Ranganathan, Shyam Swain, Ranjula Bali Sumpter, David J. T.
Year of Publication:
Working Paper, Department of Economics, Uppsala University 2014:9
A key aim of economics is to set goals and investigate the relationship between various socio-economic indicators. By fitting time series data using a Bayesian dynamical systems approach we identify non-linear interactions between GDP, child mortality, fertility rate and female education. We show that reduction in child mortality is best predicted by the level of GDP in a country over the preceding 5 years. Fertility rate decreases when current or predicted child mortality is low, and is weakly dependent on female education and economic growth. As fertility drops, GDP increases producing a cycle that drives the demographic transition.
Demographic transition Human Development dynamical systems Bayesian data-driven GDP child mortality fertility rate