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.

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. 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

- Wednesdays 11-12:30pm
- Thursdays 11:30-1pm
- Fridays 11:30-1pm

Weeks 2-9 of Trinity Term. (For the North Americans among us, these are *TA office hours*.)

- Mondays 2-5pm, MRB Skills Lab
- Tuesdays 2-5pm, MRB Seminar Room D

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.
It will be assessed based on a single assignment **due at noon on Tuesday of Trinity Term Week 9**, in other words: June 20th.
The assignment will *extremely similar* to the weekly problem sets, described below.
In effect it will be a “coursework portfolio.”
For further details see Problem Sets and Asessment along with Marking Criteria and Inspera Submission Requirements below.

**Week 1**- Lectures 01-03: Crash Course in R Programming, Solutions

**Week 2**- Lecture 04: Continuation of R Crash Course
- Lecture 05: Getting Started with
`dplyr`

, Solutions - Lecture 06: Getting Started with
`ggplot2`

, Solutions

**Week 3**- Lecture 07: Monte Carlo Simulation Basics, Solutions
- Lecture 08: Research Plumbing I, Solutions
- Lecture 09: Linear Regression, Solutions

**Week 4**- Lecture 10: Running a Simulation Study, Solutions
- Lecture 11: The Multivariate Normal Distribution, Solutions
- Lecture 12: Instrumental Variables, Solutions

**Week 5**- Lecture 13: Research Plumbing II, Solutions
- Lecture 14: Logistic Regression, Solutions
- Lecture 15: Statistical Inference - Defense Against the Dark Arts, Solutions

**Week 6**:- Lecture 16: Q&A Session (MRB Lecture Theatre)
- Lecture 17: Heteroskedasticity and Clustering, Solutions
- Lecture 18: Panel Data Basics, Solutions

**Week 7**:- Lecture 19: Selection-on-observables
- Lecture 20: DAGs and Bad Controls
- Lecture 21: Regression Discontinuity

**Week 8**:- Lecture 22: Guest Lecture (Ana Verdnik)
- Lecture 23: Local Average Treatment Effects
- Lecture 24: Difference-in-Differences

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 newly-created lecture slides will be the final authority on the course material in the 2023 version of core ERM. I hope to rework the book before the 2024 version of core ERM.

Each Friday of term, I will assign a problem set covering that week’s material.
Last year, these problems were graded on a pass/fail basis and you had to pass 6/8 to pass the course.
For complicated and frustrating reasons, I am no longer permitted to assess core ERM in this way.
Instead you will be assessed, again pass/fail, on the basis of a single large assignment that I will post on canvas on Friday of week 8 and which will be due at **noon on June 20th** on Inspera.
See below for details of the Inspera submission requirements.
Nearly all of the problems from this assessment will be taken *verbatim* from your weekly problem sets, so it behooves you to solve them every week and get help from the GTAs at their drop-in surgeries if you get stuck.
Since the problem sets will feature in your final assessment, I will not circulate solutions during the term.
You are allowed, and indeed encouraged, to discuss the problem sets with your classmates, but you are not allowed to directly copy code or results from another student.
The work that you submit at the end of the term must be your own, even if it incorporates suggestions from your classmates and GTAs.
If you fail the final assessment for core ERM, you will be given an opportunity to resubmit it in early September, but your aim should be to **pass the first time around**.
I’m sure you have better things to do with your summer than revisit my problem set questions.

- Problem Set #1: Making Change, Sieving Primes
- Problem Set #2: Bias in the Labor Market, Growth Accounting
- Problem Set #3: Desert Island Monte Carlo, Quarto/RMarkdown, Football & Market Efficiency
- Problem Set #4: Optimal Stopping, Bivariate Normal Simulation, Colonial Origins
- Problem Set #5: Lead Cleanup, Contaminated Wells in Bangladesh, Filedrawer / Publication Bias
- Problem Set #6: Robust SEs, Airfare Panel
- Problem Set #7:

The final assessment for 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.

**Clean Code:**Your R code must adhere to the tidyverse style guide. It should be clean, easy to read, and appropriately commented.**Correct Code:**Your R code must be syntactically correct, i.e. it must run without errors. This will be assessed based on your ability to successfully knit an RMarkdown/Quarto file with your results: your file will not knit unless the code is correct. More details on RMarkdown/Quarto will be provided in lectures.**Formatting & Typesetting:**You will submit a single pdf document constructed from one or more underlying RMarkdown/Quarto reports incorporating your code and detailing your solutions to the questions on the assessment. Your write-ups should be clearly formatted using appropriate markdown commands. Any mathematical formulas that you incorporate should be clearly and cleanly typeset using appropriate LaTeX commands.**Completeness:**To pass a given question on the final assessment, your answer must at a minimum be substantially complete. Partial solutions only receive partial marks, regardless of quality.**Quality:**To pass a given question on the assignment, your answer must be substantially correct. Poorly explained or substantially incorrect answers will only receive partial marks.

I am sorry to report that Inspera is a royal pain in the posterior.
Only the “World’s Best University” could get away with using a system this silly!
To avoid heartache, it’s crucial that you follow these instructions **precisely**.

- Submit a single PDF document to Inspera. This document should be generated following the instructions that I will provide in class later in the term.
- This course is graded
*anonymously*so**do not write your name on your assignment!** - You can log into Inspera with your Oxford Single Sign-on at this url
- The Online Assessments Page has has all the information needed to successfully submit your coursework, including a Quick Reference Guide.
- In addition, this short video walks you through the final step of pressing “Submit now” to ensure that your work reaches your examiners.
- You
**MUST**ensure that you upload your file and, when you are happy you have uploaded the correct and final file(s), submit them. This is a two-step process. Your work is**NOT**submitted until you have pressed the**Submit now**button. - Once you press the “Submit now” button, you will be shown a confirmation that your work has been submitted. You can also view the work you have submitted by going to the Dashboard in Inspera and clicking on “Archive”
- You won’t be able to edit your submission in Inspera after you press “Submit now” so make sure that you check your work
**VERY CAREFULLY**before you submit it. - If you do identify a problem with the file you have submitted, you can replace the file before the deadline, or within 30 minutes of the deadline by emailing
**Lesley Darcy**at econgrad@economics.ox.ac.uk. Lesley is a busy person, so please reserve this option for serious problems, not minor errors. Remember: this is a pass/fail course. - It is your responsibility to familiarize yourself with Inspera. You can practice before the deadline by visiting the practice site on your Inspera dashboard.

Around 80 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.