Flexibility without foresight: the predictive limitations of mixture models
Fuente:
arXiv
Salvato in:
| Autori principali: | , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866909834105847808 |
|---|---|
| author | Hess, Stephane van Cranenburgh, Sander |
| author_facet | Hess, Stephane van Cranenburgh, Sander |
| contents | Models allowing for random heterogeneity, such as mixed logit and latent class, are generally observed to obtain superior model fit and yield detailed insights into unobserved preference heterogeneity. Using theoretical arguments and two case studies on revealed and stated choice data, this paper highlights that these advantages do not translate into any benefits in forecasting, whether looking at prediction performance or the recovery of market shares. The only exception arises when using conditional distributions in making predictions for the same individuals included in the estimation sample, which obviously precludes any out-of-sample forecasting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_09185 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Flexibility without foresight: the predictive limitations of mixture models Hess, Stephane van Cranenburgh, Sander Econometrics Models allowing for random heterogeneity, such as mixed logit and latent class, are generally observed to obtain superior model fit and yield detailed insights into unobserved preference heterogeneity. Using theoretical arguments and two case studies on revealed and stated choice data, this paper highlights that these advantages do not translate into any benefits in forecasting, whether looking at prediction performance or the recovery of market shares. The only exception arises when using conditional distributions in making predictions for the same individuals included in the estimation sample, which obviously precludes any out-of-sample forecasting. |
| title | Flexibility without foresight: the predictive limitations of mixture models |
| topic | Econometrics |
| url | https://arxiv.org/abs/2510.09185 |