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Discrete Choice Methods with Simulation

Discrete Choice Methods with Simulation PDF Author: Kenneth Train
Publisher: 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.

Discrete Choice Methods with Simulation

Discrete Choice Methods with Simulation PDF Author: Kenneth Train
Publisher: 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.

Handbook of Econometrics

Handbook of Econometrics PDF Author: J.J. Heckman
Publisher: Elsevier
ISBN: 0080524796
Category : Business & Economics
Languages : en
Pages : 737

Book Description
The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics. Comprehensive surveys, written by experts, discuss recent developments at a level suitable for professional use by economists, econometricians, statisticians, and in advanced graduate econometrics courses. For more information on the Handbooks in Economics series, please see our home page on http://www.elsevier.nl/locate/hes

Discrete Choice Methods with Simulation

Discrete Choice Methods with Simulation PDF Author: Kenneth E. Train
Publisher: Cambridge University Press
ISBN: 1139480375
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. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This 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.

Nonlinear Statistical Modeling

Nonlinear Statistical Modeling PDF Author: Takeshi Amemiya
Publisher: Cambridge University Press
ISBN: 9780521662468
Category : Business & Economics
Languages : en
Pages : 472

Book Description
This collection investigates parametric, semiparametric, nonparametric, and nonlinear estimation techniques in statistical modeling.

Simulation-based Econometric Methods

Simulation-based Econometric Methods PDF Author: Christian Gouriéroux
Publisher: OUP Oxford
ISBN: 019152509X
Category : Business & Economics
Languages : en
Pages : 190

Book Description
This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach. After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.

Maximum Simulated Likelihood Estimation of Consumer Demand Systems with Binding Non-negativity Constraints

Maximum Simulated Likelihood Estimation of Consumer Demand Systems with Binding Non-negativity Constraints PDF Author: Chihwa Kao
Publisher:
ISBN:
Category :
Languages : en
Pages : 32

Book Description


The Econometrics of Panel Data

The Econometrics of Panel Data PDF Author: Lászlo Mátyás
Publisher: Springer Science & Business Media
ISBN: 3540758925
Category : Business & Economics
Languages : en
Pages : 966

Book Description
This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. Readers discover how econometric tools are used to study organizational and household behaviors as well as other macroeconomic phenomena such as economic growth. The book contains sixteen entirely new chapters; all other chapters have been revised to account for recent developments. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.

Financial Economics

Financial Economics PDF Author: Antonio Mele
Publisher: MIT Press
ISBN: 0262046849
Category : Business & Economics
Languages : en
Pages : 1147

Book Description
A comprehensive reference for financial economics, balancing theoretical explanations, empirical evidence, and the practical relevance of knowledge in the field. This volume offers a comprehensive, integrated treatment of financial economics, tracking the major milestones in the field and providing methodological tools. Doing so, it balances theoretical explanations, empirical evidence, and practical relevance. It illustrates nearly a century of theoretical advances with a vast array of models, showing how real phenomena (and, at times, market practice) have helped economists reformulate existing theories. Throughout, the book offers examples and solved problems that help readers understand the main lessons conveyed by the models analyzed. The book provides a unique and authoritative reference for the field of financial economics. Part I offers the foundations of the field, introducing asset evaluation, information problems in asset markets and corporate finance, and methods of statistical inference. Part II explains the main empirical facts and the challenges these pose for financial economists, which include excess price volatility, market liquidity, market dysfunctionalities, and the countercyclical behavior of market volatility. Part III covers the main instruments that protect institutions against the volatilities and uncertainties of capital markets described in part II. Doing so, it relies on models that have become the market standard, and incorporates practices that emerged from the 2007–2008 financial crisis.

Statistical Inference with Simulated Likelihood Functions

Statistical Inference with Simulated Likelihood Functions PDF Author: Lung-fei Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 56

Book Description


Hybrid Modeling and Simulation

Hybrid Modeling and Simulation PDF Author: Masoud Fakhimi
Publisher: Springer Nature
ISBN: 3031599993
Category :
Languages : en
Pages : 359

Book Description