Author: Kazumitsu NawataPublisher:
ISBN: 9780864223876
Category : Correlation (Statistics)
Languages : en
Pages : 6
Book Description
Estimation of Sample-selection Models by the Maximum Likelihood Method
Author: Kazumitsu NawataPublisher:
ISBN: 9780864223876
Category : Correlation (Statistics)
Languages : en
Pages : 6
Book Description
Maximum Likelihood Estimation for Sample Surveys
Author: Raymond L. ChambersPublisher: CRC Press
ISBN: 1420011359
Category : Mathematics
Languages : en
Pages : 374
Book Description
Sample surveys provide data used by researchers in a large range of disciplines to analyze important relationships using well-established and widely used likelihood methods. The methods used to select samples often result in the sample differing in important ways from the target population and standard application of likelihood methods can lead to
Estimation of Spatial Sample Selection Models
Author: Renata RabovicEstimation of Spatial Sample Selection Models
Author: Renata RabovičSpecification and Estimation of Count Data Regression and Sample Selection Models
Author: Lung-fei LeeDynamic Nonlinear Econometric Models
Author: Benedikt M. PötscherPublisher: Springer Science & Business Media
ISBN: 3662034867
Category : Business & Economics
Languages : en
Pages : 307
Book Description
Many relationships in economics, and also in other fields, are both dynamic and nonlinear. A major advance in econometrics over the last fifteen years has been the development of a theory of estimation and inference for dy namic nonlinear models. This advance was accompanied by improvements in computer technology that facilitate the practical implementation of such estimation methods. In two articles in Econometric Reviews, i.e., Pötscher and Prucha {1991a,b), we provided -an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a review of the literature up to the beginning of this decade. Among others, the class of M-estimators contains least mean distance estimators (includ ing maximum likelihood estimators) and generalized method of moment estimators. The present book expands and revises the discussion in those articles. It is geared towards the professional econometrician or statistician. Besides reviewing the literature we also presented in the above men tioned articles a number of then new results. One example is a consis tency result for the case where the identifiable uniqueness condition fails.
Maximum Likelihood Estimation
Author: Scott R. EliasonPublisher: SAGE
ISBN: 9780803941076
Category : Mathematics
Languages : en
Pages : 100
Book Description
This is a short introduction to Maximum Likelihood (ML) Estimation. It provides a general modeling framework that utilizes the tools of ML methods to outline a flexible modeling strategy that accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models linking endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, the author discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.
Maximum Likelihood Estimation of Misspecified Models
Author: T. FombyPublisher: Elsevier
ISBN: 9780762310753
Category : Business & Economics
Languages : en
Pages : 280
Book Description
Comparative study of pure and pretest estimators for a possibly misspecified two-way error component model / Badi H. Baltagi, Georges Bresson, Alain Pirotte -- Estimation, inference, and specification testing for possibly misspecified quantile regression / Tae-Hwan Kim, Halbert White -- Quasimaximum likelihood estimation with bounded symmetric errors / Douglas Miller, James Eales, Paul Preckel -- Consistent quasi-maximum likelihood estimation with limited information / Douglas Miller, Sang-Hak Lee -- An examination of the sign and volatility switching arch models under alternative distributional assumptions / Mohamed F. Omran, Florin Avram -- estimating a linear exponential density when the weighting matrix and mean parameter vector are functionally related / Chor-yiu Sin -- Testing in GMM models without truncation / Timothy J. Vogelsang -- Bayesian analysis of misspecified models with fixed effects / Tiemen Woutersen -- Tests of common deterministic trend slopes applied to quarterly global temperature data / Thomas B. Fomby, Timothy J. Vogelsang -- The sandwich estimate of variance / James W. Hardin -- Test statistics and critical values in selectivity models / R. Carter Hill, Lee C. Adkins, Keith A. Bender -- Introduction / Thomas B Fomby, R. Carter Hill.
Nonparametric and Semiparametric Methods in Econometrics and Statistics
Author: William A. BarnettPublisher: Cambridge University Press
ISBN: 9780521424318
Category : Business & Economics
Languages : en
Pages : 512
Book Description
Papers from a 1988 symposium on the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data.
Maximum Likelihood Estimation of Endogenous Switching and Sample Selection Models for Binary, Count, and Ordinal Variables
Author: Alfonso MirandaPublisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 28
Book Description