Shyam Ranganathan (), Ranjula Bali Swain () and David Sumpter ()
Additional contact information
Shyam Ranganathan: Department of Mathematics, Postal: Uppsala University,
Ranjula Bali Swain: Department of Economics, Postal: Uppsala University, P.O. Box 513, SE-751 20 Uppsala, Sweden
David Sumpter: Department of Mathematics, Postal: Uppsala University,
Abstract: A key aim of economics is to set goals and investigate the relationship between various socio-economic indicators. By tting 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.
Keywords: Demographic transition; Human Development; dynamical systems; Bayesian; data-driven; GDP; child mortality; fertility rate
JEL-codes: C51; C52; C53; C61; J13; O21
42 pages, October 31, 2014
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