A major issue with rd designs, in terms of internal validity, is whether units are able to manipulate their score on the assignment variable e. Justin mccrary university of michigan december 2006 abstract standard su. Using a regression discontinuity design and selfreported test data from national health surveys, we find test rates for breast, colorectal, and prostate cancer increase at the guideline age. The regressiondiscontinuity rd design is widely used in applied work.
As ive said im beginning to study statistics and have read a bit on regression discontinuity designs but i dont know if all the computations to get the discontinuity graph and the local average effect should be done by hand or if theres a stata command that may help im thinking of a sharp regression discontinuity design as a first step. An intuitive introduction to regression discontinuity youtube. Polynomials should not be used in regression discontinuity. In this article, we describe a major upgrade to the stata and r software package. It is impossible to definitively test for validity if agents are able to perfectly determine their treatment status. Testing for treatment effect hetereogeneity in regression. Card, lee, pei, and weber 2012 regression kink design models continuous kinked treatment. Manipulation of the running variable in the regression. Regression discontinuity frd design, where the probability of receiving the treatment jumps discontinuously at the threshold for the forcing variable, but not necessarily from zero to one. Stata code and data for all examples will be available on chalk.
In this sense, it is much like an experimental design. We examine local polynomial estimators that include discrete or continuous covariates in an additive separable way, but without imposing any parametric restrictions on the underlying. The rdrobust package provides stata and r implementations of statistical inference and graphical procedures for regression discontinuity designs employing local polynomial and partitioning methods. We describe a major upgrade to the stata and r rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regressiondiscontinuity designs.
Local linear regression discontinuity analyses were conducted using the rdrobust program in stata 14 for information about this software and corresponding techniques, see calonico et al. Regression discontinuity practical applications basic intuition ii we see these institutional rules all the time cannot get medicaid unless income is below 150 percent of the poverty line must have a gpa of 3. Statistical software components from boston college department of economics. Software for estimation and inference in regression discontinuity designs. As a substantive application of our results, we develop a novel discontinuity in density testing procedure, an important problem in regression discontinuity designs and other program evaluation settings. Regression discontinuity rd analysis is a rigorous nonexperimental1 approach that can be used to estimate program impacts in situations in which candidates are. It provides point estimators, confidence intervals estimators, bandwidth selectors, automatic rd plots, and other related features. Regression discontinuity designs exploit substantive knowledge that treatment is assigned in a particular way. Regression discontinuity rd analysis is a rigorous nonexperimental1 approach that can be used to estimate program impacts in situations in which candidates are selected for treatment based on whether their value for a numeric rating exceeds a designated threshold or cutpoint. The main new features of this upgraded version are as follows. An r package for robust nonparametric inference in regression discontinuity designs, r journal 71.
Plan of the three lectures on regression discontinuity designs. Estimation is accomplished using local linear regression. Under stata versions 10 or later using lpoly to construct local regression. Regressiondiscontinuity analysis research methods knowledge base. Robust datadriven inference in the regression discontinuity design, stata journal 144.
We should emphasize that this book is about data analysis and that it demonstrates how stata can be used for regression analysis, as opposed to a book that covers the statistical basis of multiple regression. Notes for matlab and stata regression discontinuity software. Graphs in regression discontinuity design in stata or r. Regression discontinuity design in stata part 1 stata daily. Introduction to regression discontinuity rd designs rd designs as local randomized experiments and the manipulation problem. Feb 25, 2014 as ive said im beginning to study statistics and have read a bit on regression discontinuity designs but i dont know if all the computations to get the discontinuity graph and the local average effect should be done by hand or if theres a stata command that may help im thinking of a sharp regression discontinuity design as a first step. Simple local polynomial density estimators princeton. Software for regressiondiscontinuity designs matias d. However, there are some tests that can provide evidence that either supports or discounts the validity of the regression discontinuity design. For the full sample, i keep observations only within the desired bandwidth and then run the following stata code. Testing for treatment e ect heterogeneity in regression discontinuity design yuchin hsuy institute of economics academia sinica shu shenz department of economics university of california, davis yemail. Estimating causal effects using a regression discontinuity approach stata textbook examples. Journal of econometrics, 1422, february 2008, pages 698.
It is one of the most credible quasiexperimental research designs for identi. Copy the do and help files into your stata working directory or use stata s net install command to access them remotely from a web page. The stata journal analysis of regression discontinuity. By analyzing a set of user defined placebo estimates.
The test involves estimation of the discontinuity in the density function of the running variable at the cutoff. Stata module to perform regression discontinuity, statistical software components s458238, boston college department of economics. Create a regression discontinuity design declaredesign. Stata module to perform a permutation test for the regression kink rk and regression discontinuity rd design, statistical software components s458536, boston college department of economics, revised 25 dec 2018. It presents the basic theory behind the research design, details when rd is likely to be valid or invalid given economic incentives. Regression discontinuity design regression discontinuity rdd is a research design for the purposes of causal inference. Regression discontinuity designs in economics david s. Discontinuity design relative to an otherwise comparable randomized. Using spss to analyze data from a regression discontinuity design the methods employed here follow the advice found in chapter 11 of trochim, w.
