Is there a statistical test that would allow me to test whether i should use a sharp or fuzzy regression discontinuity design. 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. Do you know where to access any stata data set that is at least describes something similar to what i am looking for. There are a bunch of theoretical articles, but not that many that seems to explain how to im. We use a regression discontinuity design taking advantage of the fact that the spanish 2010 and 2012 vat reforms had a sharp implementation date, which implies that from one day to another the tax. Optimal datadriven regression discontinuity plots, with sebastian calonico and rocio titiunik. The sharp rd design is a special case of the fuzzy rd design, since the denominator in the sharp case is just one. 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. Notes for matlab and stata regression discontinuity software. I mean for getting the graphs and carrying out the local regression. Stata module to perform sharp regression discontinuity design with cross validation. In this case, assignment to treatment depends on a single variable x i.
Regression discontinuity design rdd using stata statalist. A practical introduction to regression discontinuity. This is what is referred to as a sharp regression discontinuity. 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. Discontinuity design relative to an otherwise comparable randomized. Although it seems there are specific command such as rd that can be used to apply rdd, i was told that rdd could be carried out using just regular regression model, which in my case it would be logistic model i suppose because the outcome i am interested. In this element and its accompanying second element, a practical introduction to regression discontinuity designs. Jan 30, 2015 when the circumstances are right, regression discontinuity can be an excellent way to extract causal estimates from observational data. Posttest scores in the treatment group are better predicted by a new regression line than the regression line of the comparison group. Statistical test whether to use sharp or fuzzy regression. Stata module to perform sharp regression discontinuity design with cross validation bandwidth selection, statistical software components s457908, boston college department of economics, revised 07 nov 2015. Oct 14, 20 hello expert sas users, im in the midst of doing some srd analysis sharp regression discontinuity in sas. An intuitive introduction to regression discontinuity youtube.
Is there a command for running a regression discontinuity desgin in stata. This video explains how economists use regression discontinuity to establish causality. In this design, units receive treatment on the basis of whether. In this article, we describe a major upgrade to the stata and r software package rdrobust. The regression discontinuity rd design is widely used in economics and other social, behavioral, biomedical, and statistical sciences. Local linear regressions are performed to either side of the cutpoint using the imbenskalyanaraman optimal bandwidth calculation, ikbandwidth. Within the causal inference framework, this design is considered among the most credible nonexperimental strategies because it relies on relatively weak and easy. Polynomials should not be used in regression discontinuity.
Journal of the american statistical association 110512. The idea behind the sharp regression discontinuity srd design is that the treatment wi is determined solely by the value of the forcing variable xi being on either side of a. Setting \ code deriv 1 results in estimation of a kink rd design up to scale, or. Ceo regression discontinuity design rdd checklist study. Hello everybody, i have a big problem in computing a sharp regression discontinuity design via the rd function. Regression discontinuity design in stata part 1 stata daily. Cuto point increases the probability of treatment but doesnt completeley determines treatment. The rdrobust package provides stata and r implementations of statistical inference and graphical procedures for regression discontinuity designs employing local polynomial and partitioning methods. 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. Software for regressiondiscontinuity designs we describe a major upgrade to the stata. It provides point estimators, confidence intervals estimators, bandwidth selectors, automatic rd plots, and other related features. Robust datadriven inference in the regression discontinuity design, stata journal 144. Rd designs are also easy to present, interpret and falsify, features that have contributed to their popularity among. Sharp regression discontinuity design identi cation sharp regression discontinuity design assignment to the scholarship treatment d i is completely determined by the value of the sat score x i being on either side of the threshold c.
A practical guide to regression discontinuity mdrc. Software demonstrations will use stata, but r code will also be included for participants who are using r for their research projects. How to do regression discontinuity and interpret results in. The technique is still somewhat rare, so ive had significant problems finding textbook examples. 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.
Regression discontinuity designs for evaluating programs. 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. Default is sharp rd design and hence this option is not used. R and stata software, replication codes, and other supplementary materials, are avail.
This command implements estimation of sharp regression. Inference in regression discontinuity designs under local randomization, with rocio titiunik and gonzalo vazquezbare. 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. Optimal bandwidth choice for the regression discontinuity. C1,h0,i0,j0 abstract this paper provides an introduction and user guide to regression discontinuity rd designs for empirical researchers. Panel data and regression discontinuity designs due wednesday, december 5 1.
Regression discontinuity rd designs, sharp discontinuity. Design with cross validation bandwidth selection, statistical software. Journal of econometrics, 1422, february 2008, pages 698. Regression discontinuity designs for evaluating programs and policies. It is one of the best quasiexperimental research designs for identi cation, estimation and inference of treatment e ects local to the cuto.
Help finding stata dataset for sharp regression discontinuity design. The main new features of this upgraded version are as follows. Capital punishment and crime iii in problem set 4, you analyzed the association between capital punishment and crime in firstdifferences. Sharp regression discontinuity srd design report provides a graphical depiction of the data using the average value or weighted average value, using, for example, kernel weights of the outcome variable within bins defined by ranges of the forcing variable. The data should look something like this in stata we can think about estimating the end of the red line and the. Regression discontinuity designs in economics david s.
Regression discontinuity world bank sief aphrc impact. Austin nichols simulation results indicate that the marginal effects may be less sensitive than the latent index function parameters to biprobit assumption violations. The regression discontinuity design can be thought of as an extension of instrumental variable analysis, in circumstances where an exogenous source of variation arises from a continuously measured random variable that at least partially assigns treatment or other exposure based on a. Rdestimate supports both sharp and fuzzy rdd utilizing the aer package for 2sls regression under the fuzzy design.
