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. H...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.展开更多
基金funded in part by National Natural Science Foundation of China (Grant No. 71032005)the MOE Project of Key Research Institute of Humanities and Social Science in University (Grant No. 10JJD630005)+3 种基金supported in part by New Century Excellent Talent Supporting program (Grant No. NCET-09-0538)National Natural Science Foundation of China(Grant Nos. 70871073 and 71171127)Shanghai Leading Academic Discipline Project (Grant No. B801)the Key Laboratory of Mathematical Economics (SUFE), Ministry of Education of China
文摘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.
