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Matching techniques

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When can we use matching?
What if the assignment to the treatment is not done randomly or based on an eligibility index, but on the basis of observable variables?
This is when matching methods come in! Matching methods allow you to construct comparison groups when the assignment to the treatment (or the take-up of treatment) can be modeled on the basis of observable variables.
When can we use matching?
Intuition: the comparison group needs to be as similar as possible to the treatment group, in terms of the observables before the start of the treatment. Avoids possible “confounders” from imbalance in observables. The method assumes there are no ‘remaining’ unobservable differences between treatment and comparison groups.
Key Question
What is the effect of treatment when the assignment to the treatment is based on observable variables?
Unconfoundedness & Selection on observables
Let X denote a matrix in which each row is a vector of pre-treatment observable variables for individual i.
Unconfoundedness: Assignment to treatment is unconfounded given pre-treatment variables X if
Y 1, Y0  D | X
Unconfoundedness is equivalent to saying that: (1) within each cell defined by X: treatment is random (2) the selection into treatment depends only on the observables X.
Average effects of treatment
Assuming unconfoundedness given X
Intuition
o Estimate the treatment effect within each cell defined by X o Take the weighted average over the different cells
In your handouts: Annex 1
Math


Full Text
Title Matching techniques
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Material Type Proceedings
Author(English)

Beath, Andrew; Trias, Julieta

Publisher

[Washington, DC]:The World Bank

Date 2012
Event

The Regional Impact Evaluation Workshop

Series Title; No Technical Track Session
Pages 32
Language English
File Type Documents
Original Format pdf
Subject Official Aid < Others
Holding KDI; KDI School

User Note

These slides constitute supporting material to the Impact Evaluation in Practice Handbook : Gertler, P. J.; Martinez, S., Premand, P., Rawlings, L. B. and Christel M. J. Vermeersch, 2010, Impact Evaluation in Practice: Ancillary Material, The World Bank, Washington DC (www.worldbank.org/ieinpractice). The content of this presentation reflects the views of the authors and not necessarily those of the World Bank.

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