Tweaking the rise and fall of empires and economies
summary
Implements Lotka‑Volterra, SIR, Keen and Turchin models in Python, packages them as modeldrop.io, and wires a Dash UI to tweak parameters live. Uses scipy’s odeint (Fortran ODE solver) and Plotly for plots. Shows R crossing 1 flipping epidemic curves, Keen‑style rising debt from higher depreciation triggering crashes, and Turchin’s elite share exceeding half production while elite per‑capita income falls with a predicted 2020 violence peak in the fitted data.
AI-written summary · about
chapters (8)
- 0:00Intro
- 0:55Who am I
- 1:56Models
- 9:20Model Drop
- 14:50Demo
- 16:10Sir epidemiology
- 18:00Economic modelling
- 21:33Peter Turchin model
related talks
44mPython for Economists: An overview of Python tools for Economists
30mDisease Modeling with Scipy and PyMC
45mInteractive Analysis of (Large) Financial Data Sets
02h 23mEffective Data Visualization
33mData Science & Data Visualization in Python
29mUsing Dash by Plotly for Interactive Visualisation of Crime Data
26mTime Series Analysis in Python: Easy Tools for Scientific Insight
22mUsing Python & R in Harmony