dynamic diff-in-diff in r

To conduct a dynamic diff-in-diff analysis in R, you can use the ddid package. This package provides a set of functions that implements difference-in-differences models for panel data.

First, you need to load the ddid package:

main.r
library(ddid)
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The package includes two main functions for dynamic diff-in-diff analysis:

1. dynamicDID: This function estimates dynamic difference-in-differences models using a first differences approach.

2. did_coefficients: This function computes the difference-in-differences coefficients for each time period and stores them in a data frame.

Here is an example of how to use these functions with some simulated panel data:

main.r
# Load simulated panel data
data("simPanelData")

# Estimate dynamic diff-in-diff model
diabetes_diff <- dynamicDID(outcome_variable = "y",
                             treatment_variable = "treat",
                             time_variable = "time",
                             id_variable = "id",
                             data = simPanelData)

# Compute difference-in-differences coefficients
diabetes_coeffs <- did_coefficients(model = diabetes_diff)
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In this example, simPanelData is a simulated panel dataset that includes an outcome variable y, a treatment variable treat, a time variable time, and an id variable id. The dynamicDID function estimates the dynamic difference-in-differences model using these variables, and did_coeficients computes the difference-in-differences coefficients for each time period.