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Frontiers of Economics in China

Front. Econ. China    2016, Vol. 11 Issue (1) : 40-59     DOI: 10.3868/s060-005-016-0004-6
Orginal Article |
Inference for Optimal Split Point in Conditional Quantiles
Yanqin Fan1(),Ruixuan Liu2,Dongming Zhu3
1. Department of Economics, University of Washington, Seattle, WA 98195, USA
2. Department of Economics, Emory University, Atlanta, GA 30322, USA
3. School of Economics & Key Laboratory of Mathematical Economics, Shanghai University of Finance and Economics, Shanghai 200433, China
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In this paper we show the occurrence of cubic-root asymptotics in misspecified conditional quantile models where the approximating functions are restricted to be binary decision trees. Inference procedure for the optimal split point in the decision tree is conducted by inverting a t-test or a deviation measure test, both involving Chernoff type limiting distributions. In order to avoid estimating the nuisance parameters in the complicated limiting distribution, subsampling is proved to deliver the correct confidence interval/set.

Keywords cubic-root asymptotics      Chernof distribution      misspecified Quantile regression      optimal split point     
Issue Date: 22 March 2016
 Cite this article:   
Yanqin Fan,Ruixuan Liu,Dongming Zhu. Inference for Optimal Split Point in Conditional Quantiles[J]. Front. Econ. China, 2016, 11(1): 40-59.
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Yanqin Fan
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