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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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Estimation of forest values using choice modeling: An application to Spanish forests
Raul Brey,Pere Riera,Joan Mogas +2 more
TL;DR: In this article, a choice modeling application of forest goods and services valuation for an afforestation program in the Northeast of Spain has been presented, and the results from a random parameter logit model reveal that on average, individuals would annually pay an average of 11.79 euros for the forests to sequester 68,000 tones of CO2, 0.12 euros for delaying the loss of land productivity for ten years, and 6.33 euros from picnic users for being allowed to picnic in the new forests.
Posted Content
Regulation and Welfare: Evidence from Paragraph IV Generic Entry in the Pharmaceutical Industry
Lee Branstetter,Lee Branstetter,Chirantan Chatterjee,Matthew J. Higgins,Matthew J. Higgins,Matthew J. Higgins +5 more
TL;DR: In this article, the welfare effects of accelerated generic entry via patent-protected drugs challenges are investigated. But the authors focus on the effect of these challenges on the overall market and do not consider the impact on individual consumers.
Posted Content
An Analysis of Travel Demand in Japan's Intercity Market Empirical Estimation and Policy Simulation
Xiaowen Fu,Tae H. Oum,Jia Yan +2 more
TL;DR: In this paper, a travel demand model was used to estimate the effects of introducing super high-speed-rail (HSR), and alternative levels of CO 2 emission taxation on the demands for airline and HSR modes.
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Context effects and heterogeneity in voluntary carbon offsetting – a choice experiment in Switzerland
Julia Blasch,Mehdi Farsi +1 more
TL;DR: In a choice experiment among more than a thousand Swiss consumers, this paper analyzed how the propensity to offset varies with consumption contexts and offset project attributes and found that consumers are not only responsive to project type and quality aspects, but also to the consumption context.
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Using best–worst scaling to explore perceptions of relative responsibility for ensuring food safety
Seda Erdem,Dan Rigby,Ada Wossink +2 more
TL;DR: In this article, the authors examine stakeholders' perceptions of the share of the overall responsibility of each stage in the food supply chain has in ensuring that the meat people cook and eat at home is safe to consume.
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.