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
 
- Event
- 
                Geistige Schöpfung
 
- (who)
- 
                Lee, Sokbae
 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
- 
                
                    
                        10.03.2025, 11:42 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
- Lee, Sokbae
- Salanié, Bernard
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2018
