Document Type

Working Paper

Date

1-2020

Keywords

Sample Splitting, Threshold, Nonparametric, Random Field, Tipping Point, Metropolitan Area Boundary

Language

English

Acknowledgements

We thank Bo Honoré, Sokbae Lee, Yuan Liao, Myung Seo, Ping Yu, and participants at numerous seminar/conference presentations for very helpful comments. Financial supports from the ApplebyMosher grant and the CUSE grant are highly appreciated.

Disciplines

Economic Policy | Economics | Public Affairs, Public Policy and Public Administration

Description/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 crosssectionally 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

ISSN

1525-3066

Additional Information

Working paper no. 222

Source

Local input

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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