Discrete Choice Methods with Simulation
| Author | : | |
| Rating | : | 4.55 (539 Votes) |
| Asin | : | 0521747384 |
| Format Type | : | paperback |
| Number of Pages | : | 400 Pages |
| Publish Date | : | 2016-03-18 |
| Language | : | English |
DESCRIPTION:
Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. 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)
No other book incorporates all these fields, which have arisen in the past 25 years. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. 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. 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. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. Simulation-assisted estimation procedures are investigated
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. Ken Train's many papers have made a large contribution to this literature. The chapters on simulation and recent developments such as mixed logit are most lucid. 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. The book is blessed by Kenneth Train's unique gift for simplifying and explaini
excellent discussion of what the models mean JVerkuilen 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 surroundin. "A must have" according to izhak. Classics and a must have for anyone who does or aspires to do any structural work in Economics or Marketing.. Happy Customer Enough math to solidify the explanation and enough text to make it readable. Very well done.