CoChat
Sign Up
Cited by 3,600Advanced Causal Inference TechniquesElectoral Systems and Political ParticipationSpatial and Panel Data Analysis

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

Open access
McCrary, Justin·2008·Journal of Econometrics
DOI 10.1016/j.jeconom.2007.05.005
Open this paper in CoChat — free accountOpen PDF

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 · 10.1016/j.jeconom.2007.05.005

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The distribution of applicants is smooth across the Berkeley admissions threshold, with the McCrary test yielding a p-value of 0.58, and baseline characteristics are also smooth across the threshold.

    “The distribution of applicants is smooth across the threshold, with the McCrary (2008) test yielding a p-value of 0.58 at the threshold.Baseline characteristics are also smooth across the threshold.”

    From Affirmative Action, Mismatch, and Economic Mobility after California’s Proposition 209 (2021) · cites this paper as McCrary (2008)

Self-check

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

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

Cites

Flagged first, then by citations

Research works printed but not linked: 34

  1. Aigner, Dennis J., Takeshi Amemiya, and Dale J. Poirier, "On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function," Interna- tional Economic Review, 1976, 17 (2), 377-396.
  2. Angrist, Joshua D., Guido W. Imbens, and Donald B. Rubin, "Identification of Causal Effects Using Instrumental Variables," Journal of the American Statistical Association, June 1996, 91 (434), 444- 455.
  3. Becker, Gary S., The Economics of Discrimination, Chicago: University of Chicago Press, 1957.
  4. Bouezmarni, Taoufik and Olivier Scaillet, "Consistency of Asymmetric Kernel Density Estimators and Smoothed Histograms with Application to Income Data," Econometric Theory, April 2005, 21 (2), 390-412.
  5. Card, David E., "The Causal Effect of Education on Earnings," in Orley Ashenfelter and David E. Card, eds., The Handbook of Labor Economics, Vol. 3A, Amsterdam: Elsevier, 1999.
  6. Cheng, Ming-Yen, "On Boundary Effects of Smooth Curve Estimators (Dissertation)," April 1994. Un- published manuscript Series # 2319, Institute for Statistics, University of North Carolina. , "A Bandwidth Selector for Local Linear Density Estimators," Annals of Statistics, 1997, 25 (3), 1001-1013. , "Boundary Aware Estimators of Integrated Density Products," Journal of the Royal Statistical Society, Series B, 1997, 59 (1), 191-203.
  7. Jianqing Fan, and James S. Marron, "Minimax Efficiency of Local Polynomial Fit Estimators at Boundaries," May 1993. Unpublished manuscript Series # 2098, Institute for Statistics, University of North Carolina. , , and , "On Automatic Boundary Corrections," The Annals of Statistics, August 1997, 25 (4), 1691-1708.
  8. Chernozhukov, Victor and Han Hong, "Likelihood Estimation and Inference in a Class of Nonregular Econometric Models," Econometrica, September 2004, 72 (5), 1445-1480.
  9. Chu, C.K. and P.E. Cheng, "Estimation of Jump Points and Jump Values of a Density Function," Statistica Sinica, 1996, 6 (1), 79-96.
  10. Cline, Darren B.H. and Jeffrey D. Hart, "Kernel Estimation of Densities with Discontinuities or Discon- tinuous Derivatives," Statistics, 1991, 22 (1), 69-84.
  11. Davison, Anthony C. and David V. Hinkley, Bootstrap Methods and Their Application, New York: Cam- bridge University Press, 1997.
  12. DiNardo, John E. and David S. Lee, "Economic Impacts of New Unionization on Private Sector Employers: 1984-2001," Quarterly Journal of Economics, November 2004, 119 (4), 1383-1441.
  13. DiNardo, John, Nicole Fortin, and Thomas Lemieux, "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semi-Parametric Approach," Econometrica, 1996, 64 (5), 1001-1044.
  14. Gawronski, Wolfgang and Ulrich Stadtmüller, "On Density Estimation by Means of Poisson's Distribu- tion," Scandinavian Journal of Statistics, 1980, 7 (2), 90-94.
  15. and , "Smoothing Histograms by Means of Lattice-and Continuous Distributions," Metrika, 1981, 28 (3), 155-164.
