Download or read book Essays on Semiparametric Estimation of Multinomial Discrete Choice Models written by and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the first chapter I propose a semiparametric estimator that allows for a flexible form of heteroskedasticity for multinomial discrete choice (MDC) models. Despite being semiparametric, the rate of convergence of the smoothed maximum score (SMS) estimator is not affected by the number of alternative choices. I show the strong consistency and asymptotic normality of the proposed estimator. The rate of convergence of the SMS estimator for MDC models can be made arbitrarily close to the inverse of the square root of the sample size, which is the same as the rate of convergence of Horowitz's (1992) SMS estimator for the binary response model. Monte Carlo experiments provide evidence that the proposed estimator has a smaller mean squared error than both the conditional logit estimator and the maximum score estimator when heteroskedasticity exists. I apply the SMS estimator to study the college decisions of high school graduates using a subset of Chilean data from 2011. The estimation results of the SMS estimator differ significantly from the results of the conditional logit estimator, which suggests possible misspecification of parametric models and the usefulness of considering the SMS estimator as an alternative for estimating MDC models. Many MDC applications include potentially endogenous regressors. To allow for endogeneity, in the second chapter I propose a two-stage instrumental variables estimator where the endogenous variable is replaced by a linear estimate, and then the preference parameters in the MDC equation are estimated by the SMS estimator described in the first chapter. In neither stage do I specify the distribution of the error terms, so this two-stage estimation method is semiparametric. This estimator is a generalization of the estimator proposed by Fox (2007). Fox suggests applying the maximum score estimator in the second stage of estimation. This chapter is the first to derive the statistical properties of an estimator allowing for endogeneity in this semiparametric setting. The two-stage instrument variables estimator is consistent when the linear function of instrument variables and other covariates can rank order the choice probabilities. The second chapter also provides results of some Monte Carlo experiments.

Download or read book Essays on Discrete Choice Models written by Wei Song and published by . This book was released on 2017 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation focuses on the identification and estimation of discrete choice models. In practice, if the error term is independent of the covariates and follows some known distribu- tion, the discrete choice model is usually estimated using some parametric estimator, such as Probit and Logit. However, when the distribution of the error is unknown, misspecification would in general cause the estimators inconsistent even if the independence between the covariates and the error still holds. The two chapters relax the assumptions on the error distribution in the discrete choice models and propose semiparametric estimators.

Download or read book Semiparametric Identi tion and Estimation of Multinomial Discrete Choice Models Using Error Symmetry written by Arthur Lewbel and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on Estimation of Discrete Choice Models with Endogeneity written by Nese Yildiz and published by . This book was released on 2005 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three Essays on Semiparametric Models of Dynamic Discrete Choice Program Evaluation and the College Premium in the Eighties written by Christopher Taber and published by . This book was released on 1995 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays in Discrete Choice Demand Estimation written by Konstantinos Hatzitaskos and published by . This book was released on 2007 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semiparametric Estimation of Binary Discrete Choice Models written by Margarida Genius and published by . This book was released on 1990 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semiparametric Estimation of Discrete Choice Models written by Trueman Scott Thompson and published by . This book was released on 1989 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semiparametric Bayesian Estimation of Dynamic Discrete Choice Models written by Andriy Norets and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a tractable semiparametric estimation method for dynamic discrete choice models. The distribution of additive utility shocks is modeled by location-scale mixtures of extreme value distributions with varying numbers of mixture components. Our approach exploits the analytical tractability of extreme value distributions and the flexibility of the location-scale mixtures. We implement the Bayesian approach to inference using Hamiltonian Monte Carlo and an approximately optimal reversible jump algorithm. For binary dynamic choice model, our approach delivers estimation results that are consistent with the previous literature. We also apply the proposed method to multinomial choice models, for which previous literature does not provide tractable estimation methods in general settings without distributional assumptions on the utility shocks. In our simulation experiments, we show that the standard dynamic logit model can deliver misleading results, especially about counterfactuals, when the shocks are not extreme value distributed. Our semiparametric approach delivers reliable inference in these settings. We develop theoretical results on approximations by location-scale mixtures in an appropriate distance and posterior concentration of the set identified utility parameters and the distribution of shocks in the model.

Download or read book Essays on Semiparametric Models with Partial Identification written by and published by . This book was released on 2012 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of two self-contained essays on partially identified econometric models, organized in the form of two chapters. The first chapter develops inference methods for conditional moment models in which the unknown parameter is possibly partially identified and may contain infinite-dimensional components. I consider testing the hypothesis that a given restriction on the parameter is satisfied by at least one element of the identification set. I propose using the sieve minimum of a Kolmogorov-Smirnov type statistic as the test statistic, derive its asymptotic distribution, and provide consistent bootstrap critical values. In this way a broad family of restrictions can be consistently tested, making the proposed procedure applicable to various types of inference. In particular, I show how to: (1) test the semiparametric model specification; (2) construct confidence sets for unknown parametric components; and (3) construct confidence sets for unknown functions at a given point. The specification test is consistent against fixed alternatives. The confidence sets have correct asymptotic coverage probability, excluding any value outside the identification set with asymptotic probability one. My methods are robust to partial identification, and allow for the moment functions to be nonsmooth. A Monte Carlo study demonstrates finite sample performance. In the second chapter, I consider estimation in dynamic discrete choice panel data models of short time series, in which neither the cross-sectional heterogeneity nor the initial condition is observed. The major challenges are: (1) point-identification often fails in these models as demonstrated by Honoré and Tamer (2006); and (2) the heterogeneity cannot be differenced out by the standard "within" or first difference transformations due to nonlinearity. I show that the parameter can be equivalently defined by a finite number of conditional moment equalities. And I propose set estimators that are fixed-T consistent with respect to a properly defined Hausdorff distance. Rates of convergence in the Hausdorff distance are derived.

Download or read book Applied Discrete choice Modelling written by David A. Hensher and published by Taylor & Francis. This book was released on 1981 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semiparametric Estimation and Inference in Multinomial Choice and Systems of Censored Demand Equation Models with Application to Estimating Demand Systems written by Rafic H. Fahs and published by . This book was released on 2001 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on the Simulation based Estimation of Dynamic Discrete Choice Models written by Ben Waltmann and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three Essays on the Application of Discrete Choice Models with Discrete continuous Heterogeneity Distributions written by Chen Wang and published by . This book was released on 2016 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unobserved heterogeneity is comprehensively acknowledged as an important feature to be considered in discrete choice modeling. Over the last decade, there were abundant studies showing the great outperformance of capturing unobserved heterogeneity of Mixed-Mixed Logit(MM-MNL) models. However, most empirical researches still use mixed logit(MIXL) models or latent class(LC) models which introduced strong assumptions on distributions of marginal utility. In this dissertation, a Mixed-Mixed Logit model(MM-MNL) that assumes a non-parametric mixing distribution for marginal utility is discussed. Consequently, three empirical studies solving different transportation problems are introduced.

Download or read book Essays on Semiparametric Estimation of Models with Structural Breaks written by Abhisek Banerjee and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2003-01-13 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of contents

Download or read book Essays on Semiparametric Estimations of the Binary Choice Model and the General Heteroskedastic Transformation Model written by Hanghui Zhang and published by . This book was released on 2013 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: