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Discrete Choice Methods with Simulation [Hardcover]

Kenneth E. Train (Author)
5.0 out of 5 stars  See all reviews (5 customer reviews)

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Book Description

January 13, 2003
Focusing on the many advances that are made possible by simulation, this book describes the new generation of discrete choice methods. 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. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

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Editorial Reviews

Review

"Simulation methods have unshackled discrete choice analysis, breaking down the computational barriers to use of plausible, interpretable models. Kenneth Train provides an excellent road map for both econometric specialists and practitioners through this comprehensive, readable treatment that pulls together the research literature and provides many new and useful results." Daniel McFadden, Nobel Laureate, University of California, Berkeley

"An outstanding textbook for advanced students and a reference for experienced practitioners of discrete choice analysis. The text covers modern simulation methods that advanced choice modelers should know. The book is blessed by Kenneth Train's unique gift for simplifying and explaining the topic." Moshe Ben-Akiva, Massachusetts Institute of Technology

"A must have, must read book for academics and practitioners interested in understanding, modelling and predicting decision-making and choice behavior. As we have come to expect from Ken, his new book makes very complex topics accessible to a wide audience. The book covers the basics through to leading-edge thought and work in complex model systems using Bayesian and simulation estimation methods. But wait there's more! There's `Ken the movie'! You also can watch and listen to Ken's lectures on each topic via his UC Berkeley website and access his lecture notes. An unbeatable package for serious students that sets a new standard in educational communication for the field of probabilistic discrete choice modelling." Jordan Louviere, University of Technology, Sydney, Australia

"Ken Train's book provides outstanding coverage of the most advanced elements of the estimation and usage of discrete choice models that require simulation to take account of randomness in the population under study. His writing is clear and understandable providing both the new and experienced reader with excellent insights into and understanding of all aspects of these new and increasingly important methods." Frank S. Koppelman, Northwestern University

"This is a masterful book, authored by one of the leading contributors to discrete choice methods and analysis. No other book covers this ground with such up-to-date detail in respect of theory and implementation. The chapters on simulation and recent developments such as mixed logit are most lucid. As a text or reference work this volume should have currency for a long time. It will appeal to the practitioner as much as to the specialist researcher who has been in this field for many years." David Hensher, The University of Sydney

"Simulation based estimation is a major advance in econometrics and discrete choice modeling. The technique has revolutionized both classical and Bayesian analysis. Ken Train's many papers have made a large contribution to this literature. Discrete Choice Methods with Simulation collects these results in a comprehensive, up-to-date source, with chapters on behavioral foundations, theoretical and practical aspects of estimation and a variety of applications. This book is a thoroughly enjoyable blend of theory, analysis, and case studies; it is a complete reference for developers and practitioners." William Greene, New York University

"The author's writing is clear and lucid. He succeeds in providing the reader with excellent insights and understanding of the methodology. This book is an excellent blend of theory, analysis, and real problems. Because of this, I would rate it as an exceptionally valuable resource." Journal of the American Statistical Association, Karla V. Ballman, Mayo Clinic College of Medicine

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. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

Product Details

  • Hardcover: 342 pages
  • Publisher: Cambridge University Press (January 13, 2003)
  • Language: English
  • ISBN-10: 0521816963
  • ISBN-13: 978-0521816960
  • Product Dimensions: 9.2 x 6.2 x 0.9 inches
  • Shipping Weight: 1.2 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #2,841,516 in Books (See Top 100 in Books)

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14 of 14 people found the following review helpful:
5.0 out of 5 stars excellent discussion of what the models mean, March 16, 2005
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JVerkuilen (BAYSIDE, NY, United States) - See all my reviews
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If I could give this book six stars I would. It's simply one of the best statistics books I've ever read.

This book is very well-written by one of the experts in the field. It covers logit models and the various generalizations (GEV, mixed logit, probit, etc.) in detail, along with a thorough discussion of modern estimation of these models. What I find most useful about it is that the words-to-equations density is highly favorable. The equations you need are there, but the words you need are there too, making sure you understand the model assumptions inside and out. Each equation is explained thoroughly and the surrounding discussion probes the model to bring the reader to a critical understanding of what exactly is implied by the model. Too often complex statistical models are treated in a "black box" fashion. The dirty little secret is that it's easier for the author to do this. Train doesn't take the easy way out. The fact that his web site has truly excellent support--including a large number of webinars in addition to the more usual papers, software, etc.--makes this book a doubly valuable item. See http://elsa.berkeley.edu/~train/distant.html for even more.
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11 of 12 people found the following review helpful:
5.0 out of 5 stars Probably the best of its kind. Good for MS students and up, April 23, 2005
-Enjoyable read
-Does not assume PhD level of econometrics
-Explanations are clear and concise

Actually, an advanced undergrad may find this book usefull as well.
Is this the best discrete choice methods book ever published?
Let y = 1 or 0 where 1 = yes, this is the best and 0 = No, the book is not the best. Also let P = Prob (y=1). My results show P = 0.98 (see forthcoming Econometrica article).
While finishing a Master's Thesis in applied econ which focuses on a multinomial logit model, I have sought good info on this topic. Not having gone through the rigors of a PhD program, I have gone through many of the important books and articles which address discrete choice modeling methods some of which address a post-doc audience only. Dr. Train's is by far the best I have encountered. His explanations are concise yet not too dense (see Amemiya). I first encountered many of the concepts in other publications but did understand them until reading Train's book. In my opinion Train has that rare quality of being, not only an exceptional economist, but quite enjoyable to read.
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7 of 7 people found the following review helpful:
5.0 out of 5 stars An excellent and thorough book, March 8, 2006
This book is one of the best for introduction to Discrete choice models. I had been using Ben-Akiva & Lerman, but feel this book should be read along with that one for a better understanding of choice models. Also, Train covers recent advances in the field and provides a good introduction to Halton draws. He really makes sure you get the concepts and the online lecture series are really excellent.
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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
average representative utility, mixed logit probability, large gas cars, iid extreme value, sampled decision maker, logit formula, sample size rises, mixed logit model, random taste variation, overlapping nests, unbiased simulator, extreme value term, unobserved utility, unobserved portion, proportional substitution, distributed extreme value, average outer product, standard logit model, simulated approximation, simulated probability, simulation bias, joint normal density, maximum simulated likelihood, score simulators, unobserved factors
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Behavioral Models, Individual-Level Parameters, Properties of Discrete Choice Models, Simulation-Assisted Estimation, Pacific Heights, Estimation Table, Bernstein-von Mises, Monte Carlo, Angler's Guide, Modell Model, Case Study, Nested Logit, Upper Model
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