2018
DOI: 10.1016/j.jeem.2018.05.002
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Estimation and welfare analysis from mixed logit models with large choice sets

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Cited by 20 publications
(11 citation statements)
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References 41 publications
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“…Scholars such as, Parsons and Kealy (1992), Parsons and Needelman (1992), Feather (1994), andBayer et al (2007) showed that using alternatives in estimation can obviate such difficulties and produce consistent parameter estimates as also suggested by McFadden (1978). Von Haefen and Domanski (2018) confirmed that larger efficiency losses arise with smaller samples as predicted by theory. Therefore, the mixed logit model is considered to be the most promising state-of-the-art discrete choice model currently available.…”
Section: Literature Reviewsupporting
confidence: 60%
“…Scholars such as, Parsons and Kealy (1992), Parsons and Needelman (1992), Feather (1994), andBayer et al (2007) showed that using alternatives in estimation can obviate such difficulties and produce consistent parameter estimates as also suggested by McFadden (1978). Von Haefen and Domanski (2018) confirmed that larger efficiency losses arise with smaller samples as predicted by theory. Therefore, the mixed logit model is considered to be the most promising state-of-the-art discrete choice model currently available.…”
Section: Literature Reviewsupporting
confidence: 60%
“…To evaluate the welfare effects of a reform on physicians, we calculated, for each doctor, his EV, that is, the minimum payment he would be willing to accept to forego the reform. Our calculations are based on simulation procedures, first suggested in McFadden (1999), and applied in several papers on discrete choice (see, e.g., Creedy et al, 2011; Herriges & Kling, 1999; von Haefen & Domanski, 2018). Of course, these welfare measures are partial as they do not provide information on the impact of a reform neither on patients' welfare (i.e., quality of services) nor on tax payers' welfare.…”
Section: Resultsmentioning
confidence: 99%
“…Here, and while there is no proof that this strategy will generate consistent parameter estimates in non-CL models, it has been found in various studies to only result in small or modest efficiency losses when sampling reasonable numbers of alternatives (e.g. Daly et al 2014;von Haefen and Domanski, 2018).…”
Section: Discussionmentioning
confidence: 91%