An Efficient Semiparametric Estimator for Binary Response Models PDF Download
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Author: Roger Klein
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 52
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Author: Roger Klein
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 52
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Author: Anas Ramadan
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Category :
Languages : en
Pages :
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Author:
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Category :
Languages : en
Pages :
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Author: Ron Mittelhammer
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Category :
Languages : en
Pages : 60
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Author:
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Category : Sampling (Statistics)
Languages : en
Pages :
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Author:
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ISBN:
Category :
Languages : en
Pages : 0
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Semiparametric estimation of monotonic single index models is studied. In this class of models, the unknown components are a monotonic link function along with finite-dimensional parameters including the coefficient of the single index. The proposed method optimizes objective functionals with respect to both finite and infinite dimensional parameters. In the first chapter, proofs of consistency, rates of convergence, asymptotic normality and semiparametric efficiency are offered. The main result is applied to the semiparametric Least Squares (LS) estimation, semiparametric Least Absolute Deviation (LAD) estimation, and the semiparametric Maximum Likelihood (ML) estimation for various types of single index models. The second chapter focuses on an iteration-based method proposed by Wang and Zhou (1995) for the standard binary choice model. The algorithm is kernel free, very fast and easy-to-implement. The estimator is consistent and nearly efficient. These desirable large sample properties of the estimator, however, have not been rigorously proven so far. In this chapter, a set of sufficient conditions for consistency and asymptotic normality of the WZ estimator will be given. In the third chapter, the estimation methods developed in the previous two chapters are applied to dichotomous choice contingent valuation, which has been one of the most popular methods to estimate Willingness-To-Pay (WTP) for non-market goods, such as environmental resources. The proposed method is a two-step estimatior. In the first step, the underlying binary response model is estimated by the method studied in the previous chapters. In the second step, the distribution of the WTP is computed based on the first estimates. Consistency, asymptotic normality, and semiparametric efficiency of the estimator are studied.
Author: Kazumitsu Nawata
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ISBN:
Category :
Languages : en
Pages :
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Author: Margarida Genius
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 274
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Author: Jin-Young Choi
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ISBN:
Category :
Languages : en
Pages : 0
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A semiparametric estimator for binary-outcome sample-selection models is proposed that imposes only single index assumptions on the selection and outcome equations without specifying the error term distribution. I adopt the idea in Lewbel (2000) using a 'special regressor' to transform the binary response Y so that the transformed Y becomes linear in the latent index, which then makes it possible to remove the selection correction term by differencing the transformed Y equation. There are various versions of the estimator, which perform differently trading off bias and variance. A simulation study is conducted, and then I apply the estimators to US presidential election data in 2008 and 2012 to assess the impact of racial prejudice on the elections, as a black candidate was involved for the first time ever in the US history.
Author: Joel L. Horowitz
Publisher: Springer Science & Business Media
ISBN: 1461206219
Category : Mathematics
Languages : en
Pages : 211
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Book Description
Many econometric models contain unknown functions as well as finite- dimensional parameters. Examples of such unknown functions are the distribution function of an unobserved random variable or a transformation of an observed variable. Econometric methods for estimating population parameters in the presence of unknown functions are called "semiparametric." During the past 15 years, much research has been carried out on semiparametric econometric models that are relevant to empirical economics. This book synthesizes the results that have been achieved for five important classes of models. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data.
