  Family planning has been characterized by highly different strategic programs
in India, including method-specific contraceptive targets, coercive
sterilization, and more recent target-free approaches. These major changes in
family planning policies over time have motivated a considerable interest
towards assessing the effectiveness of the different programs, while
understanding which subsets of the population have not been properly addressed.
Current studies consider specific aspects of the above policies, including, for
example, the factors associated with the choice of alternative contraceptive
methods other than sterilization, for women using contraceptives. Although
these analyses produce relevant insights, they fail to provide a global
overview of the different family planning policies, and the determinants
underlying the contraceptive choices. Motivated by this consideration, we
propose a Bayesian semiparametric model relying on a reparameterization of the
multinomial probability mass function via a set of conditional Bernoulli
choices. The sequential binary structure is defined to be consistent with the
current family planning policies in India, and coherent with a reasonable
process characterizing the contraceptive choices. This combination of flexible
representations and careful reparameterizations allows a broader and
interpretable overview of the different policies and contraceptive preferences
in India, within a single model.
