Arbeitspapier
Identifying effects of multivalued treatments
Multivalued treatment models have typically been studied under restrictive assumptions: ordered choice, and more recently unordered monotonicity. We show how treatment effects can be identified in a more general class of models that allows for multidimensional unobserved heterogeneity. Our results rely on two main assumptions: treatment assignment must be a measurable function of threshold-crossing rules, and enough continuous instruments must be available. We illustrate our approach for several classes of models.
- Language
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Englisch
- Bibliographic citation
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Series: cemmap working paper ; No. CWP34/18
- Classification
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Wirtschaft
- Subject
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Identification
selection
multivalued treatments
instruments
monotonicity
multidimensional unobserved heterogeneity
- Event
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Geistige Schöpfung
- (who)
-
Lee, Sokbae
Salanié, Bernard
- Event
-
Veröffentlichung
- (who)
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Centre for Microdata Methods and Practice (cemmap)
- (where)
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London
- (when)
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2018
- DOI
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doi:10.1920/wp.cem.2018.3418
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the 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
- Lee, Sokbae
- Salanié, Bernard
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2018
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