Although semiparametric alternatives are available, parametric binary choice models are widely used in practice, in spite of their sensitivity to misspecification. Here we present the results of a simulation study on the finite sample performance of parametric and semiparametric specification tests for this kind of models. The results obtained indicate that the computationally demanding semiparametric tests do not generally outperform the simpler score tests against parametric alternatives
Estimation results obtained by parametric models may be seriously misleading when the model is missp...
Most empirical work in the social sciences is based on observational data that are often both incomp...
Several new tests are proposed for examining the adequacy of a family of parametric models against l...
The following thesis compares the performance of several parametric and semiparametric estimators in...
Strong assumptions needed to correctly specify parametric binary choice probability models make them...
AbstractModel misspecification is a serious issue since misspecification generally renders statistic...
Binary choice models occur frequently in economic modeling. A measure of the predictive performance ...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
In this paper, we develop a bayesian analysis of a semi-parametric binary choice model.The prior spe...
A general model specification test of a parametric model against a nonparametric or semiparametric a...
This paper provides a general framework for constructing specification tests for parametric and semip...
The estimation of conditional probability distribution functions (PDFs) in a kernel nonparametric fr...
This dissertation consists of three essays evaluating model selection criteria in both sampling the...
The estimation of conditional probability distribution functions (PDFs) in a kernel nonparametric fr...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
Estimation results obtained by parametric models may be seriously misleading when the model is missp...
Most empirical work in the social sciences is based on observational data that are often both incomp...
Several new tests are proposed for examining the adequacy of a family of parametric models against l...
The following thesis compares the performance of several parametric and semiparametric estimators in...
Strong assumptions needed to correctly specify parametric binary choice probability models make them...
AbstractModel misspecification is a serious issue since misspecification generally renders statistic...
Binary choice models occur frequently in economic modeling. A measure of the predictive performance ...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
In this paper, we develop a bayesian analysis of a semi-parametric binary choice model.The prior spe...
A general model specification test of a parametric model against a nonparametric or semiparametric a...
This paper provides a general framework for constructing specification tests for parametric and semip...
The estimation of conditional probability distribution functions (PDFs) in a kernel nonparametric fr...
This dissertation consists of three essays evaluating model selection criteria in both sampling the...
The estimation of conditional probability distribution functions (PDFs) in a kernel nonparametric fr...
This Master thesis investigates the semi-parametric estimation method Maximum Score of Manski (1988)...
Estimation results obtained by parametric models may be seriously misleading when the model is missp...
Most empirical work in the social sciences is based on observational data that are often both incomp...
Several new tests are proposed for examining the adequacy of a family of parametric models against l...