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Discrete Choice Methods with Simulation - Kenneth E. Train

Discrete Choice Methods with Simulation

Buch | Softcover
400 Seiten
2009 | 2nd Revised edition
Cambridge University Press (Verlag)
978-0-521-74738-7 (ISBN)
CHF 78,50 inkl. MwSt
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Each of the major models is covered including logit, generalized extreme value, or GEV, 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. 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.

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.

1. Introduction; Part I. Behavioral Models: 2. Properties; 3. Logit; 4. GEV; 5. Probit; 6. Mixed logit; 7. Variations on a theme; Part II. Estimation: 8. Numerical maximization; 9. Drawing from densities; 10. Simulation-assisted estimation; 11. Individual-level parameters; 12. Bayesian procedures; 13. Endogeneity; 14. EM algorithms.

Zusatzinfo 17 Tables, unspecified; 46 Line drawings, unspecified
Verlagsort Cambridge
Sprache englisch
Maße 152 x 229 mm
Gewicht 530 g
Themenwelt Mathematik / Informatik Mathematik
Wirtschaft Volkswirtschaftslehre Ökonometrie
ISBN-10 0-521-74738-4 / 0521747384
ISBN-13 978-0-521-74738-7 / 9780521747387
Zustand Neuware
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