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
-
Englisch
- Bibliographic citation
-
Series: cemmap working paper ; No. CWP34/18
Classification
Wirtschaft
Subject
Identification
selection
multivalued treatments
instruments
monotonicity
multidimensional unobserved heterogeneity
selection
multivalued treatments
instruments
monotonicity
multidimensional unobserved heterogeneity
Event
Geistige Schöpfung
(who)
Lee, Sokbae
Salanié, Bernard
Salanié, Bernard
Event
Veröffentlichung
(who)
Centre for Microdata Methods and Practice (cemmap)
(where)
London
(when)
2018
- DOI
-
doi:10.1920/wp.cem.2018.3418
- Handle
- Last update
-
20.09.2024, 8:24 AM CEST
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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