Artikel

Multiple discrete endogenous variables in weakly-separable triangular models

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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.

Language
Englisch

Bibliographic citation
Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 4 ; Year: 2016 ; Issue: 1 ; Pages: 1-21 ; Basel: MDPI

Classification
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
Subject
nonparametric identification
discrete endogenous regressors
triangular models

Event
Geistige Schöpfung
(who)
Jun, Sung Jae
Pinkse, Joris
Xu, Haiqing
Yıldız, Neşe
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2016

DOI
doi:10.3390/econometrics4010007
Handle
Last update
10.03.2025, 11:43 AM CET

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Object type

  • Artikel

Associated

  • Jun, Sung Jae
  • Pinkse, Joris
  • Xu, Haiqing
  • Yıldız, Neşe
  • MDPI

Time of origin

  • 2016

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