A Global Value Chain Approach to Emerging Market Catch-up

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• Professor Ram Mudambi, Temple University, USA
• Friday 21 September 2012, 09:00-09:45
• Moller Centre, Cambridge.

If you have a question about this talk, please contact Jo Griffiths.

Registration is required - contact Jo Griffiths for information - jg393@cam.ac.uk

Part of the Cambridge International Manufacturing Symposium “Capturing Value in International Manufacturing and Supply Networks – new models for a changing world”

Value chain analysis is an innovative tool that views economy in terms of activities instead of its constituent industries and firms (Mudambi, 2008). The value chain approach analyses, at the sector level, each link in the ‘chain of activity’ — from the ideation of the product or service to its post-use disposal.1 A value chain for any product or service consists of a number of inter-linked activities extending from upstream R&D, to raw materials and component supply, production, through delivery to international buyers, and often beyond that to disposal and recycling.

Global Value Chains (GVCs) are part and parcel of international trade and have existed as long as there have been trade relations between countries. However, two fundamental trends have arisen over the last few decades that have changed the characteristics of GVCs in fundamental ways. First, the advance of technology, especially information technology has enabled firms to re-configure themselves in very basic ways so that they can now outsource activities deep in the heart of the firm with surgical precision and focus on activities where they have superior competencies. Second, the number of locations where such activities can be undertaken has risen dramatically over the last two decades with the increasing sophistication of infrastructure and other resources in a wide range of emerging markets.

In this presentation, we apply GVC analysis to Chinese data to examine the extent of economy-wide catch-up. Using this approach we find that catch-up is significantly less advanced than simple output-based measures indicate.

This talk is part of the IfM Seminars series.

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