Semiparametric Estimation of a Multinomial Response Model with Random Coefficients PDF Download
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Author: Yue Yu
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 166
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Book Description
Author: Yue Yu
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 166
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
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.
Author: Badi H. Baltagi
Publisher: John Wiley & Sons
ISBN: 047099830X
Category : Business & Economics
Languages : en
Pages : 736
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Book Description
A Companion to Theoretical Econometrics provides a comprehensive reference to the basics of econometrics. This companion focuses on the foundations of the field and at the same time integrates popular topics often encountered by practitioners. The chapters are written by international experts and provide up-to-date research in areas not usually covered by standard econometric texts. Focuses on the foundations of econometrics. Integrates real-world topics encountered by professionals and practitioners. Draws on up-to-date research in areas not covered by standard econometrics texts. Organized to provide clear, accessible information and point to further readings.
Author: Trueman Scott Thompson
Publisher:
ISBN:
Category :
Languages : en
Pages : 310
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Author: Xiaoxia Shi
Publisher:
ISBN:
Category :
Languages : en
Pages : 32
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This paper proposes a new semi-parametric identification and estimation approach to multinomial choice models in a panel data setting with individual fixed effects. Our approach is based on cyclic monotonicity, which is a defining convex-analytic feature of the random utility framework underlying multinomial choice models. From the cyclic monotonicity property, we derive identifying inequalities without requiring any shape restrictions for the distribution of the random utility shocks. These inequalities point identify model parameters under straightforward assumptions on the covariates. We propose a consistent estimator based on these inequalities.
Author: Rafic H. Fahs
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 276
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Author: Shakeeb Khan
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Yale University. Cowles Foundation for Research in Economics
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 636
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Author: Aman Ullah
Publisher: CRC Press
ISBN: 9780203911075
Category : Business & Economics
Languages : en
Pages : 754
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Book Description
Summarizing developments and techniques in the field, this reference covers sample surveys, nonparametric analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, engineering, sociology, psychology, and information technology. It supplies a geometric proof of an extended Gauss-Markov theorem, approaches for the design and implementation of sample surveys, advances in the theory of Neyman's smooth test, and methods for pre-test and biased estimation. It includes discussions ofsample size requirements for estimation in SUR models, innovative developments in nonparametric models, and more.
Author:
Publisher:
ISBN:
Category : Sampling (Statistics)
Languages : en
Pages :
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