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Author: Kedagni, Desire
Resulting in 2 citations.
1. Kedagni, Desire
Testing Instrument Validity and Identification with Invalid Instruments
Ph.D. Dissertation, Department of Economics, The Pennsylvania State University, 2018
Cohort(s): Young Men
Publisher: ProQuest Dissertations & Theses (PQDT)
Keyword(s): College Education; Educational Returns; Modeling, Instrumental Variables

Permission to reprint the abstract has not been received from the publisher.

In the second chapter, I consider identification of treatment effects when the treatment is endogenous. The use of instrumental variables is a popular solution to deal with endogeneity, but this may give misleading answers when the instrument is invalid. I show that when the instrument is invalid due to correlation with the first stage unobserved heterogeneity, a second (also possibly invalid) instrument allows to partially identify not only the local average treatment effect, but also the entire potential outcomes distributions for compliers. I exploit the fact that the distribution of the observed outcome in each group defined by the treatment and the instrument is a mixture of the distributions of interest. I write the identified set in the form of conditional moment inequalities, and provide an easily implementable inference procedure. Under some (testable) tail restrictions, the potential outcomes distributions are point-identified for compliers. Finally, I illustrate my methodology on data from the National Longitudinal Survey of Young Men to estimate returns to college using college proximity as (potential) instrument. I find that a 95% level confidence set for the average return to college for compliers is [38%, 79%].
Bibliography Citation
Kedagni, Desire. Testing Instrument Validity and Identification with Invalid Instruments. Ph.D. Dissertation, Department of Economics, The Pennsylvania State University, 2018.
2. Kedagni, Desire
Mourifie, Ismael
Generalized Instrumental Inequalities: Testing the Instrumental Variable Independence Assumption
Biometrika published online (29 February 2020): DOI: 10.1093/biomet/asaa003.
Also: https://academic.oup.com/biomet/advance-article/doi/10.1093/biomet/asaa003/5767137
Cohort(s): NLSY79
Publisher: Oxford University Press
Keyword(s): College Cost; College Education; Modeling, Instrumental Variables; Parental Influences; Wages

Permission to reprint the abstract has not been received from the publisher.

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.
Bibliography Citation
Kedagni, Desire and Ismael Mourifie. "Generalized Instrumental Inequalities: Testing the Instrumental Variable Independence Assumption." Biometrika published online (29 February 2020): DOI: 10.1093/biomet/asaa003.