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 simulated
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. No other book incorporates all these
fields, which have arisen in the past 20 years. The procedures are
applicable in many fields, including energy, transportation,
environmental studies, health, labor, and marketing.
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