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Discrete Choice Methods with Simulation
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In this paper, the authors describe the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation, and compare simulation-assisted estimation procedures, including maximum simulated likelihood, method of simulated moments, and methods of simulated scores.Abstract:
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.read more
Citations
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Generalized random utility model
Joan L. Walker,Moshe Ben-Akiva +1 more
TL;DR: A practical, generalized model that integrates many enhancements that have been made to RUM is presented that encompasses all models, describes each enhancement, and shows relationships between models including how they can be integrated.
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Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability
TL;DR: The authors applied mixed logit to combined revealed and stated preference data on commuter choices of whether to pay a toll for congestion free express travel and found that motorists exhibit high values of travel time and reliability and substantial heterogeneity in those values.
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A multiple discrete–continuous extreme value model: formulation and application to discretionary time-use decisions
TL;DR: This paper derives and formulates a utility theory-based model for discrete/continuous choice that assumes diminishing marginal utility as the level of consumption of any particular alternative increases (i.e., satiation), and has a surprisingly simple and elegant closed form expression for the discrete-continuous probability of not consuming certain alternatives and consuming given levels of the remaining alternatives.
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Designing efficient stated choice experiments in the presence of reference alternatives
TL;DR: In this article, the authors examined various design strategies that might be employed to construct statistically more efficient stated choice designs in the presence of a reference alternative in a choice set, and concluded that D-efficiency design strategies produce significantly improved results, in a statistical sense of relative efficiency, than the more traditional orthogonal design.
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Economic Analysis for Ecosystem Service Assessments
Ian J. Bateman,Ian J. Bateman,Ian J. Bateman,Georgina M. Mace,Carlo Fezzi,Giles Atkinson,R. Kerry Turner +6 more
TL;DR: A single period during which ecological stocks are maintained at sustainable levels is considered and economic approaches to the incorporation of depleting ecological assets with a particular focus upon stocks which exhibit thresholds below which restoration is compromised are considered.
References
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Maximum likelihood from incomplete data via the EM algorithm
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Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Journal ArticleDOI
Equation of state calculations by fast computing machines
TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
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Sample Selection Bias as a Specification Error
TL;DR: In this article, the bias that results from using non-randomly selected samples to estimate behavioral relationships as an ordinary specification error or "omitted variables" bias is discussed, and the asymptotic distribution of the estimator is derived.