Difference between revisions of "Regression Discontinuity"

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Regression Discontinuity is a quasi-experimental impact evaluation design which attempts to find the causal effects of interventions by assigning a threshold above and below which the treatment is assigned. Observations closely on either side of the threshold are compared to estimate the average treatment effect.  
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Regression Discontinuity is a quasi-experimental impact evaluation design which attempts to find the causal effects of interventions by assigning a threshold(cut off point) above and below which the treatment is assigned. Observations closely on either side of the threshold are compared to estimate the average treatment effect.  
  
 
== Read First ==
 
== Read First ==

Revision as of 19:18, 2 February 2017

Regression Discontinuity is a quasi-experimental impact evaluation design which attempts to find the causal effects of interventions by assigning a threshold(cut off point) above and below which the treatment is assigned. Observations closely on either side of the threshold are compared to estimate the average treatment effect.

Read First


Types of RD

Sharp RD

Sharp regression discontinuity designs are designs where the cut off point perfect predicts whether the subject(individual, groups, etc) becomes treatment or control.

Examples from DIME portfolio of sharp RD

Fuzzy RD

A fuzzy RD design is a design where the cutoff point does not completely separate the controls and treatments. Some people who should be in the treatment might not be in treatment and some people who should be in the control group could be in the treatment group.

Examples from DIME portfolio of fuzzy RD

Choosing the right bin width

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This article is part of the topic Impact Evaluation Design

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