Arbeitspapier
Heterogeneous coefficients, control variables, and identification of multiple treatment effects
Multidimensional heterogeneity and endogeneity are important features of models with multiple treatments. We consider a heterogeneous coefficients model where the outcome is a linear combination of dummy treatment variables, with each variable representing a different kind of treatment. We use control variables to give necessary and sufficient conditions for identification of average treatment effects. With mutually exclusive treatments we find that, provided the heterogeneous coefficients are mean independent from treatments given the controls, a simple identification condition is that the generalized propensity scores (Imbens, 2000) be bounded away from zero and that their sum be bounded away from one, with probability one. Our analysis extends to distributional and quantile treatment effects, as well as corresponding treatment effects on the treated. These results generalize the classical identification result of Rosenbaum and Rubin (1983) for binary treatments.
- Language
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Englisch
- Bibliographic citation
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Series: cemmap working paper ; No. CWP41/21
- Classification
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Wirtschaft
- Subject
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Treatment effect
Multiple treatments
Heterogeneous coefficients
Control variable
Identification
Conditional nonsingularity
Propensity score
- Event
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Geistige Schöpfung
- (who)
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Newey, Whitney K.
Stouli, Sami
- Event
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Veröffentlichung
- (who)
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Centre for Microdata Methods and Practice (cemmap)
- (where)
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London
- (when)
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2021
- DOI
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doi:10.47004/wp.cem.2021.4121
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Newey, Whitney K.
- Stouli, Sami
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2021
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