Jul 07, 2017 this video provides an introduction to regression discontinuity analysis. Including covariates in the local linear regression setting is also specifically warned against in the stata rd module used to implement the regression discontinuity estimator see nichols, 2011. Stata module for regression discontinuity estimation. Software demonstrations will use stata, but r code will also be included for participants who are using r for their research projects. External validity in fuzzy regression discontinuity designs marinho bertanha and guido w. I am running a fuzzy regression discontinuity rd design in stata and i am having doubts about whether i am specifying my regressions correctly. Regression discontinuity design regression discontinuity rdd is a research design for the purposes of causal inference. An intuitive introduction to regression discontinuity youtube. The advantages of regression discontinuity design over alternative research designs. An r package for robust nonparametric inference in regressiondiscontinuity designs, r journal 71. 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 is a binary variable 1drop out, 0 didnt drop out. To estimate the effect of education on euroscepticism, we use fuzzy rds with an. Willett this is one of the books available for loan from academic technology services see statistics books for loan for.
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. A regression discontinuity design using compulsory schooling reforms in four. There has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. Willett this is one of the books available for loan from academic technology services see statistics books for loan for other such books, and details about borrowing. Software for regressiondiscontinuity designs matias d. The rdrobust package provides stata and r implementations of. 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. Discontinuity design relative to an otherwise comparable randomized. Robust datadriven inference in the regression discontinuity design, stata journal 144.
Velke karlovice, czech republic fuzzy linear regression analysis jana nowakov. In this article, we describe a major upgrade to the stata and r software package. Local linear regression is used to construct point estimates. 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. The regression discontinuity rd design is widely used in applied work. My running variable is age and the cutoff point differs by gender. Regression discontinuity designs for evaluating programs and.
Robust inference in fuzzy regression discontinuity designs yang he november 2, 2017 abstract fuzzy regression discontinuity rd design and instrumental variables iv regression share similar identi cation strategies and numerically yield the same results under certain conditions. It is one of the most credible quasiexperimental research designs for identi. Thus far, it has been implicitly assumed that all sample units comply with their treatment assignments, that is, that all treatments and no controls receive intervention services. In my case the conventional differs in sign and size from the other two. This video provides an introduction to regression discontinuity analysis.
While the weak identi cation problem is widely recognized in iv. Lee and thomas lemieux this paper provides an introduction and user guide to regression discontinuity rd designs for empirical researchers. In this case, we implement the fuzzy regression discontinuity. It would seem that employing a regression discontinuity design would be appropriate given the cutoff point and jump in the data.
Basic idea is that the assignment to the treatment is going to be. It presents the basic theory behind the research design, details when rd is likely to be valid or invalid given economic incentives. Using a fuzzy regression discontinuity design in close mixed gender races for the election of mayors in italian municipalities in the period 20002015, we find that female mayors collect more. More specifically, this command gives a conventional coefficient, a biascorrected one, and a robust one. We investigate the choice of the bandwidth for the regression discontinuity estimator. An r package for robust nonparametric inference in regression discontinuity designs, r journal 71. Regression discontinuity world bank sief aphrc impact. Plot for a fuzzy regression discontinuity design 15 oct 2019, 14.
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. It is one of the best quasiexperimental research designs for identi cation, estimation and inference of treatment e ects local to the cuto. This video is part of a project at the univeristy of amsterdam in which instruction videos were produced to supplement a. An intuitive introduction to regression discontinuity. Robust datadriven inference in the regressiondiscontinuity design sebastian calonico, matias d. 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. It can be obtained using the lowess command in stata. Rdd is one of the most powerful tools in the suite of quasiexperimental methods used to capture causal effects of programs and policies. Regression discontinuity designs for evaluating programs and policies. Regression discontinuity designs in economics david s. Estimating the fuzzy regression discontinuity design model when subjects are not compliant with treatment intent.
