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Nonparametric Sample Splitting

Yoonseok Lee () and Yulong Wang
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Yoonseok Lee: Center for Policy Research, Maxwell School, Syracuse University, 426 Eggers Hall, Syracuse, NY 13244,

No 222, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: This paper develops a threshold regression model where an unknown relationship between two variables nonparametrically determines the threshold. We allow the observations to be cross-sectionally dependent so that the model can be applied to determine an unknown spatial border for sample splitting over a random field. We derive the uniform rate of convergence and the nonstandard limiting distribution of the nonparametric threshold estimator. We also obtain the root-n consistency and the asymptotic normality of the regression coefficient estimator. Our model has broad empirical relevance as illustrated by estimating the tipping point in social segregation problems as a function of demographic characteristics; and determining metropolitan area boundaries using nighttime light intensity collected from satellite imagery. We find that the new empirical results are substantially different from the existing studies.

Keywords: Sample Splitting; Threshold; Nonparametric; Random Field; Tipping Point; Metropolitan Area Boundary (search for similar items in EconPapers)
JEL-codes: C14 C21 C24 R1 (search for similar items in EconPapers)
Pages: 74 pages
Date: 2020-01
New Economics Papers: this item is included in nep-ore
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