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Title: Colombian women's life choices: A Bayesian nonparametric multivariate regression approach Authors:  Isadora Antoniano-Villalobos - Ca' Foscari University of Venice (Italy) [presenting]
Andrea Cremaschi - Universitetet i Oslo (Norway)
Raffaella Piccarreta - Bocconi University (Italy)
Sara Wade - University of Cambridge (United Kingdom)
Abstract: Women in the Latin America and Caribbean countries face difficulties related to the patriarchal traits of their society. In Colombia, the well-known conflict afflicting the country since 1948, has increased the risk of vulnerable groups. It is important to determine if recent efforts to improve the welfare of women have had a positive effect extending beyond the capital, Bogota. In an initial effort to shed life on this matter, we analyze cross-sectional data arising from the Demographic and Health Survey Program which collects and disseminates data on random samples of households selected from a national sampling frame. The aim is to study the relationship between baseline socio-demographic factors and variables associated to fertility, partnership patterns and work activity. We propose a flexible Bayesian nonparametric multivariate regression model, which can capture nonlinear regression functions and the presence of non-normal errors, such as heavy tails or multi-modality. The model has interpretable covariate-dependent weights constructed through normalization, allowing for combinations of both categorical and continuous covariates, as well as censoring in one or more of the responses. Computational difficulties for inference are overcome through an adaptive truncation algorithm combining adaptive Metropolis-Hastings and sequential Monte Carlo to create a sequence of automatically truncated posterior mixtures.