Arbeitspapier

Heterogeneous coefficients, control variables, and identification of 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 generalized propensity scores (Imbens, 2000) are bounded away from zero with probability one, a simple identification condition is that their sum be bounded away from one with probability one. These results generalize the classical identification result of Rosenbaum and Rubin (1983) for binary treatments.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP45/20

Klassifikation
Wirtschaft
Thema
Treatment effect
Multiple treatments
Heterogeneous coefficients
Control variable
Identification
Conditional nonsingularity
Propensity score

Ereignis
Geistige Schöpfung
(wer)
Newey, Whitney K.
Stouli, Sami
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2020

DOI
doi:10.47004/wp.cem.2020.4520
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Newey, Whitney K.
  • Stouli, Sami
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2020

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