Sharp regression discontinuity design examples incumbency advantage j. Multidimensional regression discontinuity and regression. Notes for matlab and stata regression discontinuity software. Regression discontinuity designs in stata matias d.
Stata code and data for all examples will be available on chalk. The rdrobust package provides stata and r implementations of statistical inference and graphical procedures for regression discontinuity designs employing local polynomial and partitioning methods. An r package for robust nonparametric inference in regressiondiscontinuity designs. We introduce the \textttstata and \textttr package \textttrdmulti, which includes three commands \textttrdmc, \textttrdmcplot. Regression discontinuity rd analysis is a rigorous nonexperimental1 approach that can be. Stata module for regression discontinuity estimation request. Variancepxq erpx i xqpx i xs epx i 2q x 2 we subtract off x2 just for scaling purposes. The stata journal analysis of regression discontinuity. So for a given row if the the date variable has a date of 10mar2018 and the time var has a value of 12. Age changes the probability of having health insurance fuzzy design. Rd relies on regression, yet rd identication is distinct.
By comparing observations lying closely on either side of the threshold, it is possible. Introduction to regression discontinuity designs in economics thomas lemieux, ubc spring course in labor econometrics university of coimbra, march 18 2011. Regression discontinuity design in stata part 1 stata. 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. 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. How imprecise control over ratings affects the distribution of. Heapinginduced bias in regressiondiscontinuity designs. The basic idea of regression discontinuity design rdd is the following. Polynomials should not be used in regression discontinuity designs \we argue that estimators for causal e. It can be obtained using the lowess command in stata.
Graphs in regression discontinuity design in stata or r. We use elections data in which a large number of ties in vote counts between candidates are resolved via a lottery to study the personal incumbency advantage. There will be units with the same values of the controls matches but with di. Understanding society 20092018 for ghq and sf12 mental health. Regression discontinuity designs in economics, lee and lemiux, jel 2010. Joe wadding presented this 50minute talk at the university of kentucky on regression discontinuity, the first presentation in the fall 2017 applied quantitative and. A practical guide to regression discontinuity mdrc. 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. This video explains how economists use regression discontinuity to establish causality. C14 abstract we investigate the problem of optimal choice of the smoothing parameter bandwidth for the regression discontinuity. Manipulation of the running variable in the regression discontinuity design. C14,c21,i12 abstract this study uses monte carlo simulations to demonstrate that regression discontinuity designs arrive. Regression discontinuity design university of colorado denver. Stata module for regression discontinuity estimation.
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. Stata module for regression discontinuity estimation rd. Stores the last performed regression as one of the model specifications spec1 to be displayed in the table. Regressiondiscontinuity design with tenpoint treatment effect. However,unliketrueexperiments,thedatausedinnaturalexperiments comefromnaturally. 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. Regression discontinuity in practice 2 the usual practice is. Regression discontinuity and practical applications.
The regression discontinuity rd design is widely used in applied work. The important part is epx2 i q often, x 0 in which case varpxq epx2 i q. 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. Regression discontinuity d esign 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. Optimal bandwidth choice for the regression discontinuity estimator guido imbens and karthik kalyanaraman nber working paper no. Openingsaving a stata datafile quick way of finding variables subsetting using conditional if stata color coding system from spsssas to stata example of a dataset in excel from excel to stata copyandpaste. Regression discontinuity designs in economics david s. Analysis of regression discontinuity designs with multiple cutoffs. Data analysis with stata 12 tutorial university of texas. Propensity score matching regression discontinuity limited.
Manipulation of the running variable in the regression discontinuity. Regression discontinuity limited dependent variables christopher f baum ec 823. We are grateful to professors murname and willett for granting us permission to distribute the data files from his book via our web site as well as providing. Identification and estimation of treatment effects with a. Regression discontinuity design page center for effective global action university of california, berkeley 6 this provides a good example of the usefulness of loops in stata code. The data should look something like this in stata we can think about estimating the end of the red line and the. Introduction given a running variable x, a threshold c, a treatment indicator t, and an outcome y, regression discontinuity rd models identify.
It presents the basic theory behind the research design, details when rd is likely to be valid or invalid given economic incentives. Is there a way in stata to export just a regression with the margin tests beneath it, or is there another. In regression matching we hope that treatment is as good as randomly assigned after conditioning on controls. How to do regression discontinuity and interpret results in stata 16 oct 2017, 17. Heapinginduced bias in regressiondiscontinuity designs alan i. It is one of the most credible quasiexperimental research designs for identi. Propensity score matching basic mechanics of matching to estimate the propensity score, a logit or probit model is usually employed. Figure 2 is identical to figure 1 except that all points to the left of the cutoff i. 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 world bank sief aphrc impact. Stata is a software package popular in the social sciences for manipulating and summarizing data and.
Default is sharp rd design and hence this option is not used. A practical introduction to regression discontinuity designs. This work was supported by the national science foundation. Optimal bandwidth choice for the regression discontinuity. In this guide for practitioners, we discuss several features of this \ regression discontinuity in time rdit framework that di er from the more standard. Regression discontinuity design rdd in the rdd the assignment to treatment is not random, but determined at least partly by the value of an observed covariate. Local linear regression is used to construct point estimates. Justin mccrary university of michigan december 2006 abstract standard su. Polynomials should not be used in regression discontinuity designs \we argue that estimators for causal e ects based on higher order. Manipulation of the running variable in the regression. In this element and its accompanying element, matias d.
Regression discontinuity design rdd in brief this method was developed to estimate treatment e. Ceo regression discontinuity design rdd checklist study. 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. Plan of the three lectures on regression discontinuity designs. See where to buy books for tips on different places you can buy these books. It provides point estimators, confidence intervals estimators, bandwidth selectors, automatic rd plots, and other related features. Regression discontinuity \rd stata section we will use a new dataset.
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