Nonparametric regression, like linear regression, estimates mean outcomes for. Then, the average value of the outcome variable can be computed for each bin. The regression discontinuity rd design is widely used in applied work. Notes for matlab and stata regression discontinuity software. This is a long shot, but take a look at example 55.
Although the growth of rd designs has stimulated a wide discussion about rd assumptions and estimation strategies, there is no single shared approach. Trouble producing a regression discontinuity graph. The rddensity package provides stata and r implementations of manipulation tests employing local polynomial density estimation methods. We are here to help, but wont do your homework or help you pirate software. It is one of the most credible quasiexperimental research designs for identi. 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. Weights give more importances to observations close to data point predicted y, y, is then the \smoothed y i. During the last decade, an increasing number of political scientists have turned to regressiondiscontinuity rd designs to estimate causal effects. Rd plots, estimation, inference, and extrapolation with multiple cutoffs and multiple scores. For example, if the assignment variable z follows a uniform distribution over the range 0, 10, patients who are randomly assigned a value of z of. Stata makes it very easy to create a scatterplot and regression line using the graph twoway command.
Regression discontinuity design in stata part 1 stata. I am running a fuzzy regression discontinuity design using 2sls. You might want to take a look at rdrobust calonico, s. Plan of the three lectures on regression discontinuity designs. Computationally intensive one regression per data point for each data point, run a weighted linear regression linear or polynomials on x using all the observations within a window. Press question mark to learn the rest of the keyboard shortcuts.
Note, that both have the raw data along with the fitted lines in the plots. Nonparametric regression is similar to linear regression, poisson regression, and logit or probit regression. I am basing everything on a single graph, presented at the end of the example, that looks something like what i would expect from a regression discontinuity. It can be used in cases where treatment is assigned based on a cutoff value of a running variable. Regression discontinuity rd design is a sophisticated quasiexperimental approach used for inferring causal relationships and estimating treatment effects.
Lee and thomas lemieux this paper provides an introduction and user guide to regression discontinuity rd designs for empirical researchers. Robust datadriven inference in the regression discontinuity design, stata journal 144. Recent advances and applications the main reference for the lectures is d. By comparing observations lying closely on either side of the threshold, it is possible. Stata module for regression discontinuity estimation. On april 23, 2014, statalist moved from an email list to a forum. The running variable is age and the two cutoff points are at 60. Regression discontinuity design regression discontinuity rdd is a research design for the purposes of causal inference. You can record those changes to create a style that can be applie. If you work with the parametric models mentioned above or other models that predict means, you already understand nonparametric regression and can work with it. Local linear regression is used to construct point estimates.
Having seen how to make these separately, we can overlay them into one graph as shown below. An r package for robust nonparametric inference in regressiondiscontinuity designs, r journal 71. Regression discontinuity world bank sief aphrc impact. Regression discontinuity for causal effect estimation in. The regressiondiscontinuity rd design is widely used in applied work. Regression discontinuity designs in economics david s. Graphical presentation of regression discontinuity results. There has been a growing use of regression discontinuity design rdd, introduced by thistlewaite and campbell 1960, in evaluating impacts of development programs. How to graph a tendency line in a discontinuous regression. Stata news, code tips and tricks, questions, and discussion. Graphs in regression discontinuity design in stata or r. 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 stata section we will use a new dataset.
Estimating causal effects using a regressiondiscontinuity approach stata textbook examples. 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 plot with confidence intervals i am trying to build an rd plot but in order to make it more easily readable i would like to add confidence intervals, since in some cases it seems there is a discontinuity but it is non significant. For example, perhaps students in a school take a test in 8th grade. Improving causal inference in educational and social science research by richard j. However, i think both of these didnt implement the step 1. The difference to the usual case is that im considering not just one but two cutoff pointsdiscontinuities. Regression discontinuity notes for matlab and stata regression discontinuity software. In particular, their rdplot has eight different methods to select the optimal number of bins depending on the type of partitioning scheme and the spacing or polynomial regression estimators used. 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. Robust datadriven inference in the regressiondiscontinuity design, stata journal 144. Sample graph without confidence variable lee and lemieux,2009 thank you in advance. Trouble producing a regression discontinuity graph with a specified bandwidth.
We thank stephane bonhomme, david drukker, kosuke imai, michael jansson, lutz kilian, pat kline, xinwei. 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. I need to show a scatter plot of a time series variable that is static in every year the plot is actually a bunch of vertical lines. When the assignment variable is a random number that is generated by the researcher, the regression discontinuity design is equivalent to a randomized controlled trial. How can i do a scatterplot with regression line in stata. Find out how to point and click to make changes to your stata graph using the graph editor. Package rdd march 14, 2016 maintainer drew dimmery author drew dimmery version 0.
An r package for robust nonparametric inference in regression discontinuity designs, r journal 71. If i specified the model and most importantly the ivs correctly as i have never worked on a rdd before. We can likewise show a graph showing the predicted values of write by read as shown below. The function doesnt follow any given parametric form, like being. In the statalist archives i found this earlier suggestion by austin nichols. Stata version 15 now includes a command npregress, which fits a smooth function to predict your dependent variable endogenous variable, or outcome using your independent variables exogenous variables or predictors. 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. Randomized controlled trials in a regression discontinuity framework. 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. Statistical software components from boston college department of economics. Regression discontinuity plot with confidence intervals.