Recent posts

Monte Carlo Simulations in Macroeconomic Modeling

Monte Carlo simulations offer a powerful way to model uncertainty in macroeconomic systems. This article explores how they’re applied to stress testing, forecasting, and policy analysis in complex economic models.

Model Drift: Why Even the Best Machine Learning Models Fail Over Time

Model drift is a silent model killer in production machine learning systems. Over time, shifts in data distributions or target concepts can cause even the most sophisticated models to fail. This article explores what model drift is, why it happens, and how to deal with it effectively.

Nonlinear Growth Models in Macroeconomics

Nonlinear growth models offer a richer and more realistic framework for understanding macroeconomic development over time. This article explores the mathematical structures and real-world relevance of non-linear dynamics in economic growth theory.

Differential Equations in Growth Models

Differential equations are essential in modeling economic growth, providing insight into long-term trends and the impact of policy changes on macroeconomic variables.