments must be submitted via Inspera. See Inspera Submission Requirements for more details on how to submit. Your coursework assignments come in two parts, each of which will be assessed using the same marking criteria as detailed below. To pass the course, you must pass both parts of the assessment. The two parts are as follows:
Part A will consist of four problem sets due in TT weeks 2, 4, 6, and 8:
Part B will consist of “mini-project” of your choice that you will complete between weeks 3 and 9 of term. Your mini-project will be due at noon on Wednesday of TT Week 9. For full details, see the Mini-Project FAQs below. Because you choose the mini-project, you can work on something that is intrinsically interesting to you. Ideally the topic will be relevant to your MPhil thesis: you can kill two birds with one stone. And because you will complete your mini project during the term, you will have the opportunity to get help and feedback from me and your GTAs at lectures and the weekly drop-in surgeries.
You are allowed, and indeed encouraged, to discuss course problems and assignments with your classmates and GTAs, but you are not allowed to directly copy code or results from another student. The work that you submit for assessment must be your own, even if it incorporates suggestions from your classmates and GTAs.
There are some restrictions on how you are allowed to use large language models (LLMs) in your problem set submissions. In short: you can consult them in the same way that you are free to consult your classmates and GTAs, e.g. as a tool to help you learn R, help debug code, and so on. But you are not allowed to paste in problem set questions and ask for solutions. For example, asking “Can you explain how to filter rows in dplyr?” is acceptable, while asking “How would I solve question 3 from problem set 2?” is not permitted. For the same reason, you are not permitted to use tools that autocomplete code as you type–e.g. GitHub Copilot–when completing problem sets. Generative AI can most likely generate correct solutions to all of my problem set problems, so you may find yourself sorely tempted. There are two reasons why you should not succumb. First, perfectly correct solutions generated by ChatGPT and Claude look sufficiently dissimilar to the examples that I provide in my course materials that it is extremely easy for me to tell that they were AI-generated. Second, if you rely solely on AI, you will never learn to code. And if you never learn to code, you will put yourself out of a job. AI tools substitute for humans with low coding ability; they complement humans with high coding ability.
I insist that you learn to code, but I also insist that you learn to use AI. For this reason, we will help you set up Github Copilot and teach you how to use it. On your mini-project you are free to use generate AI however you see fit: there are no restrictions whatsoever. But please bear in mind that any code you submit must adhere to my Marking Criteria.
Below is the course schedule from TT 2024.
The most important change for this year (TT 2025) is that much of the lecture material will be moved into online videos. The idea is that you will watch the videos at home, work through the short exercises and check your work against the solutions. This will allow us to use class time to work together on the problem set questions, which are more substantive and interesting! Links to videos will be posted as they are recorded.
Problem set questions will be posted here during the term. Please consult the marking criteria and academic integrity policy for more information.
When I first taught this course back in 2022, I started writing a book to accompany it. This turned out to be a tall order, but I did manage to produce ten draft chapters. You can view them at https://empirical-methods.com. Based on my experiences teaching version 1.0 of core ERM, I decided to make a number of changes to the course. While much of the material in my draft book remains relevant, my lecture slides will be the final authority on the course material in the present version of core ERM. I hope to rework the book before next year’s version of core ERM.
Barring a serious personal issue that affects your studies, there is no reason why you should fail core ERM. If you attend class, participate actively, and get help at the drop-in surgeries as needed, you will develop all of the skills needed to complete the course assignments to the appropriate standard. If for some reason you do fail core ERM, you will be given the opportunity to re-sit any failed assignments the next time that core ERM is offered, i.e. in Trinity term of next year. (Remember: you need to pass all four problem sets and your mini-project to pass the course.) Clearly this is something you will want to avoid, so take my advice and do what’s necessary to pass the first time around.
These are the mini-project guidelines from 2024. There may be some slight changes for 2025 but the basic idea remains the same as does the deadline. Check back for an update in TT Week 2.
It is a small project of your own choosing, roughly equivalent to two problem sets in terms of the time required to complete it. You will complete your mini-project between weeks 3 and 9 of term and submit it as part of your course assessment.
Wednesday of TT Week 9 at noon.
Your mini-project should be a replication (or partial replication) of a reputable paper in economics or a closely related field. For an applied paper this would involve obtaining the data for the paper, and writing R code to clean the data and reproduce a few key tables and figures from the paper, e.g. those containing summary statistics and main results. For an econometrics paper it would involve programming an econometric procedure that isn’t already built into R and using your code to replicate all or part of the simulation results from the paper.
There are four key rules for choosing a paper for your mini-project:
Subject to these caveats, you can choose any paper that you like for your mini-project. That said, we strongly suggest considering a paper from one of the two sources listed in the next section.
Not to worry. Here are two excellent resources that you can use to find a paper to replicate:
If you’re stuck you are also welcome to come to the drop-in surgeries to ask your GTAs for suggestions on good papers to replicate.
Before you start working in earnest on your mini-project we will have a short discussion with each of you individually to make sure that your project is neither overly ambitious nor overly simple. If we are happy with your project, we will approve it. If it is not quite right, we will suggest some changes that you can make to get it approved or help you choose an alternative project. While you are working on your project, you can ask for help and feedback from me and your GTAs. You can even say: “here’s what I’ve done, does this look good to you?” and we will be happy to give you feedback. The drop-in surgeries offered by your GTAs are a great opportunity to get help with your mini-project. I may also allocate some time during lectures to provide feedback on the mini-projects.
We will post a sign-up sheet online by the end of week 2 where you will be able to list the paper you want to replicate and check that no other student has chosen the same one. On the sign-up sheet there will also be a place for you to supply a short description of the parts of the paper you intend to replicate. Based on this information, your GTAs and I may be able to approve your project as-is, without the need for a meeting. If not, we’ll ask you to contact us on the course discussion board with a bit more detail about your project. We may also schedule a meeting during the drop-in surgeries to discuss further.
You should submit output generated from RMarkdown/Quarto file, containing your code and output, as well as a short written report that explains what you did and what you found. I will provide further details in lecture.
The same marking criteria will apply to your mini-project as to your problem sets. It will be marked on a pass/fail basis. Remember that you have to pass all course assignments, including the mini-project, to pass the course.
Each student will complete a mini-project based on a different paper: these are individual assignments. The same academic integrity policy applies to mini-projects as to problem set questions. In particular: you are welcome to discuss your work with your GTAs and your classmates but the work that you submit must be your own.
Assignments in Core ERM will be graded pass/fail based on five criteria. Criteria 1–3 are all-or-nothing and necessary to pass a given assignment. Criteria 4 and 5 allow for partial marks.
These will be posted soon.
Between 80 and 90 students take Core ERM for credit each year, but the MRB lecture theatre seats 120. Provided that there’s space left in the room, any member of the university is most welcome to attend my lectures without asking for permission in advance. I ask only that you respect the following guidelines. First, please sit in the back row if you’re auditing so that I can more easily gauge attendance etc. Second, the Drop-In Surgeries are only for students who are taking the course for credit. Third, Core ERM lectures are fairly interactive: I and the GTAs will circulate to help students who encounter difficulties while working on the exercises. I won’t go so far as to say that we won’t help you if you’re auditing, but we will need to prioritize the students who are taking the course for credit.