  16. Hahn, Jinyong, Petra Todd, and Wilbert van der Klaauw, "Identification and Estimation of Treatment Effects with a Regression Discontinuity Design," May 1999. NBER Working Paper # 7131. , , and , "Identification and Estimation of Treatment Effects with a Regression Discontinuity Design," Econometrica, February 2001, 69 (1), 201-209.
  17. Hall, Peter, "Effect of Bias Estimation on Coverage Accuracy of Bootstrap Confidence Intervals for a Probability Density," The Annals of Statistics, June 1992, 20 (2), 675-694.
  18. Ian McKay, and Berwin A. Turlach, "Performance of Wavelet Methods for Functions with Many Discontinuities," Annals of Statistics, 1996, 24 (6), 2462-2476.
  19. Härdle, Wolfgang and Oliver Linton, "Applied Nonparametric Methods," in Robert F. Engle and Daniel L. McFadden, eds., The Handbook of Econometrics, Vol. 4, New York: Elsevier, 1994, pp. 2297-2341.
  20. Heckman, James J., "The Scientific Model of Causality," Sociological Methodology, August 2005, 35 (1), 1-98. , Sergio Urzua, and Edward Vytlacil, "Understanding Instrumental Variables in Models with Essential Heterogeneity," Review of Economics and Statistics, August 2006, 88 (3), 389-432.
  21. Horowitz, Joel L., "The Bootstrap," in James J. Heckman and Edward Leamer, eds., The Handbook of Econometrics, Vol. 5, New York: Elsevier, 2001, pp. 3463-3568.
  22. Jacob, Brian A. and Lars Lefgren, "Remedial Education and Student Achievement: A Regression- Discontinuity Analysis," Review of Economics and Statistics, 2004, 86 (1), 226-244.
  23. Jones, M. Chris, "Discretized and Interpolated Kernel Density Estimates," Journal of the American Statistical Assocation, 1989, 84 (407), 733-741.
  24. Lee, David S., "The Electoral Advantage to Incumbency and Voters' Valuation of Politicians' Experience: A Regression Discontinuity Analysis of Elections to the U.S. House," August 2001. NBER Working Paper # 8441. , "Randomized Experiments from Non-random Selection in U.S. House Elections," Journal of Econo- metrics, forthcoming 2007.
  25. Marron, James S. and David Ruppert, "Transformations to Reduce Boundary Bias in Kernel Density Estimation," Journal of the Royal Statistical Society, Series B, 1994, 56 (4), 653-671.
  26. Pagan, Adrian and Aman Ullah, Nonparametric Econometrics, New York: Cambridge University Press, 1999.
  27. Rao, C. Radhakrishna, Linear Statistical Inference and Its Applications, 1st ed., New York: John Wiley and Sons, 1965.
  28. Rice, John, "Boundary Modification for Kernel Regression," Communications in Statistics, A, 1984, 13 (7), 893-900.
  29. Riker, William H., The Theory of Political Coalitions, New Haven: Yale University Press, 1962.
  30. Schuster, Eugene F., "Incorporating Support Constraints into Nonparametric Estimators of Densities," Communications in Statistics, A, 1985, 14 (5), 1123-1136.
  31. Sheather, Simon J. and M. Chris Jones, "A Reliable Data-Based Bandwidth Selection Method for Kernel Density Estimation," Journal of the Royal Statistical Society, Series B, 1991, 53 (3), 683-690.
  32. Stone, Mervyn, "Cross-Validation and Multinomial Prediction," Biometrika, December 1974, 61 (3), 509- 515. , "Asymptotics For and Against Cross-Validation," Biometrika, April 1977, 64 (1), 29-35.
  33. van der Klaauw, Wilbert, "Estimating the Effect of Financial Aid Offers on College Enrollment: A Regression-Discontinuity Approach," International Economic Review, November 2002, 43 (4), 1249- 1287.
  34. White, Halbert, Asymptotic Theory for Econometricians, San Diego: Academic Press, 2001.

Cited by

Sorted by citations

Authors
McCrary, J.
Affiliations
University of Michigan (US)
Corresponding author
McCrary, Justin
Venue
Journal of Econometrics
Publisher
Elsevier BV
Published
2008-02
Volume
142
Issue
2
Pages
698-714
ISSN
0304-4076 (ISSN-L)
DOI
10.1016/j.jeconom.2007.05.005
OpenAlex
W3123265974
Cited by
3,600
References
2
Citations by year
2026: 231 · 2025: 281 · 2024: 261 · 2023: 245 · 2022: 246 · 2021: 274 · 2020: 285 · 2019: 284 · 2018: 240 · 2017: 261 · 2016: 222 · 2015: 184 · 2014: 154 · 2013: 148 · 2012: 96
FWCI
34.43
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Journal of Econometrics (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
Keywords
regression discontinuity design, identification, sorting, House of Representatives elections, roll-call voting, potential outcomes

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