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 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. 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
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.
Weeks 2-9 of Trinity Term in MRB Seminar Room D. (For the North Americans among us, these are GTA office hours.)
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 week 1 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 2 drop-in surgery is an excellent place to get help with installation issues.
This course is pass/fail and will be assessed entirely on the basis of a single coursework assignment: there is no exam. Before we go any further: yes it is possible to fail core ERM. See Re-sits for more details. Your final assignment will be released in Week 8 and will be due at noon on Wednesday, June 19th, 2024 (TT Week 9) and must submitted via Inspera. See Inspera Submission Requirements for more details on how to submit. The assignment will consist of two parts. These will be equally-weighted and assessed according to the same marking criteria as detailed below. The two parts are as follows:
Part A will consist of three questions drawn from your weekly problem sets, half as many as last year. The logistics for Part A will be identical to last year: the questions will be announced in Week 8 and will be due in Week 9.
Part B will consist of “mini-project” of your choice that you will complete between weeks 3 and 9 of term. 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. You are likewise allowed to use large language models (LLMs) as a tool to help you learn R, find errors in code that doesn’t run correctly and so on. In other words, you are free to consult an LLM in the same way that you are free to consult your classmates and GTAs. I would be remiss, however, if I failed to sound a note of caution. ChatGPT4 is an incredibly valuable tool when used appropriately. While it is capable of generating convincing-sounding solutions to my problem set questions entirely on its own, it is as yet incapable of generating solutions that would receive a passing grade according to my Marking Criteria. Check yourself before you wreck yourself.
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 2024 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, solve the weekly problem sets, 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 an opportunity to complete a re-sit assignment that is due in early September. The summer re-sit assignment will be different from the original course assignments and, as it will not include any problem set questions, you may well find it more challenging. Working on a re-sit assignment is certain to spoil your summer, so take my advice and do what’s necessary to pass the first time around.
There will be a problem set for each of weeks 1–7 of TT. Your final assessment will feature three questions taken verbatim from these problem sets. In light of the rocky start we’ve gotten this term thanks to the microeconomics exam fiasco, I have released sample solutions to the problem set questions from Weeks #1 and #2. I will not release solutions to the other problem set questions. You are allowed, and indeed encouraged, to discuss these questions with your classmates and GTAs, although you are not allowed to submit code or results directly copied from another student as part of your final assessment.
It is a small project project of your own choosing, roughly equivalent to three problem set questions 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 final assessment.
You 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 shortly 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 email us a bit more detail about your project and schedule a short meeting to discuss further. We will aim to complete the project approval process as quickly as possible and by the beginning of week 6 by the latest.
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 the written report as to the problem set questions. Each of the two parts of your final submission will be assessed on a pass/fail basis, using the marking criteria from the course website. You must submit both parts to an appropriate standard to pass the course. The re-sit policy from the course website applies to the entire final assessment, including both parts.
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, 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. 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.