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Author: Loh, Isaac
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Loh, Isaac |
Essays in Nonparametric Econometrics Ph.D. Dissertation, Department of Economics, Northwestern University, 2021 Cohort(s): Young Men Publisher: ProQuest Dissertations & Theses (PQDT) Keyword(s): Educational Returns; Modeling, Nonparametric Regression; Statistical Analysis Permission to reprint the abstract has not been received from the publisher. Chapter 1 considers a nonparametric instrumental regression model in which the regressor and instrument are discretely distributed. Here, we strengthen the conventional moment independence assumption between instrument and residual to include higher order moments. We give conditions under which a function of interest is partially identified when the regressor has more mass points than the instrument. We also show that the function is point identified as long as certain latent parameters corresponding to conditional moments of the residual lie outside of a set of measure zero. We use our results on identification to construct an estimator for the structural function. The estimator performs well in Monte Carlo simulations, and in applications to studies of Angrist and Evans (1998), Card (1995), and Acemoglu and Angrist (2000). |
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Bibliography Citation
Loh, Isaac. Essays in Nonparametric Econometrics. Ph.D. Dissertation, Department of Economics, Northwestern University, 2021. |