What Triggers Structural Change Across Countries? Machine Learning Evidence from Long-Term Dynamics

This research analyzed the determinants of countries’ structural change using machine learning techniques. The findings demonstrate the predictors’ potential to trigger cumulative causation mechanisms that predict countries’ long-term trends toward an SC process or stagnation and decline

Julián Salinas

Oct 03, 2026

Humanities and Social Sciences Communications

Behind the Paper

How do structural change patterns differ across countries? Evidence from long‑term systemic dynamics

Structural change is dynamic, systemic, and by far nonlinear. Using structural tendencies as the core analytical unit, this post deepens the article, which examines structural change patterns in 147 economies using unsupervised machine learning techniques and provides policy insights.

Julián Salinas

Apr 14, 2026

Computational Economics

Behind the Paper

What shapes countries’ structural tendencies? Evidence from midterm competitive industrial perfomance index (CIP) trends and machine learning

This study examines the midterm determinants of CIP trends across 148 economies. It reveals the dynamic factors that shape midterm structural changes, analyzes the role of predictive features in delineating CIP midterm trends, and shows how machine learning can advance social science.

Julián Salinas

Mar 12, 2026

Julián Salinas (He/Him)

What Triggers Structural Change Across Countries? Machine Learning Evidence from Long-Term Dynamics

How do structural change patterns differ across countries? Evidence from long‑term systemic dynamics

What shapes countries’ structural tendencies? Evidence from midterm competitive industrial perfomance index (CIP) trends and machine learning