Treatment Effects Using Inverse Probability Weighting and Contaminated Treatment Data An Application to the Evaluation of a Government Female Sterilization Campaign in Peru
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Cited by:
- Leon-Ciliotta, Gianmarco & Zejcirovic, Dijana & Fernández Bazán, Fernando, 2022.
"Policy-Making, Trust and the Demand for Public Services: Evidence from a Mass Sterilizations Campaign,"
CEPR Discussion Papers
17361, C.E.P.R. Discussion Papers.
- Gianmarco León-Ciliotta & Dijana Zejcirovic & Fernando Fernandez, 2022. "Policy-Making, Trust and the Demand for Public Services: Evidence from a Mass Sterilization Campaign," Working Papers 1352, Barcelona School of Economics.
- Akanksha Negi & Digvijay Singh Negi, 2022. "Difference-in-Differences with a Misclassified Treatment," Papers 2208.02412, arXiv.org.
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More about this item
Keywords
female sterilization; fertility; family planning; contaminated data models; inverse probability weighting; casual effects; observational data;All these keywords.
JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
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