The iv characterization of the fuzzy rd design is useful but it is not how one should evaluate whether the method can be extended to other. Regression discontinuity \rd stata section we will use a new dataset. C14 abstract many empirical studies use fuzzy regression discontinuity frd designs to identify treatment effects when the receipt of treatment is potentially correlated to outcomes. We focus on estimation by local linear regression, which was shown to have attractive properties porter, j. The rdrobust package provides stata and r implementations of statistical inference and graphical procedures for regression discontinuity designs employing local polynomial and partitioning methods. In this video i give you a prototypical situation where rd. Within the causal inference framework, this design is considered among the most credible nonexperimental strategies because it relies on relatively weak and easy. Plot for a fuzzy regression discontinuity design statalist. 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 design in stata part 1 stata daily. The stata journal analysis of regression discontinuity. Robust datadriven inference in the regressiondiscontinuity design, stata journal 144. Journal of econometrics, 1422, february 2008, pages 698. The wwc continues to refine its processes, develop new standards, and create new products. You can find an intro to the command in cattaneo, calonico, and titiuniks stata journal paper robust datadriven inference in the regression discontinuity design. External validity in fuzzy regression discontinuity designs. The main new features of this upgraded version are as follows. When the circumstances are right, regression discontinuity can be an excellent way to extract causal estimates from observational data. 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. Many empirical studies use fuzzy regression discontinuity frd designs to identify treatment effects when the receipt of treatment is potentially correlated to outcomes. You can find an intro to the command in cattaneo, calonico, and titiuniks stata journal paper robust datadriven inference in the regressiondiscontinuity design. Local linear regressions are performed to either side of the cutpoint using the imbenskalyanaraman optimal bandwidth calculation, ikbandwidth.
A practical guide to regression discontinuity mdrc. Regression discontinuity designs for evaluating programs. 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. Regression discontinuity design in stata part 1 stata.
Polynomials should not be used in regression discontinuity designs. First, we present rdrobust, a command that implements the robust biascorrected confidence intervals proposed in calonico, cattaneo, and titiunik 2014d, econometrica 82. Apr 20, 2020 for software and implementation details see. Manipulation of the running variable in the regression discontinuity design. Problem with optimal bandwidth selection for fuzzy regression discontinuity design. For example, perhaps students in a school take a test in 8th grade. You may also be interested in our propensity score analysis workshop register overview. Problem with optimal bandwidth selection for fuzzy regression. These commands employ the stata and r package rdrobust for plotting, estimation, and inference. Companion r functions with the same syntax and capabilities are provided. Notes for matlab and stata regression discontinuity software. Cattaneo, and rocio titiunik the stata journal 2014 14. Improving causal inference in educational and social science research by richard j. In this article, we introduce three commands to conduct robust datadriven statistical inference in regressiondiscontinuity rd designs.
Regression discontinuity notes for matlab and stata regression discontinuity software. A practical introduction to regression discontinuity designs arxiv. Rdestimate supports both sharp and fuzzy rdd utilizing the aer package for 2sls regression under the fuzzy design. Robust inference in fuzzy regression discontinuity designs. Rd designs are also easy to present, interpret and falsify, features that have contributed to their popularity among. Austin nichols simulation results indicate that the marginal effects may be less sensitive than the latent index function parameters to biprobit assumption violations. Jan 30, 2015 when the circumstances are right, regression discontinuity can be an excellent way to extract causal estimates from observational data. 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. It can be used in cases where treatment is assigned based on a cutoff value of a running variable.
Both implemented in r and stata with the rdrobust package. The stata and r package rdmulti complements several recent software. Polynomials should not be used in regression discontinuity designs \we argue that estimators for causal e ects based on higher order. 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. Existing frd methods identify the local average treatment effect late on the subpopulation of compliers with values of the forcing variable that are equal to the threshold. Robust datadriven inference in the regressiondiscontinuity. Stata code and data for all examples will be available on chalk. This workshop provides an introduction to the practical application of regression discontinuity design in evaluating programs and policies. Estimating causal effects using a regressiondiscontinuity approach stata textbook examples. The regression discontinuity rd design is widely used in economics and other social, behavioral, biomedical, and statistical sciences.
The regressiondiscontinuity rd design is widely used in applied work. R and stata software, replication codes, and other supplementary materials, are avail. 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. 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.