Using the regression discontinuity design with implicit partitions: The impacts of comunidades solidarias rurales on schooling in El Salvador
Regression discontinuity design (RDD) is a useful tool for evaluating programs when a single variable is used to determine program eligibility. RDD has also been used to evaluate programs when eligibility is based on multiple variables that have been aggregated into a single index using explicit, of...
| Main Authors: | , |
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| Format: | Artículo preliminar |
| Language: | Inglés |
| Published: |
International Food Policy Research Institute
2011
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/152610 |
| Summary: | Regression discontinuity design (RDD) is a useful tool for evaluating programs when a single variable is used to determine program eligibility. RDD has also been used to evaluate programs when eligibility is based on multiple variables that have been aggregated into a single index using explicit, often arbitrary, weights. In this paper, we show that under specific conditions, regression discontinuity can be used in instances when more than one variable is used to determine eligibility, without assigning explicit weights to map those variables into a single measure. |
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