Dear all, i am a freshman and learning regression discontinuity design in recent days. If there are thresholds whereby some observations receive the treatment above it, other those below it do not, and those immediately above or below that threshold are similar, we can use the difference of the outcome between those just above and those just below the threshold to estimate the causal effect of the treatment. Journal of the american statistical association 110512. The command rdmc applies to noncummulative and cummulative multicuto rd settings. Regression discontinuity design rdd is a quasiexperimental evaluation option that measures the impact of an intervention, or treatment, by applying a treatment assignment mechanism based on a continuous eligibility index which is a variable with a continuous distribution. We introduce the stata and r package rdmulti, which includes three commands rdmc, rdmcplot, rdms for analyzing regression discontinuity rd designs with multiple cuto s or multiple scores. Thistlewhite and campbell introduced the regression discontinuity design in the 1960s to study the impact of scholarships on academic success. The regression discontinuity design rdd is a quasiexperimental approach that was developed specifically to minimize confounding bias in the assessment of policies, treatments and interventions that are based on a cutoff rule or threshold. Regression discontinuity rd analysis is a rigorous nonexperimental. Two companion stata and r software packages are provided. Regression discontinuity rdd is a research design for the purposes of causal inference. Even though researchers do not control the assignment, substantive knowledge about the threshold serves as a basis for a strong identification claim.
How to do regression discontinuity and interpret results in stata 16 oct 2017, 17. Recent advances and applications the main reference for the lectures is d. Inference in regression discontinuity designs under local randomization, with rocio titiunik and gonzalo vazquezbare. This book is composed of four chapters covering a variety of topics about using stata for regression. Bloom, 2012, a practical guide to regression discontinuity, mdrc, pdf. The average treatment effect local to the cutpoint is equal to tau. Software for bandwidth and codes for the manipulation. In this video i give you a prototypical situation where rd. Manipulation of the running variable in the regression discontinuity design.
Command rdplot is a newly developed code by very renowned scholars in this field. For a term paper, i am estimating local treatment effects using a regression discontinuity design, and i want to test whether the effect of crossing the threshold is different for men and women. I am trying to estimate the impact of a social program on intrahousehold labour supply. Testing for treatment e ect heterogeneity in regression. In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design rdd is a quasiexperimental pretestposttest design that elicits the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned. Dcdensity implements the mccrary 2008 sorting test. This work was supported by the national science foundation. There has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. As ive said im beginning to study statistics and have read a bit on regression discontinuity designs but i dont know if all the computations to get the discontinuity graph and the local average effect should be done by hand or if theres a stata command that may help im thinking of a sharp regression discontinuity design as a. This paper describes identification problems encountered in the regression discontinuity design pertaining to manipulation of the running variable and describes a simple test for manipulation. Regression discontinuity world bank sief aphrc impact evaluation training 2015 owen ozier development research group the world bank 6 may 2015 owen ozier the world bank regression discontinuity 6 may 2015 1 9.
This presentation focused on the theory, design, and implementation of regression discontinuity rdd. Imbens and lemieux 2008 regression discontinuity design. Stata module to perform a permutation test for the. For example, perhaps students in a school take a test in 8th grade. Dec 16, 2015 there has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. Regression discontinuity and practical applications. Misunderstandings about the regression discontinuity design in the study of close elections. See stata and matlab code here code from imbens software page. All methods are implemented in r and stata software packages. Lee and thomas lemieux this paper provides an introduction and user guide to regression discontinuity rd designs for empirical researchers.
A practical guide to regression discontinuity mdrc. Regression discontinuity world bank sief aphrc impact. The latest version of this software, as well as other related software for rd designs. Jan 30, 2015 when the circumstances are right, regression discontinuity can be an excellent way to extract causal estimates from observational data. Ab we study regression discontinuity designs when covariates are included in the estimation. The regression discontinuity rd design is widely used in applied work. Builds a design with sample from population of size n. Rd designs are also easy to present, interpret and falsify, features that have contributed to their popularity among. The stata journal university of california, berkeley.
A function is also included to test the assumption of nosorting effects. A provided function will utilize imbenskalyanaraman optimal bandwidth calculation. The basic rd design is a twogroup pretestposttest model as indicated in the design notation. Manipulation testing based on density discontinuity. Stata module to perform a permutation test for the regression kink rk and regression discontinuity rd design, statistical software.
A guide to practice, imbens and lemiux, journal of econometrics 2008. It is one of the best quasiexperimental research designs for identi cation, estimation and inference of treatment e ects local to the cuto. Stata module for regression discontinuity estimation. A density test, mccrary, journal of econometrics 2008 regression discontinuity designs. Improving causal inference in educational and social science research by richard j. Regression discontinuity design in stata part 1 posted on 16 december 2015 by mitch abdon there has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. This work was supported in part by the national science foundation through grants ses57561 and ses1459931. Using a regression discontinuity design and selfreported test data from national health surveys, we find test rates for breast and colorectal cancer increase at the guideline age thresholds by. Copy the do and help files into your stata working directory or use statas net install command to access them remotely from a web page. Part 2 explains how in theory a regression discontinuity analysis can identify an average effect of treatment for a population and how different types of regression discontinuity analyses sharp versus fuzzy can identify average. How to do regression discontinuity and interpret results. Mar 07, 2020 for software and implementation details see. Second, we investigate the changes in density distributions over purchase years. A guide to practice, imbens and lemieux, journal of econometrics 2008.
Regression discontinuity rd analysis is a rigorous nonexperimental approach that can be used to estimate program impacts in situations in which candidates are selected for treatment based on whether their value for a numeric rating exceeds a designated threshold or cutpoint. Misunderstandings about the regression discontinuity. It can be used in cases where treatment is assigned based on a cutoff value of a running variable. Rddtools is a new r package under development, designed to offer a set of tools to run all the steps required for a regression discontinuity design rdd analysis, from primary data visualisation to discontinuity estimation, sensitivity and placebo testing.
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