Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 960

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test

Open access
McCrary, Justin·2007·National Bureau of Economic Research

Abstract

Standard sufficient conditions for identification in the regression discontinuity design are continuity of the conditional expectation of counterfactual outcomes in the running variable.These continuity assumptions may not be plausible if agents are able to manipulate the running variable.This paper develops a test of manipulation related to continuity of the running variable density function.The methodology is applied to popular elections to the House of Representatives, where sorting is neither expected nor found, and to roll-call voting in the House, where sorting is both expected and found.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3386/t0334

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 6 references

Cited by

See all 960

Metadata

Authors
McCrary, J.
Venue
National Bureau of Economic Research
Published
2007-01
OpenAlex
W2151352067
Cited by
960
References
6
Type
report
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test. https://app.cochat.ai/papers/10.3386/t0334
The paper
McCrary, J. (2007). Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test. National Bureau of Economic Research. https://doi.org/10.3386/t0334

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.