A Bayesian mixed logit-probit model for multinomial choice
By Martin Burda, Matthew Harding, Jerry A. Hausman. 2008
141 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Economics and Econometrics, Marketing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Economics and Econometrics
- Michael P. Keane
- Nada Wasi
- Stephane Hess
- Jordan J. Louviere
- Kenneth Train
- Denzil G. Fiebig
- Chandra R. Bhat
- Matthew Harding
In Marketing
- Michael P. Keane
- Kenneth Train
- Nada Wasi
- Jordan J. Louviere
- Stephane Hess
- Chandra R. Bhat
- Denzil G. Fiebig
- Matthew Harding
Citations in the corpus
- Pass-through as an Economic Tool (2009, unknown): “For both the net effect is a dollar increase in price.”
- COMPARING ALTERNATIVE MODELS OF HETEROGENEITY IN CONSUMER CHOICE BEHAVIOR (2012, methodology): “Burda et al (2008) specified a subset of coefficients in MIXL model to follow mixture-of-normal distributions while some other still follow a simple MVN distribution.”
- The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity (2010, methodology): “(2005) and Burda et al. (2008).4 Figure 5.7 in Rossi et al. (2005) provides a nice illustration of how flexible the distribution of household posterior means can be in a mixture of normals model.”
- Bayesian semiparametric modeling of realized covariance matrices (2016, background): “When combined with returns, and 1There are numerous applications in economics, e.g. Hirano (2002), Conley et al. (2008), Burda et al. (2008), Chib & Greenberg (2010) and Bassetti et al. (2014). conditional on appropriate quantities, all of the mixture models based on inverse-Wishart kernels imply…”
- Mixed logit with a flexible mixing distribution (2016, methodology): “(2011), Burda et al. (2008) and Fosgerau and Mabit (2013).”
- The Heterogeneous Geographic and Socioeconomic Incidence of Cigarette Taxes: Evidence from Nielsen Homescan Data † (2012, background): “Note however, that close to 30% of the panel participants are not employed.(8) Overall, these de-”