Discrete Choice Models
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Author | : Kenneth Train |
Publisher | : Cambridge University Press |
Total Pages | : 399 |
Release | : 2009-07-06 |
Genre | : Business & Economics |
ISBN | : 0521766559 |
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.
Author | : Kenneth Train |
Publisher | : Cambridge University Press |
Total Pages | : 346 |
Release | : 2003-01-13 |
Genre | : Business & Economics |
ISBN | : 9780521017152 |
Author | : Moshe E. Ben-Akiva |
Publisher | : MIT Press |
Total Pages | : 424 |
Release | : 1985 |
Genre | : Architecture |
ISBN | : 9780262022170 |
Discrete Choice Analysis presents these results in such a way that they are fully accessible to the range of students and professionals who are involved in modelling demand and consumer behavior in general or specifically in transportation - whether from the point of view of the design of transit systems, urban and transport economics, public policy, operations research, or systems management and planning. The methods of discrete choice analysis and their applications in the modelling of transportation systems constitute a comparatively new field that has largely evolved over the past 15 years. Since its inception, however, the field has developed rapidly, and this is the first text and reference work to cover the material systematically, bringing together the scattered and often inaccessible results for graduate students and professionals. Discrete Choice Analysis presents these results in such a way that they are fully accessible to the range of students and professionals who are involved in modelling demand and consumer behavior in general or specifically in transportation - whether from the point of view of the design of transit systems, urban and transport economics, public policy, operations research, or systems management and planning. The introductory chapter presents the background of discrete choice analysis and context of transportation demand forecasting. Subsequent chapters cover, among other topics, the theories of individual choice behavior, binary and multinomial choice models, aggregate forecasting techniques, estimation methods, tests used in the process of model development, sampling theory, the nested-logit model, and systems of models. Discrete Choice Analysis is ninth in the MIT Press Series in Transportation Studies, edited by Marvin Manheim.
Author | : David A. Hensher |
Publisher | : Routledge |
Total Pages | : 280 |
Release | : 2018-04-09 |
Genre | : Business & Economics |
ISBN | : 1351140744 |
Originally published in 1981. Discrete-choice modelling is an area of econometrics where significant advances have been made at the research level. This book presents an overview of these advances, explaining the theory underlying the model, and explores its various applications. It shows how operational choice models can be used, and how they are particularly useful for a better understanding of consumer demand theory. It discusses particular problems connected with the model and its use, and reports on the authors’ own empirical research. This is a comprehensive survey of research developments in discrete choice modelling and its applications.
Author | : Simon P. Anderson |
Publisher | : MIT Press |
Total Pages | : 454 |
Release | : 1992 |
Genre | : Business & Economics |
ISBN | : 9780262011280 |
"The discrete choice approach provides an ideal framework for describing the demands for differentiated products and can be used for studying most product differentiation models in the literature. By introducing extra dimensions of product heterogeneity, the framework also provides richer models of firm location and product selection."--BOOK JACKET.
Author | : Martine Labbe |
Publisher | : Springer Science & Business Media |
Total Pages | : 364 |
Release | : 1998-10-20 |
Genre | : Business & Economics |
ISBN | : 9783540646525 |
This is a collection of state-of-the-art surveys on topics at the interface between transportation modeling and operations research given by leading international experts. Based on contributions to a NATO workshop, the surveys are up-to-date and rigorous presentations or applications of quantitative methods in the area. The subjects covered include dynamic traffic simulation techniques and dynamic routing in congested networks, operation and control of traffic management tools, optimized transportation data collection, and vehicle routing problems.
Author | : David A. Hensher |
Publisher | : Cambridge University Press |
Total Pages | : 1219 |
Release | : 2015-06-11 |
Genre | : Business & Economics |
ISBN | : 1107092647 |
A fully updated second edition of this popular introduction to applied choice analysis, written for graduate students, researchers, professionals and consultants.
Author | : Caspar G. Chorus |
Publisher | : Springer Science & Business Media |
Total Pages | : 60 |
Release | : 2012-04-05 |
Genre | : Business & Economics |
ISBN | : 3642291511 |
This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. This tutorial is written for students, scholars and practitioners who have a basic background in choice modeling in general and RUM-modeling in particular. It has been taken care of that all concepts and results should be clear to readers that do not have an advanced knowledge of econometrics.
Author | : Professor Laurie A Garrow |
Publisher | : Ashgate Publishing, Ltd. |
Total Pages | : 327 |
Release | : 2012-10-01 |
Genre | : Technology & Engineering |
ISBN | : 1409486338 |
In recent years, airline practitioners and academics have started to explore new ways to model airline passenger demand using discrete choice methods. This book provides an introduction to discrete choice models and uses extensive examples to illustrate how these models have been used in the airline industry. These examples span network planning, revenue management, and pricing applications. Numerous examples of fundamental logit modeling concepts are covered in the text, including probability calculations, value of time calculations, elasticity calculations, nested and non-nested likelihood ratio tests, etc. The core chapters of the book are written at a level appropriate for airline practitioners and graduate students with operations research or travel demand modeling backgrounds. Given the majority of discrete choice modeling advancements in transportation evolved from urban travel demand studies, the introduction first orients readers from different backgrounds by highlighting major distinctions between aviation and urban travel demand studies. This is followed by an in-depth treatment of two of the most common discrete choice models, namely the multinomial and nested logit models. More advanced discrete choice models are covered, including mixed logit models and generalized extreme value models that belong to the generalized nested logit class and/or the network generalized extreme value class. An emphasis is placed on highlighting open research questions associated with these models that will be of particular interest to operations research students. Practical modeling issues related to data and estimation software are also addressed, and an extensive modeling exercise focused on the interpretation and application of statistical tests used to guide the selection of a preferred model specification is included; the modeling exercise uses itinerary choice data from a major airline. The text concludes with a discussion of on-going customer modeling research in aviation. Discrete Choice Modelling and Air Travel Demand is enriched by a comprehensive set of technical appendices that will be of particular interest to advanced students of discrete choice modeling theory. The appendices also include detailed proofs of the multinomial and nested logit models and derivations of measures used to represent competition among alternatives, namely correlation, direct-elasticities, and cross-elasticities.
Author | : Riccardo Scarpa |
Publisher | : Springer Science & Business Media |
Total Pages | : 456 |
Release | : 2005-08-12 |
Genre | : Business & Economics |
ISBN | : 9781402036835 |
Simulation methods are revolutionizing the practice of applied economic analysis. In this book, leading researchers from around the world discuss interpretation issues, similarities and differences across alternative models, and propose practical solutions for the choice of the model and programming. Case studies show the practical use and the results brought forth by the different methods.