knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )

`bacondecomp`

is a package with tools to perform the Goodman-Bacon decomposition for differences-in-differences with variation in treatment timing. The decomposition can be done with and without time-varying covariates.

You can install `bacondecomp 0.1.0`

from CRAN:

install.packages("bacondecomp")

You can install the development version of `bacondecomp`

from GitHub:

library(devtools) install_github("evanjflack/bacondecomp")

`bacon()`

: calculates all 2x2 differences-in-differences estimates and weights for the Bacon-Goodman decomposition.

`math_refom`

: Aggregated data from Goodman (2019, JOLE)`castle`

: Data from Cheng and Hoekstra (2013, JHR)`divorce:`

Data from Stevenson and Wolfers (2006, QJE)

This is a basic example which shows you how to use the bacon() function to decompose the two-way fixed effects estimate of the effect of an education reform on future earnings following Goodman (2019, JOLE).

library(bacondecomp) df_bacon <- bacon(incearn_ln ~ reform_math, data = bacondecomp::math_reform, id_var = "state", time_var = "class") library(ggplot2) ggplot(df_bacon) + aes(x = weight, y = estimate, shape = factor(type)) + geom_point() + geom_hline(yintercept = 0) + labs(x = "Weight", y = "Estimate", shape = "Type")

Goodman-Bacon, Andrew. 2018. "Difference-in-Differences with Variation in Treatment Timing." National Bureau of Economic Research Working Paper Series No. 25018. doi: 10.3386/w25018.

evanjflack/bacondecomp documentation built on Jan. 28, 2020, 12:10 a.m.

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