juliadiffindiffs/diffindiffs.jl

A suite of Julia packages for difference-in-differences

DiffinDiffs.jl is a suite of Julia packages for difference-in-differences (DID). The goal of its development is to promote applications of the latest advances in econometric methodology related to DID in academic research while leveraging the performance and composability of the Julia language.

Why DiffinDiffs.jl?

• Fast: Handle datasets of multiple gigabytes with ease
• Transparent: Completely open source and natively written in Julia
• Extensible: Unified interface with modular package organization

Package Organization

DiffinDiffs.jl reexports types, functions and macros defined in component packages that are separately registered. The package itself does not host any concrete functionality except documentation. This facilitates decentralized code development under a unified framework.

Package	Description	Version	Status
DiffinDiffsBase	Base package for DiffinDiffs.jl
InteractionWeightedDIDs	Regression-based multi-period DID

More components will be included in the future as development moves forward.

Installation

DiffinDiffs.jl can be installed with the Julia package manager Pkg. From the Julia REPL, type ] to enter the Pkg REPL and run:

pkg> add DiffinDiffs

This will install all the component packages of DiffinDiffs.jl as dependencies. There is no need to explicitly add the individual components unless one needs to access internal objects.

Usage

For details on the usage, please see the documentation.

diffindiffs.jl's Issues

Collaborate?

Hey, good to see someone else working on modern causal inference in Julia!

I'm the author of SynthControl and TreatmentPanels, two packages in a similar space.

With TreatmentPanels I'm trying to build a foundational "data prep" package which takes in a table and a treatment assignment and then constructs an object with a type which tells you whether the panel is balanced/unbalanced, single/multi-unit treatment, and whether the treatment is absorbing or switches on and off. It then provides functions to extract e.g. pre- and post-treatment outcomes, treatment periods and IDs of treated units etc.

In SynthControl I'm trying to pull together a bunch of recent methods in this space - starting from the most simple "just use all pretreatment outcomes" case to the classical Abadie/Diamond/Hainmueller and things like Synthetic Diff-in-Diff and Matrix Completion.

Finally I've also started implementing Sant'Anna/Zhao's DRDID, although that's not public yet (need to check licensing on that).

Maybe have a look at my stuff and see if any of it is useful or if you'd like to collaborate on anything!

Callaway SantAnna estimator

Hi and thanks again for this package!
I'd like to use it for my research project. Is there a chance this package can implement the estimator in DiD.R?

TagBot trigger issue

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I'll open a PR within a few hours, please be patient!

Cannot install by add DiffinDiffs and Documentation links (stable version) are invalid

Excited to know that such a useful package is now in Julia! As the title indicates, I found that two packages as a bundle are not available in project. Users have to install them separately and the doc link seems to be no longer valid.

And another issue w.r.t installing is that installation downgrades CSV from 0.10 to 0.8.5 and parsers.jl frome 2.2 to 1.1

Host component packages in `lib`

For the ease of resolving issues across multiple component packages and ensuring consistency with documentation in the long-run, I consider it worthwhile to migrate existing components to the lib folder as packages inside subfolders. It will still be possible to develop new components as separate packages, but anything that goes into the documentation should not be scattered elsewhere.

• Register DiffinDiffs.jl in General (#3)
• #10
• JuliaRegistries/General#56182
• Archive old repos for component packages

Interest in co-implementing additional methods?

Hi there,

I am the author of the {did2s} package for R and Stata and was wondering if you would be interested in implementing the method into Julia? I'm interested in learning a bit more Julia and figured this would be a good way to do it, but also would probably face some difficulties as it's a new language for me.