NDLI: Semi-parametric estimation for the Box-Cox transformation model with partially linear structure

Content Provider	Springer Nature Link
Author	Zhou, GuoLiang Zhou, YaHong
Copyright Year	2012
Abstract	The Box-Cox transformation model has been widely used in applied econometrics, positive accounting, positive finance and statistics. There is a large literature on Box-Cox transformation model with linear structure. However, there is seldom seen on the discussion for such a model with partially linear structure. Considering the importance of the partially linear model, in this paper, a relatively simple semi-parametric estimation procedure is proposed for the Box-Cox transformation model without presuming the linear functional form and without specifying any parametric form of the disturbance, which largely reduces the risk of model misspecification. We show that the proposed estimator is consistent and asymptotically normally distributed. Its covariance matrix is also in a closed form, which can be easily estimated. Finally, a simulation study is conducted to see the finite sample performance of our estimator.
Starting Page	459
Ending Page	481
Page Count	23
File Format	PDF
ISSN	16747283
Journal	Science in China Series A: Mathematics
Volume Number	56
Issue Number	3
e-ISSN	18691862
Language	English
Publisher	SP Science China Press
Publisher Date	2012-06-29
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Box-Cox transformation model semiparametric estimation rank condition smoothed kernel Applications of Mathematics
Content Type	Text
Resource Type	Article
Subject	Mathematics

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