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Semiparametric estimation of a binary response model with a change-point due to a covariate threshold

机译:由于协变量阈值而具有变化点的二进制响应模型的半参数估计

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摘要

This paper is concerned with Semiparametric estimation of a threshold binary response model. The estimation method considered in the paper is Semiparametric since the parameters for a regression function are finite-dimensional, while allowing for heteroskedasticity of unknown form. In particular, the paper considers Manski's [Manski, Charles F., 1975. Maximum score estimation of the stochastic utility model of choice. Journal of Econometrics 3 (3), 205-228; Manski, Charles F., 1985. Semiparametric analysis of discrete response. Asymptotic properties of the maximum score estimator. Journal of Econometrics 27 (3), 313-333] maximum score estimator. The model in this paper is irregular because of a change-point due to an unknown threshold in a covariate. This irregularity coupled with the discontinuity of the objective function of the maximum score estimator complicates the analysis of the asymptotic behavior of the estimator. Sufficient conditions for the identification of parameters are given and theconsistency of the estimator is obtained. It is shown that the estimator of the threshold parameter, consistent and the estimator of the remaining regression parameters, is n~(1/3)-consistent. Furthermore, we obtain the asymptotic distribution of the estimator. It turns out that both estimators y and 9 are oracle-efficient in that converge weakly to the distributions to which they would converge weakly if the other parameter(s) were known.
机译:本文涉及阈值二进制响应模型的半参数估计。本文考虑的估计方法是半参数的,因为回归函数的参数是有限维的,同时允许未知形式的异方差性。特别是,本文考虑了Manski的[Manski,Charles F.,1975。所选择的随机效用模型的最大分值估计。计量经济学杂志3(3),205-228; Manski,Charles F.,1985年。离散响应的半参数分析。最大分数估计器的渐近性质。 Journal of Econometrics 27(3),313-333]最大分数估算器。本文中的模型是不规则的,因为协变量中的未知阈值会导致变化点。这种不规则性加上最大分数估算器的目标函数的不连续性使估算器的渐近行为的分析变得复杂。给出了参数辨识的充分条件,并获得了估计量的一致性。结果表明,阈值参数的估计量是一致的,其余回归参数的估计量是n〜(1/3)-一致的。此外,我们获得了估计量的渐近分布。事实证明,估计器y和9都是Oracle有效的,因为如果已知其他一个或多个参数,它们将收敛到它们将弱收敛的分布。

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