Skip to main content

A Network Analysis of Global Value Chains (GVCs)

We often speak of trade in simple, bilateral terms: "Germany exports cars to France" or "China ships phones to the US." But in a modern hyper-connected economy, these statements are deceptively simple. A "German" car might contain a Polish engine, Italian electronics, and Chinese batteries, while a "Chinese" phone may effectively be a bundle of Korean chips and American intellectual property wrapped in plastic.

To understand who really creates value in the global economy, we cannot rely on standard customs data. We need to look deeper. The interactive network map below does exactly that, peeling back the layers of "Gross Trade" to reveal the Global Value Chains (GVCs) underneath.

Global Value Chain Network (2021)

Interactive Map: Hover over any arrow above to see the exact trade volume (USD Millions). Click an arrow to highlight the path.

The Data Problem: The "$1,000 iPhone" Illusion

Why do we need this map? Standard trade statistics suffer from a massive "double counting" problem. Imagine an iPhone. When China exports it to the US for $1,000, customs data records a $1,000 export from China. But if $300 of that value was a chip made in Korea and $200 was a screen from Japan, China only created $500 of value. Standard data credits China with the full $1,000, inflating its trade surplus and hiding the contributions of its neighbors.

This visualization uses the OECD Trade in Value Added (TiVA) 2025 database to correct this. Specifically, I utilized the EXGR_DVA indicator (Domestic Value Added in Gross Exports), which strips away foreign components to isolate the "true" economic contribution of a nation—the wages paid to its workers and the profits earned by its firms.

Methodology: Mapping "Factory World"

Using Python and network analysis, I modeled the global economy as a directed graph:

  • Nodes (Flags): Represent major economies. Their size is dynamic, determined not by GDP, but by their total volume of domestic value-added exports.
  • Edges (Arrows): Represent the flow of value. To avoid the "hairball effect" common in network data, I applied a $1 billion threshold, visualizing only the major arteries of the global economy.
  • Geography: Nodes are anchored to their geographic coordinates to visualize the spatial reality of supply chains.

Key Insights: Three Factories, Three Models

The map reveals that the global economy is not a uniform mesh, but rather three distinct "Regional Factories," each with a unique structure:

  1. "Factory Europe" (The Integrated Web): Look at the dense tangle of yellow arrows in Europe. This visualizes the success of the Single Market. Unlike other regions, Europe does not rely on a single hub-and-spoke model. Instead, Germany (DEU), France (FRA), Italy (ITA), and the Netherlands (NLD) form a deeply integrated "multi-polar" web. Germany acts as the gravitational center, but the heavy bidirectional flows show a relationship of mutual dependency rather than simple dominance.
  2. "Factory Asia" (The Conveyor Belt): The Asian cluster (green nodes) reveals a different dynamic: the "Assembly Line." Notice the thick arrows flowing from advanced economies like Japan (JPN) and South Korea (KOR) into China (CHN). This visualizes the flow of high-tech intermediate components (chips, screens) moving into China for final assembly. China then acts as the global launchpad, exporting the final value to the US and Europe.
  3. "Factory North America" (The Triangle): In the West, the red nodes show a clear triangular structure. The US is the massive anchor, with thick, singular arteries connecting to Canada and Mexico. This reflects the USMCA (formerly NAFTA) dynamic, where supply chains are often built to feed the US consumer market, rather than the multi-directional web seen in Europe.

The Strategic Implication: The Myth of Decoupling

In an era where "de-risking" and "decoupling" are buzzwords, this map offers a reality check. The thickness of the connections—particularly between the "Three Factories"—shows that the global economy is not just connected; it is fused.

Disrupting a single node (like China or Germany) doesn't just cut a trade line; it strands the upstream suppliers (who lose their assembler) and the downstream buyers (who lose their final goods). This network analysis confirms that while political rhetoric focuses on borders, economic value flows right through them.

Comments

Post a Comment

Constructive feedback is always welcome. Thank you

Popular posts from this blog

Modeling Core PCE inflation: A dual approach

Today's release of the August 2025 Personal Consumption Expenditures (PCE) inflation data drew widespread media attention, with coverage highlighting both the persistence of inflation and its implications for Federal Reserve policy. Across outlets, analysts pointed to resilient consumer spending and income growth as signs of underlying economic strength, even as inflation remains above the Fed's 2% target. The consensus among media reports is that while inflation is not worsening, its stubbornness continues to challenge policymakers navigating a softening labor market and evolving rate expectations. To provide deeper insights into inflation's trajectory, I've developed a forecasting framework that combines two econometric approaches — ARIMA time series modeling and Phillips Curve analysis—to predict Core PCE inflation. This analysis presents a unique opportunity to validate my forecasting methodology against eight months of 2025 data. ...
Post a Comment
Read more

Do Minimum Wage Increases Really Kill Jobs? Evidence from the "Fight for $15" Era

The debate over minimum wage policy has raged for decades, with economists, policymakers, and business leaders offering sharply different predictions about its effects on employment. Critics warn that raising the minimum wage will force employers to cut jobs, while supporters argue that higher wages boost worker productivity and spending power. But what does the actual data tell us. Using a comprehensive difference-in-differences analysis and Federal Reserve Economic Data covering 43 U.S. states from 2012-2020 of the "Fight for $15" movement between 2012 and 2020, I provide some evidence about how minimum wage increases actually affect employment in the real world. The Perfect Natural Experiment The period from 2012 to 2020 provided economists with an ideal "natural experiment" to study minimum wage effects. Here's why this timeframe was perfect for analysis: Federal Stability : The federal minimum wage remained frozen at $7.25 per hour since 2009, creating ...
Post a Comment
Read more

Mapping the Matrix: Malaysia's Corporate Network

The complex interconnections that define modern society are readily visible in our Facebook or LinkedIn networks. But what about the corporate world? I recently began mapping the web of cross-shareholding among Malaysia's listed corporations. Using Social Network Analysis (SNA), I visualized the ecosystem to identify key "communities" and power brokers. The goal? To see if a company's position in this web predicts its financial destiny. The State of Play (2015) Figure 1: Malaysia's Corporate Network in 2015 (Created via Gephi) The map above visualizes the network as of 2015. While I have excluded specific company names, the "super-nodes" (the largest circles) represent the most connected shareholders in the economy—primarily government-linked investment companies (GLICs), fund managers, and international asset managers. A Decade of Growing Complexity ...
2 comments
Read more