Multiple discrete endogenous variables in weakly-separable triangular models

Artikel

We consider a model in which an outcome depends on two discrete treatment variables, where one treatment is given before the other. We formulate a three-equation triangular system with weak separability conditions. Without assuming assignment is random, we establish the identification of an average structural function using two-step matching. We also consider decomposing the effect of the first treatment into direct and indirect effects, which are shown to be identified by the proposed methodology. We allow for both of the treatment variables to be non-binary and do not appeal to an identification-at-infinity argument.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 4 ; Year: 2016 ; Issue: 1 ; Pages: 1-21 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Econometrics ; Semiparametric and Nonparametric Methods: General ; Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
• Thema: nonparametric identification ; discrete endogenous regressors ; triangular models

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Jun, Sung Jae ; Pinkse, Joris ; Xu, Haiqing ; Yıldız, Neşe
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2016

Weitere Informationen

• DOI: doi:10.3390/econometrics4010007
• Handle: http://hdl.handle.net/10419/171862
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