Difference in Differences - Online Course
A 3-Day Livestream Seminar Taught by
Nick Huntington-Klein10:00am-12:30pm (convert to your local time)
1:30pm-3:30pm
This course offers an overview of difference-in-differences (DID) methodology. DID compares before/after differences for a treated group against before/after differences for a group that did not receive treatment at that time to estimate a causal effect of treatment.
Difference-in-differences can be applied in many settings, and is probably the most-used quasi-experimental design in the modern quantitative social sciences. Learning to use and evaluate DID designs is crucial for policy evaluation and understanding the applied causal inference literature. However, using DID appropriately can be tricky, and several poor practices have become common in the literature (especially in regards to rollout designs where different groups receive treatment at different times).
In this course, we will address the fundamentals of difference-in-differences methods in depth, with special attention to the many details of execution. We will also evaluate several studies so that participants will be able to understand and use findings from the published literature that uses DID methods, such as work on minimum wage or immigration.
Starting February 9, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.
*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.
Closed captioning is available for all live and recorded sessions.
More details about the course content
After this course, you will be able to:
- Understand difference-in-differences designs and when to use them.
- Estimate DID models.
- Evaluate the plausibility of DID assumptions.
- Use popular extensions to DID, such as rollout designs.
- Understand related methods like synthetic control and matrix completion.
After this course, you will be able to:
- Understand difference-in-differences designs and when to use them.
- Estimate DID models.
- Evaluate the plausibility of DID assumptions.
- Use popular extensions to DID, such as rollout designs.
- Understand related methods like synthetic control and matrix completion.
Computing
This is a hands-on course with instructor-led software demonstrations and guided exercises. These guided exercises will be presented using the R language, so you should use a computer with a recent version of R (version 4.0.0 or later) and RStudio (version 1.4 or later). Code files will also be available for Stata. If you wish to work in Stata, we recommend using version 15 or later.
To follow along with the course exercises, you should be able to perform basic data manipulation and analyses in R or Stata.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent on-line resources for building your R skills.
This is a hands-on course with instructor-led software demonstrations and guided exercises. These guided exercises will be presented using the R language, so you should use a computer with a recent version of R (version 4.0.0 or later) and RStudio (version 1.4 or later). Code files will also be available for Stata. If you wish to work in Stata, we recommend using version 15 or later.
To follow along with the course exercises, you should be able to perform basic data manipulation and analyses in R or Stata.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent on-line resources for building your R skills.
Who should register?
You should take this course if you want to understand how to evaluate published difference-in-differences studies or perform DID analyses on your own. You should have a basic working knowledge of your language of choice (R or Stata) and should be familiar with linear regression and how to work with regression in code. Extensive programming experience is not necessary.
This course does not require calculus or familiarity with statistical proofs, and is appropriate for students or researchers who have a working knowledge of introductory statistics and linear regression.
You should take this course if you want to understand how to evaluate published difference-in-differences studies or perform DID analyses on your own. You should have a basic working knowledge of your language of choice (R or Stata) and should be familiar with linear regression and how to work with regression in code. Extensive programming experience is not necessary.
This course does not require calculus or familiarity with statistical proofs, and is appropriate for students or researchers who have a working knowledge of introductory statistics and linear regression.
Seminar outline
Day 1:
-
- The concepts behind difference-in-differences
- The structure of the research design
- Key assumptions (no-anticipation and parallel trends)
- Divorcing design from estimation
- Basic DID estimation
- 2×2 designs
- Two-way fixed effects
- Covariates and/or matching
Day 2:
-
-
- Other approaches to covariates and/or matching
-
- Evaluating assumptions
- Prior trends estimation
- Other placebo tests
Day 3:
-
- Dynamic DID
- Rollout designs
- Problems with two-way fixed effects
- Alternative estimators
- A preview of extensions and related methods
- Difference-in-difference-in-differences
- Fuzzy DID
- Distributional DID
- Synthetic control
- Matrix completion
Day 1:
-
- The concepts behind difference-in-differences
- The structure of the research design
- Key assumptions (no-anticipation and parallel trends)
- Divorcing design from estimation
- Basic DID estimation
- 2×2 designs
- Two-way fixed effects
- Covariates and/or matching
- The concepts behind difference-in-differences
Day 2:
-
-
- Other approaches to covariates and/or matching
-
-
- Evaluating assumptions
- Prior trends estimation
- Other placebo tests
- Evaluating assumptions
Day 3:
-
- Dynamic DID
- Rollout designs
- Problems with two-way fixed effects
- Alternative estimators
- A preview of extensions and related methods
- Difference-in-difference-in-differences
- Fuzzy DID
- Distributional DID
- Synthetic control
- Matrix completion
Payment information
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.