Measuring industrial upgrading: applying factor analysis in a global value chain framework

ABSTRACT

A key question for promoting international competition is how to improve the position of countries and industries in global value chains (GVCs). The first step is to properly measure industrial upgrading in GVCs. This is not a trivial issue because upgrading has not been defined unambiguously. Several authors have used different (and sometimes related) measures, all of which indicate certain aspects of upgrading. Rather than trying to find the single, ultimate measure of upgrading, we propose a different approach. We examine the multidimensionality of industrial upgrading, using eight indicators in factor analysis. Four of the eight indicators adopt the GVC perspective and include, for example, the growth of the share in value-added exports. We provide three quantitative dimensions of industrial upgrading: process upgrading, product upgrading, and skill upgrading. With these dimensions, we compare and analyze the upgrading of different countries and industries using the World Input–Output Database.     

Local clusters in global value chains: exploring dynamic linkages between Germany and Pakistan

Recent research has underlined the importance of external linkages for industrial clusters. Suppliers and buyers within a global value chain offer important external ties for cluster-based producers not only in terms of the distribution of physical goods, but also for knowledge flows and innovation. Globalization has intensified such value chain links, connecting geographically dispersed producers to global markets. Yet, there is limited research on how local clusters enter global chains or on ties between clusters in the developed and developing world. This study addresses this gap. It uses the case of the global surgical instrument industry to analyse connections and differences between the industry's leading production clusters in Germany and Pakistan. Global standards, low-cost competition, and advances in medical technology raise challenges for both clusters. The paper explores the responses to these challenges. It distinguishes between knowledge and production links to illustrate differentiation in each cluster, diverging trajectories and continuing ties.     

中国制造业参与全球价值链的程度与方式——基于世界投入产出表的分析

本文利用世界投入产出表数据,构建后向和前向垂直专业化率指标,并据此对中国制造业参与全球价值链的程度与方式进行详细分析。结果表明：（1）中国制造业主要是以后向方式参与全球价值链;（2）中国制造业处于全球价值链的下游位置,主要参与全球价值链中的低端生产环节;（3）伴随着跨国生产分工的深化,中国制造业正由全球价值链低端向中高端攀升;（4）中国制造业主要集中参与全球价值链中的某一个生产环节,且国内价值链的构建和发展相对薄弱;（5）在四类技术类别制造业中,中低技术制造业在全球价值链中处于相对优势地位,但高技术制造业并未实现真正意义上的高技术;（6）相对于中国主要以后向方式参与全球价值链,美国主要是以前向方式参与全球价值链。     

Explaining value chain differences in MRIO databases through structural path decomposition

Many multiregional input–output (MRIO) databases are used to calculate consumption-based accounts. Results feature in climate policy discussion on emissions reduction responsibilities; yet studies show that outcomes produced by each database differ. This paper compares the emissions associated with value chains from Eora, EXIOBASE, GTAP and WIOD. Structural path analysis identifies the largest paths in each database and the differences in common paths are calculated. For the top 100 value chain paths that contain the largest difference, structural path decomposition is used to identify the contribution each part of the value chain makes towards the difference. The results identify and quantify key flows that are the cause of difference in the databases. From these, we can conclude that key MRIO database construction decisions, such as using the residence or territorial principle for emissions allocation and whether energy spends are reallocated based on physical data, are the major causes of differences.