Multiple Discrete Endogenous Variables in Weakly-Separable Triangular Models
Sung Jae Jun (),
Haiqing Xu () and
Neşe Yıldız ()
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Sung Jae Jun: CAPCP and Department of Economics, Pennsylvania State University, 608 Kern Graduate Building, University Park, PA 16802, USA
Neşe Yıldız: Department of Economics, University of Rochester, 222 Harkness Hall, Rochester, NY 14627, USA
Econometrics, 2016, vol. 4, issue 1, 1-21
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.
Keywords: nonparametric identification; discrete endogenous regressors; triangular models (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:4:y:2016:i:1:p:7-:d:63449
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