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	Nonparametric and semiparametric regressions subject to monotonicity constraints: Estimation and forecasting
	Lee, Tae-Hwy ; Tu, Yundong ; Ullah, Aman
	2014
关键词	Local monotonicity Bagging Asymptotic mean squared errors Second order stochastic dominance Equity premium prediction STOCHASTIC MONOTONICITY EQUITY PREMIUM BOOTSTRAP
英文摘要	This paper considers nonparametric and semiparametric regression models subject to monotonicity constraint. We use bagging as an alternative approach to Hall and Huang (2001). Asymptotic properties of our proposed estimators and forecasts are established. Monte Carlo simulation is conducted to show their finite sample performance. An application to predicting equity premium is taken for illustration. We introduce a new forecasting evaluation criterion based on the second order stochastic dominance in the size of forecast errors and compare models over different sizes of forecast errors. Imposing monotonicity constraint can mitigate the chance of making large size forecast errors. (C) 2014 Elsevier B.V. All rights reserved.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000337881300016&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Economics; Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical Methods; SCI(E); EI; SSCI; 2; ARTICLE; taelee@ucr.edu; yundong.tu@gsm.pku.edu.cn; aman.ullah@ucr.edu; 1; 196-210; 182
语种	英语
出处	SCI ; EI
出版者	journal of econometrics
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/209740]
专题	数学科学学院
推荐引用方式 GB/T 7714	Lee, Tae-Hwy,Tu, Yundong,Ullah, Aman. Nonparametric and semiparametric regressions subject to monotonicity constraints: Estimation and forecasting. 2014-01-01.

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