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ArtikelResponse Error In A Transformation Model With An Application To Earnings-Equation Estimation  
Oleh: Abrevaya, Jason ; Hausman, Jerry A.
Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The Econometrics Journal vol. 7 no. 2 (Dec. 2004), page 366–388.
Topik: Measurement error; Transformation model; Box–Cox model; Semi-parametric estimation; Local polynomial estimation
Fulltext: 366.pdf (227.86KB)
Isi artikelThis paper considers estimation of a transformation model in which the transformed dependent variable is subject to classical measurement error. We consider cases in which the transformation function is known and unspecified. In special cases (e.g. log and square-root transformations), least-squares or non-linear least-squares estimators are applicable. A flexible approximation approach (based on Taylor expansion) is proposed for a parametrized transformation function (like the Box–Cox model), and a semi-parametric approach (combining a semi-parametric linear-index estimator and non-parametric regression) is proposed for the case of an unspecified transformation function. The methods are applied to the estimation of earnings equations, using wage data from the Current Population Survey (CPS).
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