# A Correction for Regression Discontinuity Designs With Group-Specific Mismeasurement of the Running Variable

@article{Bartalotti2020ACF, title={A Correction for Regression Discontinuity Designs With Group-Specific Mismeasurement of the Running Variable}, author={Ot{\'a}vio Bartalotti and Quentin Brummet and Steven Dieterle}, journal={Journal of Business \& Economic Statistics}, year={2020}, volume={39}, pages={833 - 848} }

Abstract When the running variable in a regression discontinuity (RD) design is measured with error, identification of the local average treatment effect of interest will typically fail. While the form of this measurement error varies across applications, in many cases the measurement error structure is heterogeneous across different groups of observations. We develop a novel measurement error correction procedure capable of addressing heterogeneous mismeasurement structures by leveraging…

## 13 Citations

Noise-Induced Randomization in Regression Discontinuity Designs

- Economics, Mathematics
- 2020

A new approach to identification, estimation, and inference in regression discontinuity designs that exploits measurement error in the running variable is proposed and found to facilitate identification of both familiar estimands from the literature, as well as policy-relevant estimands that correspond to the effects of realistic changes to the existing treatment assignment rule.

IZA DP No . 11560 Regression Discontinuity and Heteroskedasticity Robust Standard Errors : Evidence from a Fixed-Bandwidth Approximation MAY 2018

- Mathematics, Economics
- 2018

IZA DP No. 11560 MAY 2018 Regression Discontinuity and Heteroskedasticity Robust Standard Errors: Evidence from a Fixed-Bandwidth Approximation* In regression discontinuity design (RD), for a given…

When Can We Ignore Measurement Error in the Running Variable?

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- 2021

In many empirical applications of regression discontinuity designs, the running variable used by the administrator to assign treatment is only observed with error. This paper provides easily…

Regression Discontinuity and Heteroskedasticity Robust Standard Errors: Evidence from a Fixed-Bandwidth Approximation

- Mathematics, Economics
- 2018

Abstract In regression discontinuity designs (RD), for a given bandwidth, researchers can estimate standard errors based on different variance formulas obtained under different asymptotic frameworks.…

RegressionDiscontinuity andHeteroskedasticity Robust Standard Errors : Evidence froma

- Mathematics
- 2018

In regression discontinuity designs (RD), for a given bandwidth, researchers can estimate standard errors based on different variance formulas obtained under different asymptotic frameworks. In the…

Complex Discontinuity Designs Using Covariates: Impact of School Grade Retention on Later Life Outcomes in Chile

- Mathematics
- 2020

Regression discontinuity designs are extensively used for causal inference in observational studies. However, they are usually confined to settings with simple treatment rules, determined by a single…

COMPLEX DISCONTINUITY DESIGNS USING COVARIATES: IMPACT OF SCHOOL GRADE RETENTION ON LATER LIFE OUTCOMES IN CHILE

- Mathematics
- 2022

Regression discontinuity designs are extensively used for causal inference in observational studies. However, they are usually confined to settings with simple treatment rules, determined by a single…

Covariate Adjustment in Regression Discontinuity Designs

- Economics
- 2021

The Regression Discontinuity (RD) design is a widely used non-experimental method for causal inference and program evaluation. While its canonical formulation only requires a score and an outcome…

Wild Bootstrap for Fuzzy Regression Discontinuity Designs: Obtaining Robust Bias-Corrected Confidence Intervals

- EconomicsThe Econometrics Journal
- 2020

This paper develops a novel wild bootstrap procedure to construct robust bias-corrected valid confidence intervals for fuzzy regression discontinuity designs, providing an intuitive complement to…

Revisiting the Effects of Unemployment Insurance Extensions on Unemployment: A Measurement Error-Corrected Regression Discontinuity Approach

- Economics
- 2020

The extension of Unemployment Insurance (UI) benefits was a key policy response to the Great Recession. However, these benefit extensions may have had detrimental labor market effects. While evidence…

## References

SHOWING 1-10 OF 63 REFERENCES

The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable

- Economics, Mathematics
- 2016

Identification in a regression discontinuity (RD) design hinges on the discontinuity in the probability of treatment when a covariate (assignment variable) exceeds a known threshold. If the…

Regression Discontinuity Design with Continuous Measurement Error in the Running Variable

- Mathematics, Economics
- 2017

On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference

- MathematicsJournal of the American Statistical Association
- 2018

ABSTRACT Nonparametric methods play a central role in modern empirical work. While they provide inference procedures that are more robust to parametric misspecification bias, they may be quite…

Regression Discontinuity Applications with Rounding Errors in the Running Variable

- Economics
- 2015

Many empirical applications of regression discontinuity (RD) models use a running variable that is rounded and hence is discrete, e.g., age in years, or birth weight in ounces. This paper shows that…

Including Covariates in the Regression Discontinuity Design

- Mathematics, EconomicsJournal of Business & Economic Statistics
- 2018

This article proposes a fully nonparametric kernel method to account for observed covariates in regression discontinuity designs (RDD), which may increase precision of treatment effect estimation. It…

Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs

- Mathematics
- 2014

In the regression‐discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In this design, local polynomial estimators…

Measurement Error Models with Auxiliary Data

- Mathematics, Economics
- 2005

We study the problem of parameter inference in (possibly non-linear and non-smooth) econometric models when the data are measured with error. We allow for arbitrary correlation between the true…

Heaping‐Induced Bias in Regression‐Discontinuity Designs

- Mathematics
- 2011

This study uses Monte Carlo simulations to demonstrate that regression-discontinuity designs arrive at biased estimates when attributes related to outcomes predict heaping in the running variable.…

Revisiting the Effects of Unemployment Insurance Extensions on Unemployment: A Measurement Error-Corrected Regression Discontinuity Approach

- Economics
- 2020

The extension of Unemployment Insurance (UI) benefits was a key policy response to the Great Recession. However, these benefit extensions may have had detrimental labor market effects. While evidence…