2017
DOI: 10.18637/jss.v079.i02
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Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package

Abstract: This paper introduces the package gmnl in R for estimation of multinomial logit models with unobserved heterogeneity across individuals for cross-sectional and panel (longitudinal) data. Unobserved heterogeneity is modeled by allowing the parameters to vary randomly over individuals according to a continuous, discrete, or discrete-continuous mixture distribution, which must be chosen a priori by the researcher. In particular, the models supported by gmnl are the multinomial or conditional logit, the mixed mult… Show more

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Cited by 168 publications
(98 citation statements)
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“…14 However, unlike Xuan et al (2017), our model here includes interaction effects between coral cover and environmental quality as well as between coral cover and job loss variables. 15 The MXL model is estimated in R using the "gmnl"-package (Sarrias & Daziano, 2016) and 1000 standard Halton draws.…”
Section: Tourism Value V(m)mentioning
confidence: 99%
“…14 However, unlike Xuan et al (2017), our model here includes interaction effects between coral cover and environmental quality as well as between coral cover and job loss variables. 15 The MXL model is estimated in R using the "gmnl"-package (Sarrias & Daziano, 2016) and 1000 standard Halton draws.…”
Section: Tourism Value V(m)mentioning
confidence: 99%
“…We use the BIC criteria for choosing the number of latent classes, which is the most conservative criteria in that it penalizes the most for additional parameters (Morey and Thacher, 2012). The latent class models were estimated using the package gmnl (Sarrias & Daziano, 2015) of the R Development Core Team.…”
Section: Samplementioning
confidence: 99%
“…Finally, following previous research where a betweensubject treatments approach was implemented (e.g., Alemu & Olsen, 2018;Bazzani et al, 2017;de-Magistris, Gracia, & Nayga, 2013;Lin, Ortega, & Caputo, 2018), we ran pooled models using responses from control and treatment group pairs as a robustness test of the impact of information on mWTP formation. All models were estimated using functions from the "gmnl" package for R (Sarrias & Daziano, 2017).…”
Section: Econometric Analysis Of Rcementioning
confidence: 99%