Threshold regression with nonparametric sample splitting

Yoonseok Lee and Yulong Wang

Journal of Econometrics, 2023, vol. 235, issue 2, 816-842

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. We illustrate empirical relevance of this new model 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.

Keywords: Threshold regression; Sample splitting; 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)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Threshold Regression with Nonparametric Sample Splitting (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:235:y:2023:i:2:p:816-842

DOI: 10.1016/j.jeconom.2022.07.005

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