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 inJournal of econometrics Vol. 144; no. 2; pp. 492 - 499
Main Authors Lee, Sokbae, Seo, Myung Hwan
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.06.2008
Elsevier
Elsevier Sequoia S.A
SeriesJournal of Econometrics
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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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Issue 2
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
Language English
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Snippet This paper is concerned with semiparametric estimation of a threshold binary response model. The estimation method considered in the paper is semiparametric...
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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
URI https://dx.doi.org/10.1016/j.jeconom.2008.02.003
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Volume 144
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