Users of any of the software, ideas, data, or other materials published in the stata journal or the supporting. You can find an intro to the command in cattaneo, calonico, and titiuniks stata journal paper robust datadriven inference in the regressiondiscontinuity design. Oct 16, 2017 how to do regression discontinuity and interpret results in stata 16 oct 2017, 17. Throughout, we focus on the case of a sharp rd design. The regression discontinuity rd design is widely used in applied work.
Local linear regression is used to construct point estimates. 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. Which brings us back to the world of instrumental variables. Checking the assumptions of regression discontinuity designs. Can be either a statistically significant change in slope or y. Robust datadriven inference in the regression discontinuity design.
Stata module to perform sharp regression discontinuity. For example, perhaps students in a school take a test in 8th grade. 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. Ahmad mohassel senior economist kimetrica linkedin. A practical introduction to regression discontinuity designs. Regression discontinuity design in stata part 1 stata. Stata module to perform sharp regression discontinuity design with cross validation bandwidth selection. A key feature of this design is that the variable c. Assignment or running variable completely determines treatment. Stata module to perform sharp regression discontinuity design with cross.
This package allows their inclusion, but cautions against them insomuch as is possible. Regression discontinuity design regression discontinuity rdd is a research design for the purposes of causal inference. This command implements estimation of sharp regression discontinuity designs. Extensions, matias cattaneo, nicolas idrobo, and roc. Software for regressiondiscontinuity designs matias d. An r package for robust nonparametric inference in regression discontinuity designs, r journal 71. It can be used in cases where treatment is assigned based on a cutoff value of a running variable. In a sharp design, individuals are treated when their running variable exceeds their corresponding cuto, d i 1 x i c i. We focus on estimation by local linear regression, which was shown to have attractive properties porter, j. Hello expert sas users, im in the midst of doing some srd analysis sharp regression discontinuity in sas. Sharp regression discontinuity example and limitations.
In section 5 we extend the srd setup to the case with additional covariates and to the fuzzy. Dec 16, 2015 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. Graphs in regression discontinuity design in stata or r. Estimating the sharp regression discontinuity design model when subjects are compliant with treatment intent estimating the fuzzy regression discontinuity design model when subjects are not compliant with treatment intent making functional form and bandwidth decisions. In the sharp rd design this variable fully determines the treatment according to the cuto. Im thinking of a sharp regression discontinuity design as a first step. In this video i give you a prototypical situation where rd. The key to the rd design is that we have a deep understanding of. The regression discontinuity design in social science. Imbenswooldridge, lecture notes 3, nber, summer 07 4 of democrats winning the subsequent election, comparing districts where the democrats won the previous election with just over 50% of the popular vote with districts where the democrats lost the previous election with just under 50% of the vote. In the rd design, the cutoff is the treatment assignment, so to make it. Once we control for a confounder x i, treatment assignment is as good as random. 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 regression discontinuity designs. A standard way of graphing the data is to divide the assignment variabled here into a number of bins, making sure there are two separate bins on each side of the cutoff point to avoid having treated and untreated observations mixed together in the same bin.
Education for college students using a regression discontinuity design. The key to the rd design is that we have a deep understanding of the mechanism which underlies the assignment of treatment d i. This workshop provides an introduction to the practical application of regression discontinuity design in evaluating programs and policies. Statistical software components from boston college department of economics. The stata journal analysis of regression discontinuity.
This is a readonly mirror of the cran r package repository. Regression discontinuity design in stata part 1 there has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. This session will provide an applied introduction to both sharp and fuzzy regression discontinuity designs rdd, discuss issues. In this element, the authors discuss the foundations of the canonical sharp rd design, which has the following features. We investigate the choice of the bandwidth for the regression discontinuity estimator. Default is \ code deriv 0 for sharp rd, or for fuzzy rd if \ code fuzzy is also specified. 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. Covariates are problematic for inclusion in the regression discontinuity design. Stata code and data for all examples will be available on chalk.
If nonedur is the individual outcome variable and tenure is the assignment variable, and treatment jumps discontinuously from zero to one at tenure1094 36 mos, then you should be using the twovariable syntax as elaborated in the stata journal article linked from rds help file. This work was supported by the national science foundation. Regression discontinuity rd designs with multiple cuto s or multiple scores are com. I have used models including linear regression, logistic regression, instrumental variable, propensity score matching, regression discontinuity design and panel data methods such as fixed effects. A jump in the probability of treatment before and after cuto point. Stata module for regression discontinuity estimation request. The regressiondiscontinuity rd design is widely used in applied work.
Stata module for regression discontinuity estimation rd. Estimating the sharp regression discontinuity design model. Regression discontinuity rd analysis is a rigorous nonexperimental 1 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. You may also be interested in our propensity score analysis workshop register overview. Regression discontinuity designs for evaluating programs and. This command implements estimation of sharp regression discontinuity designs using a flexible crossvalidation cv procedure for optimal bandwidth selection. Regression discontinuity for causal effect estimation in.
Manipulation of the running variable in the regression discontinuity design. Mar 07, 2020 for software and implementation details see. This precludes placing electronic copies of the stata journal, in whole or in part, on publicly accessible web sites. Stata module for regression discontinuity estimation. Stata module to perform sharp regression discontinuity design with cross validation bandwidth selection, statistical software components s457908, boston. It is one of the most credible quasiexperimental research designs for identi.
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