Download or read book Optimal Asymptotic Properties of Maximum Likelihood Estimators of Parameters of Some Ecometric Models written by Mary Kathleen Vickers and published by . This book was released on 1979 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimal Asymptotic Properties of Maximum Likelihood Estimators of Parameters of Some Econometric Models written by Mary Kathleen Vickers and published by . This book was released on 1977 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Four theorems are proven, which simplify the application to econometric models of Weiss's theorem on asymptotic properties of maximum likelihood estimators in nonstandard cases. The theorems require, roughly: the uniform convergence in any compact sets of the unknown parameters of the expection of the Hessian matrix of the log likelihood function; and the uniform convergence to 0 in the same sense of the variance of the same quantities. The fourth theorem allows one to conclude that the optimal properties hold on an image set of the parameters when the map satisfies certain smoothness conditions, and the first three theorems are satisfied for the original parameter set. These four theorems are applied to autoregressive models, nonlinear models, systems of equations, and probit and logit models to infer optimal asymptotic properties. (Author).
Download or read book Asymptotic Properties of Econometric Estimators written by Jeffrey M. Wooldridge and published by . This book was released on 1986 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Properties of Maximum Likelihood Estimators in the General Sampling Framework and Some Results in Non normal Linear Regression written by Robert Ernest Tarone and published by . This book was released on 1974 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Analysis for Nonlinear Spatial and Network Econometric Models written by Xingbai Xu and published by . This book was released on 2016 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial econometrics has been obtained more and more attention in the recent years. The spatial autoregressive (SAR) model is one of the most widely used and studied models in spatial econometrics. So far, most studies have been focused on linear SAR models. However, some types of spatial or network data, for example, censored data or discrete choice data, are very common and useful, but not suitable to study by a linear SAR model. That is why I study an SAR Tobit model and an SAR binary choice model in this dissertation. Chapter 1 studies a Tobit model with spatial autoregressive interactions. We consider the maximum likelihood estimation (MLE) for this model and analyze asymptotic properties of the estimator based on the spatial near-epoch dependence (NED) of the dependent variable process generated from the model structure. We show that the MLE is consistent and asymptotically normally distributed. Monte Carlo experiments are performed to verify finite sample properties of the estimator. Chapter 2 extends the MLE estimation of the SAR Tobit model studied in Chapter 1 to distribution-free estimation. We examine the sieve MLE of the model, where the disturbances are i.i.d. with an unknown distribution. This model can be applied to spatial econometrics and social networks when data are censored. We show that related variables are spatial NED. An important contribution of this chapter is that I develop some exponential inequalities for spatial NED random fields, which are also useful in other semiparametric studies when spatial correlation exists. With these inequalities, we establish the consistency of the estimator. Asymptotic distributions of structural parameters of the model are derived from a functional central limit theorem and projection. Simulations show that the sieve MLE can improve the finite sample performance upon misspecified normal MLEs, in terms of reduction in the bias and standard deviation. As an empirical application, we examine the school district income surtax rates in Iowa. Our results show that the spatial spillover effects are significant, but they may be overestimated if disturbances are restricted to be normally distributed. Chapter 3 studies the method of simulated moments (MSM) estimation of a binary choice game model with network links, where the network peer effects are non-negative, and there might be only one or few networks in the sample. The proposed estimation method can be applied to studies with binary dependent variables in the fields of empirical IO, social network and spatial econometrics. The model might have multiple Nash equilibria. We assume that the maximum Nash equilibrium, which always exists and is strongly coalition-proof and Pareto optimal, is selected. The challenging econometric issues are the possible correlation among all dependent variables and the discontinuous functional form of our simulated moments. We overcome these challenges via the empirical process theory and derive the spatial NED of the dependent variable. We establish a criterion for an NED random field to be stochastically equicontinuous and we apply it to develop the consistency and asymptotic normality of the estimator. We examine computational issues and finite sample properties of the MSM by some Monte Carlo experiments.
