Author: Da-Hsiang Donald LienPublisher:
ISBN:
Category :
Languages : en
Pages : 6
Book Description
Pseudo Maximum Likelihood Estimation of Binary Choice Models
Author: Da-Hsiang Donald LienMaximum Likelihood Estimation of a Binary Choice Model with Random Coefficients of Unknown Distribution
Author: Hidehiko IchimuraPublisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 37
Book Description
Semi-nonparametric Maximum Likelihood Estimation of Binary Choice Models with an Application to Labour Force Participation
Author: Siegfried GablerModeling Ordered Choices
Author: William H. GreenePublisher: Cambridge University Press
ISBN: 1139485954
Category : Business & Economics
Languages : en
Pages : 383
Book Description
It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.
Logit and Probit
Author: Vani K. BorooahPublisher: SAGE
ISBN: 9780761922421
Category : Mathematics
Languages : en
Pages : 108
Book Description
Many problems in the social sciences are amenable to analysis using the analytical tools of logit and probit models. This book explains what ordered and multinomial models are and also shows how to apply them to analysing issues in the social sciences.
Trimmed Likelihood-based Estimation in Binary Regression Models
Author: Pavel ČížekPseudo Conditional Maximum Likelihood Estimation of the Dynamic Logit Model for Binary Panel Data
Author: Francesco BartolucciPublisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
We show how the dynamic logit model for binary panel data may be approximated by a quadratic exponential model. Under the approximating model, simple sufficient statistics exist for the subject-specific parameters introduced to capture the unobserved heterogeneity between subjects. The latter must be distinguished from the state dependence which is accounted for by including the lagged response variable among the regressors. By conditioning on the sufficient statistics, we derive a pseudo conditional likelihood estimator for the structural parameters of the dynamic logit model which is very simple to compute. Asymptotic properties of this estimator are derived. Simulation results show that the estimator is competitive in terms of efficiency with estimators very recently proposed in the econometric literature. We also show how the approach may be exploited to construct a Wald-type test for state dependence.
A Guide to Modern Econometrics
Author: Marno VerbeekPublisher: John Wiley & Sons
ISBN: 0470517697
Category : Business & Economics
Languages : en
Pages : 489
Book Description
This revised and updated edition of A Guide to Modern Econometrics continues to explore a wide range of topics in modern econometrics by focusing on what is important for doing and understanding empirical work. It serves as a guide to alternative techniques with the emphasis on the intuition behind the approaches and their practical relevance. New material includes Monte Carlo studies, weak instruments, nonstationary panels, count data, duration models and the estimation of treatment effects. Features of this book include: Coverage of a wide range of topics, including time series analysis, cointegration, limited dependent variables, panel data analysis and the generalized method of moments Empirical examples drawn from a wide variety of fields including labour economics, finance, international economics, environmental economics and macroeconomics. End-of-chapter exercises review key concepts in light of empirical examples.
Maximum Likelihood Estimation of Misspecified Models
Author: T. FombyPublisher: Elsevier
ISBN: 0762310758
Category : Business & Economics
Languages : en
Pages : 266
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.
Discrete Choice Methods with Simulation
Author: Kenneth TrainPublisher: Cambridge University Press
ISBN: 0521766559
Category : Business & Economics
Languages : en
Pages : 399
Book Description
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.