This tutorial demonstrates the usage of BayesX for analysing Bayesian semiparametric regression models based on MCMC techniques. As an example we consider data on undernutrition of children in Zambia. The tutorial is designed to be self-contained and describes all features of BayesX in detail, that will be needed throughout the tutorial. Therefore it may also serve as a first introduction into the general usage of BayesX.

We examine the spatio-temporal dynamics of self-employment in India using geoadditive models and pseudo panel techniques. We test the claim of Iyigun and Owen (1999) that individuals invest in professional human capital and not in entrepreneurial human capital as an economy develops. The results suggest that in non-agriculture, higher education decreases the likelihood of individuals choosing self-employment over time; however, it has an opposite effect in agriculture. While increases in land possessed increase the likelihood of self-employment choice in agriculture, individuals with small land holdings are more likely to transition into self-employment in non-agriculture. Belonging to a backward class has a negative effect on self-employment choice in both sectors; however, the effect has increased in non-agriculture and remained stable in agriculture. The geoadditive models suggest that the propensity to be self-employed has decreased across most spatial units, although there are few pockets where self-employment is rising again.

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Modelling dependent yearly claim totals

Nanoparticle Properties to Biological