Linked Questions

3 votes
1 answer
6k views

Staggered Difference-in-Difference: Multiple Treatments Equation

I wonder if you can help me to figure out how to rewrite the basic difference-in-difference equation (pictured) so that it takes into account the fact that treatment has occurred at different times ...
Daria's user avatar
  • 33
4 votes
1 answer
10k views

Test for parallel trends in difference-in-difference models with staggered treatment

Following a comment from a previous thread (below), I would appreciate if you may advise me on how to test for parallel trends in Stata for a DiD model with multiple groups and staggered treatment (i....
Amira's user avatar
  • 61
3 votes
1 answer
6k views

Fixed effects in differences-in-differences

In a differences-in-differences it is quite typical to have $y_{ist} = \lambda_t + \alpha_s + \beta_1D_{s,t} + \epsilon_{ist}$, where $\lambda_t$ is a time fixed effect and $\alpha_s$ is a group ...
Daniel Pinto's user avatar
6 votes
1 answer
3k views

Difference-in-differences with no pre-treatment?

The typical difference-in-differences estimator (as fixed effects) fits a model of the form $$ y_{it} = \alpha_i + \delta T_{it} + X_{it}'\beta + \epsilon_{it} $$ where $T$ is some treatment that ...
user55417's user avatar
3 votes
1 answer
3k views

Difference-in-differences: dynamic treatment group/timing

I want to use difference-in-differences (DiD) to estimate a treatment effect. However, my problem is a little different from the standard DiD application in that: The items in the treatment group may ...
dingx's user avatar
  • 220
1 vote
1 answer
1k views

Diff-in-Diff time varying treatment

I would like to estimate a Difference in Difference specification where the treatment (i.e., the policy change P) is off then on and then off again: ...
cel's user avatar
  • 11
1 vote
1 answer
956 views

Panel data treatment effects with multiple treatments

I have a fairly large balanced panel dataset ($N$ = 1000 and $T$ = 200) that I want to estimate a treatment effect for. My first thought was a difference-in-difference (DID) framework on this, but I'm ...
WillDataForFood's user avatar
4 votes
1 answer
394 views

Is a DID model appropriate?

Suppose I have 3 groups (US states). One group has always had a "treatment" throughout the time period (always had a specific legal prohibition). One group never had the "treatment"...
Bryan's user avatar
  • 1,170
4 votes
1 answer
305 views

Does DiD work when not all individuals have pre-treatment observations?

I would like to make causal statements on the effect of a treatment on a group of individuals. I have panel data on these individuals but the treatments do not occur at the same time in their life. ...
badmax's user avatar
  • 2,171
2 votes
1 answer
346 views

Difference-in-differences with two treatments

I have two groups. Group 1 received intervention A and Group 2 received intervention B. I'm interested in seeing if intervention A is more effective than intervention B. People cannot be enrolled in ...
waterdesk91's user avatar
1 vote
1 answer
223 views

Why are my coefficients too large when control variables are not added?

I am doing a difference in differences analysis with staggered treatment time. Since the treatment time is different among subjects, I made my matrices look something like this from this post (Dynamic ...
kyrhee's user avatar
  • 45
0 votes
1 answer
158 views

How do I construct a consistent DiD estimator for this specification?

I have the following specification and I am attempting to re-write this in a DiD form which I can then go on to find $\hat{\beta}_{did}$ using OLS. $n$ observations $t \in\{1,2\}$ time periods $x_{it}/...
user avatar
0 votes
1 answer
143 views

What does an xtreg equation look like?

I ran some FE regressions in Stata using xtreg. One “normal” fixed effects model and a second generalized difference-in-differences model. Now, I am wondering how ...
Sam's user avatar
  • 95
0 votes
1 answer
82 views

What is the best way to model when the treatment is intermittent across years?

Let's say the goal is to gauge the effect of deploying certain clean technology (dummy variable: 1 for the year the technology is deployed, 0 otherwise) on a firm's pollution level (continuous ...
Chuan's user avatar
  • 145