Download or read book Asymptotic Efficiency and Higher Order Efficiency of the Limited Information Maximum Likelihood Estimator in Large Econometric Models written by Naoto Kunitomo and published by . This book was released on 1981 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Properties of Maximum Likelihood Estimators in a Nonlinear Regression Model with Unknown Parameters in the Disturbance Covariance Matrix written by R. D. H. Heijmans and published by . This book was released on 1977 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Properties of Maximum Likelihood Estimators in the Nonlinear Regression Model when the Errors are Neither Independent for Identically Distributed written by R. D. H. Heijmans and published by . This book was released on 1982 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Properties of Induced Maximum Likelihood Estimates of Nonlinear Models for Item Response Variables The Finite Generic Item Pool Case written by Douglas H. Jones and published by . This book was released on 1985 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: The progress of modern mental test theory depends very much on the techniques of maximum likelihood estimation, and many popular applications make use of likelihoods induced by logistic item response models. While, in reality, item responses are nonreplicate within a single examinee and the logistic models are only ideal, practitioners make inferences using the asymptotic distribution of the maximum likelihood estimator derived as if item responses were replicated and satisfied their ideal model. This article proposes a sample space acknowledging these two realities and derives the asymptotic distribution of the induced maximum likelihood estimator. This article assumes that items, while sampled from an infinite set of items, have but a finite domain of alternate response functions: this situation is the case of the finite-generic-item-pool. Using the proposed sample space, the article applies the statistical functional approach of von Mises to derive the influence curve of the maximum likelihood estimator; to discuss related robustness properties; and to derive new classes of resistent estimators. The aim is revealing the value of these methods for uncovering the relative merits of different item response functions. Proofs and mathematical derivations are minimized to increase the accessability of this complex subject. (Author).
Download or read book Asymptotic Properties and Computation of Maximum Likelihood Estimates in the Mixed Model of the Analysis of Variance written by Stanford University. Department of Statistics and published by . This book was released on 1973 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem considered is the estimation of the parameters in the mixed model of the analysis of variance, assuming normality of the random effects and errors. Both asymptotic properties of such estimates as the size of the design increases and numerical procedures for their calculation are discussed. Estimation is carried out by the method of maximum likelihood. It is shown that there is a sequence of roots of the likelihood equations which is consistent, asymptotically normal and asymptotically efficient in the sense of attaining the Cramer-Rao lower bound for the covariance matrix as the size of the design increases. This is accomplished using a Taylor series expansion of the log-likelihood. (Modified author abstract).
Download or read book Large Sample Properties of Maximum Likelihood Estimators written by Nicholas Herbert Stern and published by . This book was released on 1980 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Properties of Maximum likelihood estimators in Diffusion Type Models written by H. M. Dietz and published by . This book was released on 1989 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Some Asymptotic Properties of a Maximum Likelihood Estimator written by Billy Joe Attebery and published by . This book was released on 1958 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Efficiency of the Maximum Likelihood Estimators for the Parameters of Certain Stochastic Processes written by Dominique Jean-Marie Nocturne and published by . This book was released on 1970 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: A method of estimation leading to asymptotically efficient estimators for the parameters of certain stochastic processes is developed. Results are applied to estimation of parameters for Markov chains, econometric problems, and continuous time Markov processes.
Download or read book On Some Asymptotic Properties of Maximum Likelihood Estimates and Related Bayes Estimates written by Lucien Marie Le Cam and published by . This book was released on 1953 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1978 with total page 790 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Download or read book Generalized Method of Moments Estimation written by Laszlo Matyas and published by Cambridge University Press. This book was released on 1999-04-13 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: The generalized method of moments (GMM) estimation has emerged as providing a ready to use, flexible tool of application to a large number of econometric and economic models by relying on mild, plausible assumptions. The principal objective of this volume is to offer a complete presentation of the theory of GMM estimation as well as insights into the use of these methods in empirical studies. It is also designed to serve as a unified framework for teaching estimation theory in econometrics. Contributors to the volume include well-known authorities in the field based in North America, the UK/Europe, and Australia. The work is likely to become a standard reference for graduate students and professionals in economics, statistics, financial modeling, and applied mathematics.
