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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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The internalization of externalities in the production of electricity: Willingness to pay for the attributes of a policy for renewable energy
TL;DR: In this article, the authors investigated the willingness to pay of a sample of residents of Bath, England, for a hypothetical program that promotes the production of renewable energy using choice experiments, and found that respondents are in favour of a policy for renewable energy and that they attach a high value to a policy that brings private and public benefits in terms of climate change and energy security benefits.
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A note on modeling pedestrian-injury severity in motor-vehicle crashes with the mixed logit model.
TL;DR: Using police-reported collision data from 1997 through 2000 from North Carolina, several factors were found to more than double the average probability of fatal injury for pedestrians in motor-vehicle crashes including darkness without streetlights, speeding involved, and collisions involving a motorist who had been drinking.
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Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles
TL;DR: In this paper, stated preference (SP) data from 535 Canadian and 408 Californian vehicle owners under different hypothetical market conditions was collected from the same respondents by eliciting the year, make and model of recent vehicle purchases from regions with different degrees of HEV popularity.
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Some evidence that women are more mobile than men: gender differences in u.k. graduate migration behavior
TL;DR: In this article, the authors employ dichotomous, multinomial and conditional logit models to analyze the employment-migration behavior of some 380,000 U.K. university graduates.
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A Two-Sided, Empirical Model of Television Advertising and Viewing Markets
TL;DR: A two-sided model of the television industry is proposed that estimates viewer demand for programs on one side and advertiser demand for audiences on the other and suggests that advertiser preferences influence network choices more strongly than viewer preferences.
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.