Semiparametric estimation of a binary response model with a change-point due to a covariate threshold
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, th...
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Published in | Journal of econometrics Vol. 144; no. 2; pp. 492 - 499 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.06.2008
Elsevier Elsevier Sequoia S.A |
Series | Journal of Econometrics |
Subjects | |
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Abstract | 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 the consistency of the estimator is obtained. It is shown that the estimator of the threshold parameter,
γ
0
, is
n
−
1
-consistent and the estimator of the remaining regression parameters,
θ
0
, is
n
−
1
/
3
-consistent. Furthermore, we obtain the asymptotic distribution of the estimator. It turns out that both estimators
γ
ˆ
and
θ
ˆ
are oracle-efficient in that
n
(
γ
ˆ
n
−
γ
0
)
and
n
1
/
3
(
θ
ˆ
n
−
θ
0
)
converge weakly to the distributions to which they would converge weakly if the other parameter(s) were known. |
---|---|
AbstractList | 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 the consistency of the estimator is obtained. It is shown that the estimator of the threshold parameter, [gamma]0, is n-1-consistent and the estimator of the remaining regression parameters, [theta]0, is n-1/3-consistent. Furthermore, we obtain the asymptotic distribution of the estimator. It turns out that both estimators and are oracle-efficient in that and converge weakly to the distributions to which they would converge weakly if the other parameter(s) were known. 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 the consistency of the estimator is obtained. It is shown that the estimator of the threshold parameter, γ 0 , is n − 1 -consistent and the estimator of the remaining regression parameters, θ 0 , is n − 1 / 3 -consistent. Furthermore, we obtain the asymptotic distribution of the estimator. It turns out that both estimators γ ˆ and θ ˆ are oracle-efficient in that n ( γ ˆ n − γ 0 ) and n 1 / 3 ( θ ˆ n − θ 0 ) converge weakly to the distributions to which they would converge weakly if the other parameter(s) were known. 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 the consistency of the estimator is obtained. It is shown that the estimator of the threshold parameter, @c"0, is n-1-consistent and the estimator of the remaining regression parameters, @q"0, is n-1/3-consistent. Furthermore, we obtain the asymptotic distribution of the estimator. It turns out that both estimators @c@? and @q@? are oracle-efficient in that n(@c@?"n-@c"0) and n1/3(@q@?"n-@q"0) converge weakly to the distributions to which they would converge weakly if the other parameter(s) were known. All rights reserved, Elsevier 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 the consistency of the estimator is obtained. It is shown that the estimator of the threshold parameter, ..., is n...-consistent and the estimator of the remaining regression parameters, ..., is n...-consistent. Furthermore, the authors obtain the asymptotic distribution of the estimator. It turns out that both estimators ... and ... are oracle-efficient in that ... and ... converge weakly to the distributions to which they would converge weakly if the other parameter(s) were known. (ProQuest: ... denotes formulae/symbols omitted.) |
Author | Lee, Sokbae Seo, Myung Hwan |
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Keywords | Nonlinear random utility models Semiparametric estimation Maximum score estimation Binary response model Threshold regression Stochastic model Score test Statistical distribution Binary response model,Maximum score estimation,Nonlinear random utility models,Semiparametric estimation,Threshold regression Response model Non parametric estimation Change point Covariate Economic sciences Parameter identification Economic data Score function Consistent estimator Regression function Distribution function Binary response Oracle Discontinuity Data analysis Asymptotic behavior Statistical estimation Semiparametric method Weak convergence Statistical method Statistical regression Sufficient condition Objective function Econometrics |
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SubjectTerms | Applications Asymptotic methods Binary response model Covariance Distribution Econometric models Econometrics Economic models Estimating techniques Estimation Exact sciences and technology Insurance, economics, finance Linear inference, regression Mathematics Maximum score estimation Non-linear models Nonlinear random utility models Nonparametric inference Parameter estimation Parametric inference Probability and statistics Regression analysis Sciences and techniques of general use Semiparametric estimation Statistics Studies Threshold regression Utility theory |
Title | Semiparametric estimation of a binary response model with a change-point due to a covariate threshold |
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