WorldSim runs Monte Carlo simulations across socio-economic indicators for 195 countries, producing full probability distributions (P10/P50/P90) instead of single-point forecasts. Over 100 structural coupling rules connect variables causally: shock energy prices and inflation, rates, housing, and debt cascade automatically. Three scenario paths (Better/Average/Shock), user-controlled bias overlays, and reproducible runs. Built for macro analysts, policy teams, and country risk professionals.
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Maker
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After years of building ML models and forecasting pipelines, I came to a conclusion that changed how I think about the future: single-point forecasts are almost meaningless for structural questions.
When you're modelling what happens to a country over 20 years, one number tells you nothing. What matters is the distribution. The range of plausible outcomes. The tail risks.
Over the past year, I've been building WorldSim to take this seriously. 195 countries, full Monte Carlo simulation, 100+ coupling rules that cascade effects between variables automatically.
Try the country you live in and let me know what you think of the outcome. Would love your feedback.