Unlocking Methods for Analyzing Economic Growth Patterns

Chosen theme: 3. Methods for Analyzing Economic Growth Patterns. Explore approachable, evidence-based tools for understanding how and why economies expand, slow, or transform—and join our community of curious readers who test ideas, question assumptions, and share insights.

Growth Accounting Essentials

Growth accounting separates GDP growth into labor, capital, and a residual often called total factor productivity—the famous Solow residual. It helps you see whether machines, skills, or better ways of working power expansion. Try it on your country’s data and share what surprised you most.

Solow-Swan and Beyond

The Solow-Swan model suggests poorer economies can grow faster, closing gaps with richer peers—if fundamentals match. Two neighboring regions we studied diverged for years until infrastructure improved, then convergence accelerated. Share a regional story where a single investment shifted the long-run path.

Solow-Swan and Beyond

Adding education to the model, following Mankiw-Romer-Weil, often explains persistent income differences. Years of schooling and quality-adjusted learning change steady-state predictions. Which education indicators best capture skills where you live? Join the discussion and propose a better measure.

Time-Series Diagnostics for Growth

Filters like HP, Baxter–King, or local linear trends help separate persistent growth from short-run fluctuations, but parameter choices matter. We once misread a policy effect that vanished after a robustness check. What’s your favorite filter, and how do you justify it?

Time-Series Diagnostics for Growth

Bai–Perron break tests and Markov switching models can locate growth regime changes—often lining up with crises or reforms. In one case study, the 1997 shock caused a lasting productivity level drop. Run a break test and share if your economy’s turning points surprised you.

Time-Series Diagnostics for Growth

Granger causality and Johansen cointegration test whether investment, productivity, and output share stable long-run relationships. Results guide narratives beyond coincidence. Try testing cointegration between capital deepening and GDP, then post whether the relationship survives alternative sample windows and lags.

Time-Series Diagnostics for Growth

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Leontief Tables and Economic Linkages

Input–output analysis pinpoints sectors with strong backward and forward linkages that amplify shocks and policies. Upgrading a high-linkage industry can lift the whole network. Explore your country’s table, identify a pivotal sector, and share why it deserves strategic attention.

Stories of Structural Transformation

Shifts from agriculture to manufacturing to services define development arcs. In one coastal economy, light manufacturing anchored an export surge, then services scaled. Which sectoral shift best explains recent growth where you live? Tell us the story behind the numbers.

Productivity Spillovers and Clusters

Supplier quality programs and logistics hubs often trigger sector-wide productivity spillovers. We studied a corridor where training vendors lifted small firms’ output dramatically. Map a cluster near you, measure spillovers with firm-level data, and share insights to inspire evidence-based policy debate.

Entry, Exit, and Creative Destruction

Firm births and deaths reallocate resources to better uses. Studies by Foster, Haltiwanger, and Krizan show reallocation’s sizable contribution to productivity growth. Compile a simple decomposition for your sector, then share whether churn helped or hindered overall performance.

Learning from Survivors and Gazelles

A handful of fast-growing “gazelles” often drive disproportionate gains. One exporter we interviewed doubled productivity after adopting lean routines learned from a supplier visit. What distinguishes top performers in your dataset? Post a brief profile and invite feedback on your hypothesis.

New Frontiers: Night Lights, Satellites, and Machine Learning

Nighttime lights, crop yields from remote sensing, and building footprints proxy for activity when official statistics lag. We validated night lights against subnational GDP and found strong correlations. Try a lights-based growth map for your region and share anomalies that beg explanation.