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Difference In Differences
Introduction
The first time I heard about Difference in Differences was in the PhD level longitudinal analysis class at Harvard with Dr. Tom Chen.
We had a student who was previously trained as an economist who raised his hand and brought this concept up. As a bright-eyed Master’s student who got a B+ in Introduction to Economics, I did not know what this concept was.
Today, I’m going to try to learn a bit more about it.
After a solid 20 minutes of browsing the web, it’s reductively just introducing an interaction term between time and treatment…
Walking through this example: https://www.princeton.edu/~otorres/DID101R.pdf
library(foreign)
mydata <- read.dta("http://dss.princeton.edu/training/Panel101.dta")
mydata$time = ifelse(mydata$year >= 1994, 1, 0)
mydata$treated = ifelse(mydata$country == "E" |
mydata$country == "F" |
mydata$country == "G", 1, 0)
mydata$did = mydata$time * mydata$treated
didreg = lm(y ~ treated + time + did, data = mydata)
summary(didreg)
Call:
lm(formula = y ~ treated + time + did, data = mydata)
Residuals:
Min 1Q Median 3Q Max
-9.768e+09 -1.623e+09 1.167e+08 1.393e+09 6.807e+09
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.581e+08 7.382e+08 0.485 0.6292
treated 1.776e+09 1.128e+09 1.575 0.1200
time 2.289e+09 9.530e+08 2.402 0.0191 *
did -2.520e+09 1.456e+09 -1.731 0.0882 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.953e+09 on 66 degrees of freedom
Multiple R-squared: 0.08273, Adjusted R-squared: 0.04104
F-statistic: 1.984 on 3 and 66 DF, p-value: 0.1249
didreg1 = lm(y ~ treated*time, data = mydata)
summary(didreg1)
Call:
lm(formula = y ~ treated * time, data = mydata)
Residuals:
Min 1Q Median 3Q Max
-9.768e+09 -1.623e+09 1.167e+08 1.393e+09 6.807e+09
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.581e+08 7.382e+08 0.485 0.6292
treated 1.776e+09 1.128e+09 1.575 0.1200
time 2.289e+09 9.530e+08 2.402 0.0191 *
treated:time -2.520e+09 1.456e+09 -1.731 0.0882 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.953e+09 on 66 degrees of freedom
Multiple R-squared: 0.08273, Adjusted R-squared: 0.04104
F-statistic: 1.984 on 3 and 66 DF, p-value: 0.1249