Distributional Synthetic Controls Estimation
Overview
The method of synthetic controls is a widely-adopted tool for evaluating causal effects of policy changes in settings with observational data. In many settings where it is applicable, researchers want to identify causal effects of policy changes on a treated unit at an aggregate level while having access to data at a finer granularity. This package implements a simple extension of the synthetic controls estimator, developed in Gunsilius (2023) doi:10.3982/ECTA18260, that takes advantage of this additional structure and provides nonparametric estimates of the heterogeneity within the aggregate unit. The idea is to replicate the quantile function associated with the treated unit by a weighted average of quantile functions of the control units. The package contains tools for aggregating and plotting the resulting distributional estimates, as well as for carrying out inference on them.
- Performance release: the bootstrap confidence intervals are about 3x faster and the permutation test and point estimation meaningfully faster, from sorting each sample once and evaluating quantiles/CDFs on the sorted data, and from vectorizing the confidence-interval assembly. Results are numerically identical to 0.1.3 for the same seed.
From NEWS.md in the release
Install
Health
- OK13 OK2026-10-17
- ERROR12 OK, 1 ERROR2026-10-14
- OK13 OK2026-09-25
- ERROR12 OK, 1 ERROR2026-09-18
- OK13 OK2026-08-05
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- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-23
- ERROR12 OK, 1 ERROR2026-06-22
- OK13 OK2026-06-01
- ERROR11 OK, 2 ERROR2026-05-29
- OK13 OK2026-05-06
- ERROR12 OK, 1 ERROR2026-05-04
- OK14 OK2026-04-09
- ERROR13 OK, 1 ERROR2026-04-02
- OK14 OK2026-03-25
- ERROR13 OK, 1 ERROR2026-03-22
- OK14 OK2026-03-21
- ERROR13 OK, 1 ERROR2026-03-20
- OK14 OK2026-03-15
- ERROR12 OK, 2 ERROR2026-03-10
Documentation
- Help pages
- 28 (19 internal)
- Examples that run
- 0%2 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 33%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 14% with a bibliography file
Downloads
Repository
- PRs merged (all time)
- 100%
- Median days to close, 50 most recently updated closed issues
- not measured
- Median days to close, 50 most recently updated closed PRs
- 0
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8 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/davidvandijcke/discos on 2026-10-18.
GitHub Pages site last deployed 2026-08-05 · The repository has a site deploy workflow
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Dependencies
Installing DiSCos adds 60 packages (30 with compiled code, 50 MB of source tarballs). Heaviest: ggplot2 6.0 MB, clarabel 5.7 MB, data.table 5.7 MB.
CRAN will archive these unless their check problems are fixed by the date shown. This package needs each one to install.
- evmixdeadline passed Oct 12
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- 0.1.4Latest
- RR 4.6.0 released · 2026-04-24
- 0.1.32026-03-07 · diff ↗
- unarchivedReturned to CRAN2026-02-04
- 0.1.22026-02-04 · diff ↗
- archivedRemoved from CRAN2025-11-07issues were not corrected despite reminders
- RR 4.5.0 released · 2025-04-11
- 0.1.12024-07-23 · diff ↗
- 0.1.02024-05-13 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 0.0.12024-03-14
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2024-03-14
- Total releases
- 6 / 2 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 1.4 MB / 1 file
- Download size
- 1.9 MB
Cite
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