A Bayesian Mixed Multinomial Logit Model for choice-sets and decision-makers’ heterogeneity

ABSTRACT

We propose a Bayesian Mixed Multinomial Logit Model (MMLM) to deal with the critical issue of choice-set heterogeneity often present in policy evaluation studies enriched with microsimulated data. We also exploit the comparison of three clustering methods to capture decision-makers’ heterogeneity through a specific random effect. A case study, which aims to describe the determinants of labour choices of females in couples with microsimulated fiscal variables, is the test-bed for our methodological proposal. By virtue of this very flexible specification of the random components, the Bayesian MMLM proves to be more accurate, parsimonious and consistent in terms of point estimates with the research field than other models.

KEYWORDS:

• Bayesian Mixed Multinomial Logit Model labour supply heterogeneous choice-set heterogeneous decision-makers microsimulation

JEL CLASSIFICATION:

• C40
• C11
• H31
• J10

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Number of females in $C_1,\dots ,C_8$: 388, 355, 356, 359, 353, 390, 382, 372..