Journal of econometrics, 1422, february 2008, pages 698. Recent advances and applications the main reference for the lectures is d. Regression discontinuity world bank sief aphrc impact. In this sense, it is much like an experimental design. Stata module for regression discontinuity estimation. Regression discontinuity designs exploit substantive knowledge that treatment is assigned in a particular way. The command rdmc applies to noncummulative and cummulative multicuto rd settings. Manipulation of the running variable in the regression. 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.
Under stata versions 10 or later using lpoly to construct local regression. 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. The basic rd design is a twogroup pretestposttest model as indicated in the design notation. 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. How to do regression discontinuity and interpret results. Imbens and lemieux 2008 regression discontinuity design. 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.
Statistical software components from boston college department of economics. Stata module to perform regression discontinuity, statistical software components s458238, boston college department of economics. Two companion stata and r software packages are provided. 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. 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. 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.
Polynomials should not be used in regression discontinuity. 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. Second, we investigate the changes in density distributions over purchase years. Plan of the three lectures on regression discontinuity designs. In this video i give you a prototypical situation where rd. 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. Regression discontinuity design in stata part 1 stata daily. Stata module to perform a permutation test for the. It is impossible to definitively test for validity if agents are able to perfectly determine their treatment status. Their insight was that students with a test score just above a scholarship cutoff were plausibly comparable to students whose scores were just below the cutoff, so any differences in future academic. Software for estimation and inference in regression discontinuity designs. A function is also included to test the assumption of nosorting effects. It is one of the most credible quasiexperimental research designs for identi. 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.
An r package for robust nonparametric inference in regression discontinuity designs, r journal 71. Even though researchers do not control the assignment, substantive knowledge about the threshold serves as a basis for a strong identification claim. Software for regressiondiscontinuity designs matias d. 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. There has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. A provided function will utilize imbenskalyanaraman optimal bandwidth calculation. This book is composed of four chapters covering a variety of topics about using stata for regression. For the full sample, i keep observations only within the desired bandwidth and then run the following stata code. The test involves estimation of the discontinuity in the density function of the running variable at the cutoff. 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. 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. 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. How to do regression discontinuity and interpret results in stata 16 oct 2017, 17. The stata journal analysis of regression discontinuity.
A guide to practice, imbens and lemieux, journal of econometrics 2008. Regression discontinuity rdd is a research design for the purposes of causal inference. The latest version of this software, as well as other related software for rd designs. Card, lee, pei, and weber 2012 regression kink design models continuous kinked treatment. See stata and matlab code here code from imbens software page. Lee and thomas lemieux this paper provides an introduction and user guide to regression discontinuity rd designs for empirical researchers. Testing for treatment e ect heterogeneity in regression. The main new features of this upgraded version are as follows.
Regression discontinuity design in stata part 1 stata. Journal of the american statistical association 110512. I am trying to estimate the impact of a social program on intrahousehold labour supply. 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. Rd designs are also easy to present, interpret and falsify, features that have contributed to their popularity among. Discontinuity design relative to an otherwise comparable randomized. Jan 30, 2015 when the circumstances are right, regression discontinuity can be an excellent way to extract causal estimates from observational data.
Improving causal inference in educational and social science research by richard j. Create a regression discontinuity design declaredesign. 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. Robust datadriven inference in the regression discontinuity design, stata journal 144. It can be used in cases where treatment is assigned based on a cutoff value of a running variable. Stata code and data for all examples will be available on chalk. Regressiondiscontinuity analysis research methods knowledge base. Notes for matlab and stata regression discontinuity software. Dear all, i am a freshman and learning regression discontinuity design in recent days. Regression discontinuity rd analysis is a rigorous nonexperimental. In this article, we describe a major upgrade to the stata and r software package.
A guide to practice, imbens and lemiux, journal of econometrics 2008. An intuitive introduction to regression discontinuity youtube. It is one of the best quasiexperimental research designs for identi cation, estimation and inference of treatment e ects local to the cuto. It provides point estimators, confidence intervals estimators, bandwidth selectors, automatic rd plots, and other related features. Misunderstandings about the regression discontinuity. Estimation is accomplished using local linear regression. Manipulation testing based on density discontinuity. 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. Introduction to regression discontinuity rd designs rd designs as local randomized experiments and the manipulation problem. However, there are some tests that can provide evidence that either supports or discounts the validity of the regression discontinuity design. The regressiondiscontinuity rd design is widely used in applied work. Bloom, 2012, a practical guide to regression discontinuity, mdrc, pdf. Command rdplot is a newly developed code by very renowned scholars in this field.
Regression discontinuity and practical applications. Graphs in regression discontinuity design in stata or r. Mar 07, 2020 for software and implementation details see. It presents the basic theory behind the research design, details when rd is likely to be valid or invalid given economic incentives.
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. Regression discontinuity design regression discontinuity rdd is a research design for the purposes of causal inference. Using spss to analyze data from a regression discontinuity design the methods employed here follow the advice found in chapter 11 of trochim, w. The regression discontinuity rd design is widely used in applied work. By analyzing a set of user defined placebo estimates. Justin mccrary university of michigan december 2006 abstract standard su. Testing for treatment effect hetereogeneity in regression. 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. This presentation focused on the theory, design, and implementation of regression discontinuity rdd.
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 work was supported by the national science foundation. 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 module to perform a permutation test for the regression kink rk and regression discontinuity rd design, statistical software. For example, perhaps students in a school take a test in 8th grade. The rdrobust package provides stata and r implementations of statistical inference and graphical procedures for regression discontinuity designs employing local polynomial and partitioning methods. Thistlewhite and campbell introduced the regression discontinuity design in the 1960s to study the impact of scholarships on academic success. Estimating causal effects using a regression discontinuity approach stata textbook examples. A practical guide to regression discontinuity mdrc. 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. Optimal bandwidth choice for the regression discontinuity. Inference in regression discontinuity designs under local randomization, with rocio titiunik and gonzalo vazquezbare. Simple local polynomial density estimators princeton.
All methods are implemented in r and stata software packages. 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. Manipulation of the running variable in the regression discontinuity design. Ab we study regression discontinuity designs when covariates are included in the estimation. A density test, mccrary, journal of econometrics 2008 regression discontinuity designs. 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. Regression discontinuity rd analysis is a rigorous nonexperimental1 approach that can be used to estimate program impacts in situations in which candidates are. 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. How to do regression discontinuity and interpret results in. 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. This work was supported in part by the national science foundation through grants ses57561 and ses1459931. Builds a design with sample from population of size n.
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