Michael Sinanian

Quick Snapshot

Role: Data analyst
Team: Independent research project
Customers: Economists and analysts examining long-term GDP composition trends

Hierarchical cluster heatmap of U.S. industry components. — Hierarchical clustering grouped industries with similar cost structures to highlight emerging relationships.

Mandate / Opportunity / Problem Scope

I examined U.S. GDP and its components from 1947 onward to test assumptions about how compensation, taxes, operating surplus, and intermediate inputs evolve over time.

Heatmap showing industry surplus and intermediate input ratios. — Heat maps revealed how labor, surplus, and intermediate input ratios shifted across industries through decades.

Line chart tracking sector ratio changes in GDP components. — Sector ratio charts communicated the magnitude of structural economic change to stakeholders.

What I Led / Delivered / Highlights

Gathered raw data from the Bureau of Economic Analysis and normalized it using Excel.
Reshaped the dataset with custom R scripts, then applied hierarchical clustering to uncover relationships among industries and sectors.
Visualized findings through heat maps and ratio charts to communicate changes in cost structure and surplus contribution.

Impact / Lasting Value / Takeaway

The work produced an extensible analysis framework for exploring GDP composition, enabling data-driven conversations about structural shifts in the U.S. economy.

U.S. GDP Analysis with Machine Learning

Quick Snapshot

Mandate / Opportunity / Problem Scope

What I Led / Delivered / Highlights

Impact / Lasting Value / Takeaway