Add to ORKGAbstract In this paper, nonlinear least squares (NLLS) estimators are proposed for semiparametric binary response models under conditional median restrictions. The estimators can be identical to NLLS procedures for parametric binary response models (e.g. Probit), and consequently have the advantage of being easily implementable using standard software packages such as Stata. This is in contrast to existing estimators for the model, such as the maximum score estimator JEL Classification: C13, C14, C25
We propose a nonparametric approach for estimating single-index, binary-choice models when parametri...
Sample selection models are employed when an outcome of interest is observed for a restricted non-ra...
Abstract. We discuss the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 3...
Most existing semi-parametric estimation procedures for binary choice models are based on the maximu...
In this paper we reconsider the notion of optimality in estimation of partially identified models. W...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
Strong assumptions needed to correctly specify parametric binary choice probability models make them...
This paper proposes a semiparametric estimator for spatial autoregressive (SAR) binary choice models...
This paper is concerned with semiparametric estimation of a threshold binary response model. The est...
This paper describes a semiparametric estimator for binary response models in which there may be arb...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
The binary-response maximum score (MS) estimator is a robust estimator, which can accommodate hetero...
In this paper, we propose a two-step semiparametric maximum likelihood (SML) estimator for the coeff...
This paper deals with the problem of nonstationarity of regressors in binary choice model. The limit...
This paper considers a local control function approach for the binary response model under endogenei...
We propose a nonparametric approach for estimating single-index, binary-choice models when parametri...
Sample selection models are employed when an outcome of interest is observed for a restricted non-ra...
Abstract. We discuss the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 3...
Most existing semi-parametric estimation procedures for binary choice models are based on the maximu...
In this paper we reconsider the notion of optimality in estimation of partially identified models. W...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
Strong assumptions needed to correctly specify parametric binary choice probability models make them...
This paper proposes a semiparametric estimator for spatial autoregressive (SAR) binary choice models...
This paper is concerned with semiparametric estimation of a threshold binary response model. The est...
This paper describes a semiparametric estimator for binary response models in which there may be arb...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
The binary-response maximum score (MS) estimator is a robust estimator, which can accommodate hetero...
In this paper, we propose a two-step semiparametric maximum likelihood (SML) estimator for the coeff...
This paper deals with the problem of nonstationarity of regressors in binary choice model. The limit...
This paper considers a local control function approach for the binary response model under endogenei...
We propose a nonparametric approach for estimating single-index, binary-choice models when parametri...
Sample selection models are employed when an outcome of interest is observed for a restricted non-ra...
Abstract. We discuss the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 3...