Generalized instrumental inequalities: testing the instrumental variable independence assumption
被引:19
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作者:
Kedagni, Desire
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Iowa State Univ, Dept Econ, 518 Farm House Lane,260 Heady Hall, Ames, IA 50011 USAIowa State Univ, Dept Econ, 518 Farm House Lane,260 Heady Hall, Ames, IA 50011 USA
Kedagni, Desire
[1
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Mourifie, Ismael
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Univ Toronto, Dept Econ, 150 St George St, Toronto, ON M5S 3G7, CanadaIowa State Univ, Dept Econ, 518 Farm House Lane,260 Heady Hall, Ames, IA 50011 USA
Mourifie, Ismael
[2
]
机构:
[1] Iowa State Univ, Dept Econ, 518 Farm House Lane,260 Heady Hall, Ames, IA 50011 USA
[2] Univ Toronto, Dept Econ, 150 St George St, Toronto, ON M5S 3G7, Canada
This paper proposes a new set of testable implications for the instrumental variable independence assumption for discrete treatment, but unrestricted outcome and instruments: generalized instrumental inequalities. When outcome and treatment are both binary, but instruments are unrestricted, we show that the generalized instrumental inequalities are necessary and sufficient to detect all observable violations of the instrumental variable independence assumption. To test the generalized instrumental inequalities, we propose an approach combining a sample splitting procedure and an inference method for intersection bounds. This idea allows one to easily implement the test using existing Stata packages. We apply our proposed strategy to assess the validity of the instrumental variable independence assumption for various instruments used in the returns to college literature.
机构:
Harvard T H Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
Harvard T H Chan Sch Publ Hlth, Dept Biostat, Boston, MA 02115 USAHarvard T H Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
Duan, Rui
Liang, C. Jason
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NIAID, Rockville, MD USAHarvard T H Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
Liang, C. Jason
Shaw, Pamela A.
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机构:
Kaiser Permanente Washington Hlth Res Inst, Seattle, WA USA
Univ Penn, Dept Biostat Epidemiol & Informat, Philadelphia, PA USAHarvard T H Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
Shaw, Pamela A.
Tang, Cheng Yong
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机构:
Univ Penn, Dept Biostat Epidemiol & Informat, Philadelphia, PA USAHarvard T H Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
Tang, Cheng Yong
Chen, Yong
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机构:
Temple Univ, Dept Stat Operat & Data Sci, Philadelphia, PA USA
Univ Penn, Dept Biostat Epidemiol & Informat, Philadelphia, PA 19104 USAHarvard T H Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA
机构:
Carnegie Mellon Univ, Dietrich Coll Humanities & Social Sci, Dept Stat & Data Sci, Pittsburgh, PA 15213 USACarnegie Mellon Univ, Dietrich Coll Humanities & Social Sci, Dept Stat & Data Sci, Pittsburgh, PA 15213 USA
Branson, Zach
Keele, Luke
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机构:
Univ Penn, Sch Med, Dept Surg, Philadelphia, PA 19104 USACarnegie Mellon Univ, Dietrich Coll Humanities & Social Sci, Dept Stat & Data Sci, Pittsburgh, PA 15213 USA