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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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Human Capital, Higher Education and Graduate Migration: An Analysis of Scottish and Welsh Students
TL;DR: In this paper, the sequential migration behavior of some 76,000 Scottish and Welsh students, from their domicile location to the location of their higher education and on to their employment location is modeled.
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The Choice of Sourcing Mechanisms for Business Processes
TL;DR: The study builds on the modular systems theory to posit that modularization of business processes and their underlying information technology (IT) support infrastructures are associated with the choice of sourcing mechanisms for the processes and tests this proposition in a sample of business process sourcing choices made by 93 medium and large U.S. firms.
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Fast-Food Consumption and the Ban on Advertising Targeting Children: The Quebec Experience
Tirtha Pratim Dhar,Kathy Baylis +1 more
TL;DR: In this paper, the authors studied the effect of fast-food advertising targeting children in the Canadian province of Quebec and found that the advertising ban's effectiveness was not a result of a decrease in fast food expenditures per week but rather of the decrease in purchase propensity.
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Variational Inference for Large-Scale Models of Discrete Choice
Michael Braun,Jon McAuliffe +1 more
TL;DR: Extensive simulations, along with an analysis of real-world data, demonstrate that variational methods achieve accuracy competitive with Markov chain Monte Carlo at a small fraction of the computational cost.
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Occupant injury severities in hybrid-vehicle involved crashes: A random parameters approach with heterogeneity in means and variances
Puttipan Seraneeprakarn,Shuaiqi Huang,Venkataraman N. Shankar,Fred L. Mannering,Narayan Venkataraman,John Milton +5 more
TL;DR: In this article, the authors used a sample of hybrid-vehicle-involved crashes and estimates a mixed logit model of the resulting injury level of the most severely injured occupant in the crash, while accounting for possible heterogeneity in the means and variances of model parameters.
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.