Discrete Choice Models

Regular price €62.99
Title
A01=Alfred Galichon
actual datasets
Author_Alfred Galichon
Bayesian estimation
Behavioral Economics
binary choice
Category=KCH
Category=PBD
choice alternatives
choice experiments
computational issues
conditional logit
conjoint analysis
consumer choice
Crisis and Recession
decision-making
demand estimation
discrete choice experiments
discrete choice models
dynamic discrete choice
econometric models
Economic Forecasts
Economic History
economics
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_nobargain
eq_non-fiction
estimation techniques
expectation maximization
Expectations
Experiences
forthcoming
generalized linear models
generalized method of moments
gradient descent
graduate coursework
Growth and Innovation
hedonic markets
Hessian matrix
inference methods
Inflation
information matrix
international trade gravity
likelihood function
log-likelihood
logistic regression
logit model
marketing
matching models
mathematical tools
maximum likelihood estimation
MCMC methods
method of moments
mixed logit
multinomial choice
multinomial logit
nested logit
Newton-Raphson
numerical optimization
optimization
ordered logit
ordered probit
Poisson regression
political science
practical applicability
probit model
Python code
quasi-Newton methods
random utility
revealed preference
Risk and Uncertainty
score function
simulated datasets
simulation methods
social sciences
stated preference
theoretical clarity
utility maximization

Product details

  • ISBN 9780691221809
  • Dimensions: 156 x 235mm
  • Publication Date: 21 Apr 2026
  • Publisher: Princeton University Press
  • Publication City/Country: US
  • Product Form: Hardback
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A foundational treatment of discrete choice models, with a focus on random utility models

Discrete choice models are essential tools for understanding decision-making when individuals must choose among alternatives. They have applications across the social sciences, notably in economics, marketing, and political science. This book offers a foundational treatment of discrete choice models, introducing the logit model and its generalizations, logistic and Poisson regressions, and generalized linear models, and demonstrates their use in analyzing important econometric models. These include international trade gravity, demand estimation, matching with and without transfers, hedonic markets, and dynamic discrete choice. Bridging theoretical clarity and practical applicability, the book is suitable for use in graduate-level coursework and will be an essential resource for researchers and practitioners.

• Extensive coverage of computational issues, focusing on optimization and the reformulation as generalized linear models
• Emphasis on econometric questions, including simulation, estimation, and inference methods, with estimation techniques based on both simulated and actual datasets
• Substantial set of exercises and problems at the end of each chapter
• Two appendixes, with one covering the mathematical tools needed to understand the material, and the other the Python code examples

Alfred Galichon is professor of economics and of mathematics at New York University. A pioneer of the use of optimal transport theory in econometrics, he is the author of a monograph on the topic, Optimal Transport Methods in Economics (Princeton).