A lack-of-fit test in Tobit errors-in-variables regression models

Weixing Song and Weixin Yao

Statistics & Probability Letters, 2011, vol. 81, issue 12, 1792-1801

Abstract: The problem of fitting a parametric model in Tobit errors-in-variables regression models is discussed in this paper. The proposed test is based on the supremum of the Khmaladze type transformation of a certain partial sum process of calibrated residuals. This framework covers the usual error-free Tobit model as a special case. The asymptotic null distribution of this transformed process is shown to be the same as that of a time transformed standard Brownian motion. Consistency against some fixed alternatives and asymptotic power under some local nonparametric alternatives of this test are also discussed. Simulation studies are conducted to assess the finite sample performance of the proposed test.

Keywords: Tobit regression model; Errors-in-variables; Khmaladze transformation; Brownian motion; Consistency and local power (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1016/j.spl.2011.07.015

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