This study may be seen as an updated form of the article by Proen¸ca andWerwatz (1994) which used XploRe commands written for both estimators in an old MS Dos format.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:In this article, a simulation study is performed to reveal the devia- tions of the semiparametric binary response model from its parametric counterpart, based on various scenarios including different sample sizes, different bandwidth parameters containing the optimal ones, different forms of the linear index function and two and higher dimensional cases of the explanatory variables when the true model is logistic regression.
📊
Key Findings & Data:A real data set on liquefaction is used to demonstrate the effectiveness of the simula- tion results with the results in practice.
💡
Conclusion & Impact:This study may be seen as an updated form of the article by Proen¸ca andWerwatz (1994) which used XploRe commands written for both estimators in an old MS Dos format.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this article, a simulation study is performed to reveal the devia- tions of the semiparametric binary response model from its parametric counterpart, based on various scenarios including different sample sizes, different bandwidth parameters containing the optimal ones, different forms of the linear index function and two and higher dimensional cases of the explanatory variables when the true model is logistic regression. The method of the Density Weighted Average Derivative Estimator (DWADE) is used in the semi-parametric estimation. A real data set on liquefaction is used to demonstrate the effectiveness of the simula- tion results with the results in practice. Additionally, new commands written for the estimation of both models in the Windows based 4.8 version of the XploRe package are introduced. This study may be seen as an updated form of the article by Proen¸ca andWerwatz (1994) which used XploRe commands written for both estimators in an old MS Dos format.
🔖
Cite This Article
AKKUŞ, Ö., GÖKTAŞ, A., TATLIDİL, H. (2022). On the performance of the semiparametric binary response model when the true model is parametric logistic. Hacettepe Journal of Mathematics and Statistics, Cilt: 39 - Sayı: 4, 583–597. https://ajindex.com/articles/530660
Aldrich, J.H. and Nelson, F.D. Linear Probability, Logit and Probit Models (Sage Publications, London, 1984)
Geological Research Report (The General Directorate of Highways, Turkey, 2009)
Hardle, W., Müller, M., Sperlich, S. and Werwatz, A. Nonparametric and Semiparametric Models (Springer-Verlag, New York, 2004)
Hardle, W. Applied Nonparametric Regression (Cambridge University Press, Cambridge, 1990)
Hardle, W., Klinke, S. and M¨uller, M. XploRe Learning Guide (MDtech, Springer-Verlag, New York, 1999)
Hardle, W., Hlavka, Z. and Klinke, S. XploRe Application Guide, (e-book, MD Tech, Springer-Verlag, New York, 2003)
Hardle, W., Klinke, S. and Turlach, B.A. XploRe: An Interactive Statistical Computing Environment: Statistics and Computing (Springer-Verlag, New York, 2007)
Horowitz, J. L. Semiparametric Methods in Econometrics (Springer-Verlag, New York,1998)
Horowitz, J. L. and Hardle, W. Testing a parametric model against a semiparametric alternative, Econometric Theory 10, 821–848, 1994
Hosmer, D.W. and Lemeshow, S. Applied Logistic Regression (John Wiley and Sons, New York, 1989)
Ichimura, H. Semiparametric least squares (sls) and weighted sls estimation of single-index models, Journal of Econometrics 58, 71–120, 1993
Law, A.M. and Kelton, W.D. Simulation Modeling and Analysis (McGraw-Hill International Series, Singapore, 2000)
Manski, C. F. Identification of binary response models, Journal of the American Statistical Association 83, 729–738, 1988
McCullagh, P. and Nelder, J.A. Generalized Linear Models: Monographs on Statistics and Applied Probability 37 (Chapman and Hall, London, 1989)
Powell, J. L., Stock, J.H. and Stoker, T.M. Semiparametric estimation of index coefficients, Econometrica 57 (6), 1403–1430, 1989
Proença, I. and Werwatz, A. Comparing Parametric and Semiparametric Binary Response Models (Humboldt University, Berlin, 1994)
Proença, I. and Silva, S. Parametric and semiparametric specification tests for binary choice models. A comparative simulation study, Econometrics, Econ WPA, No: 0508008, 2005.