Semiparametric Estimation of the Box–Cox Transformation Model  

Oleh:

Shin, Youngki

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The Econometrics Journal vol. 11 no. 3 (2008), page 517.
Topik: Semiparametric Estimation; Box–Cox Transformation; Model
Fulltext: 517.pdf (585.13KB)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: EE39.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In this paper, I propose a semiparametric estimation procedure for the Box–Cox transformation model. I show a global identification result under mild conditions that allow conditional heteroskedastic error terms. The proposed estimator minimizes a second order U-process and does not require any user-chosen values such as a smoothing parameter that sometimes induces unstable inference result. With a slight modification, it can also be applied to random censoring which depends on covariates in an arbitrary way. The estimator converges to an asymptotic normal distribution at the rate of and Monte Carlo experiments show adequate finite sample performance.

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