A dynamical systems approach to modeling human development

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper ; No. 2014:9

Classification and Topics

• Classification: Wirtschaft ; Model Construction and Estimation ; Model Evaluation, Validation, and Selection ; Forecasting Models; Simulation Methods ; Optimization Techniques; Programming Models; Dynamic Analysis ; Fertility; Family Planning; Child Care; Children; Youth ; Planning Models; Planning Policy
• Subject: Demographic transition ; Human Development ; dynamical systems ; Bayesian ; data-driven ; GDP ; child mortality ; fertility rate

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Ranganathan, Shyam ; Swain, Ranjula Bali ; Sumpter, David J. T.
• Event: Veröffentlichung
• (who): Uppsala University, Department of Economics
• (where): Uppsala
• (when): 2014

Further information

• Handle: http://hdl.handle.net/10419/123798
• URN: urn:nbn:se:uu:diva-235541
• Last update: 10.03.2025, 11:42 AM CET