The typical way to estimate a difference in differences model with more than two time periods is your proposed solution b). Keeping your notation you would regress Y i s t = α + γ s (Treatment s) + λ (year dummy t) + δ D s t + ϵ i s t
Full Answer
Do I need an interaction term for the treatment variable?
You do not need an interaction term in this case, because the interaction is implicit in the treatment variable. The treatment variable equals 1 if an earthquake has struck in the municipality, and only after or at the same time the earthquake has struck. That is the equivalent of treatment#post.
How do you do a did analysis with two variables?
For a (basic) DiD analysis, you need two dummy variables. The first identifies the treatment group (1 if the unit belongs to the treatment group, 0 otherwise). I call this variable treatment below. The second dummy identifies the post-treatment period (1 after the event, 0 before).
When to turn on the treatment variable?
The important thing is that the treatment variable is turned on for observations when the causal mechanism is affecting the dependent variable, whatever that means. Last edited by Kris Bitney; 24 Mar 2017, 17:05 . you probably forgot to include the dependent variable in the -xtreg- command.
Why can’t I use classical difference in differences (did) analysis?
Because your treatment changes in the counties are not synchronized, this is not amenable to classical difference in differences (DID) analysis. It must be analyzed with generalized difference in differences.
Did with variation in treatment timing?
The canonical difference-in-differences (DD) model contains two time periods, “pre” and “post”, and two groups, “treatment” and “control”. Most DD applications, however, exploit variation across groups of units that receive treatment at different times.
What is staggered difference in difference?
Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the presence of treatment effect heterogeneity.
Is difference in difference time series?
In contrast to a time-series estimate of the treatment effect on subjects (which analyzes differences over time) or a cross-section estimate of the treatment effect (which measures the difference between treatment and control groups), difference in differences uses panel data to measure the differences, between the ...
Can treatment variables be continuous?
But continuous treatment variables frequently arise and can provide much richer information— sometimes fundamentally different information—about treatment effects than a binary variable can.
What is generalized diff in diff?
The modified DD is a generalized difference in differences (GDD), which is a DD with one additional time-wise difference. GDD allows the selection effect to be a constant that is not necessarily zero, and the constant is removed by the additional time-wise difference using the two pretreatment periods.
What is a difference in difference model?
The difference-in-differences method is a quasi-experimental approach that compares the changes in outcomes over time between a population enrolled in a program (the treatment group) and a population that is not (the comparison group). It is a useful tool for data analysis.
How do you perform a difference difference analysis?
General Method The data is analyzed by first calculating the difference in first and second time periods, and then subtracting the average gain (or difference) in the control group from the average gain (or difference) in the treatment group.
How do you find the difference in differences?
10:2212:48An intuitive introduction to Difference-in-Differences - YouTubeYouTubeStart of suggested clipEnd of suggested clipThe difference across time in the control group right here remember that was d1. Actually that wasMoreThe difference across time in the control group right here remember that was d1. Actually that was d2. That's going to be just beta 1 the difference across time in the treatment group is going to be
Should we combine difference in differences with conditioning on pre-treatment outcomes?
Taken together, these results suggest that we should not combine DID with conditioning on pre-treatment outcomes but rather use DID conditioning on covariates that are fixed over time. When the PTA fails, DID applied symmetrically around the treat- ment date performs well in simulations and when compared with RCTs.
What is continuous treatment?
Continuous Treatment Rule — a common law liability doctrine stating that if a physician has treated a patient over a period of time, only one policy limit applies—the one in force at the time the claim is made.