Nonparametric Sample Splitting

Yoonseok Lee and Yulong Wang

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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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:222

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