Cross-border Production-sharing Activities in Global Value Chain and Labor Migration


Student thesis: Master's Thesis

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Award date26 Apr 2021


This paper provides first evidence on the impact of a direct measure of the impact of Global Value Chain (GVC) Activities on labor migration and skill biasedness in migration. It includes the upstreamness (i.e. the steps before the production of a firm meets final demand). It also investigates whether results vary along the skills, by participation index and by share index. This paper examines the relationship between Global Value Chain Activities (GVC) and skill-biased labor migration in 14 countries with 384 country-pairs for the year 2000 to 2010. In particular, we explore how the diversity in the relative GVC position between the migration source and destination countries (especially between developed and developing countries) affects the bilateral labor flow between the two countries at different skill levels. Findings based on unique matched country-country data relative to the upstream or downstream industries for this period show that workers can migrate significantly, when the industry concentrates on more upstream activities.

We adopt the methodology of Wang et al. (2017) to identify the share of production activities at the country-sector level that is for global value chain (GVA) activities, and how this cross-border production sharing activities relates to skill-biased labor migration. In particular, we analyze the GVC Position Index to understand how upstream vs. downstream production activities affects skill-biased migration. We also collect bilateral labor migration data from the Database on Immigrants in OECD Countries (DIOC) which contains bilateral migrant stock data classified by education level and occupations in 34 destination countries from more than 200 countries of origin.

The gains from upstreamness are found to be very similar for both skill bias migration and bilateral migration. We distinguish production activities with three indexes: GVC Position Index, GVC Participation Index and GVC Share Index. Based on such an accounting framework, we further decompose labor migration into two different segments: skill bias migration and bilateral labor inflow. We discover that if destination country concentrates on upstreamness, then both bilateral migration and skill bias migration will be more. However, if origin country concentrates more on upstreamness, both bilateral and skill bias migration will be less. We also explore the reasons behind it such as higher imports of inputs or due to skill-biased technological change, relative wage, education level, labor demand, faster job creation etc. by reviewing the existing studies related to our results. We also study the relationship between labor migration and GVC participation of destination country. We find two different results for two types of participation index (forward and backward linkage). This paper also analyses the relationship between labor migration and GVC Share Indexes (forward and backward linkage). It reveals some interesting variations, in particular differences between the models of labor migration based on forward linkage and backward linkage based share indexes. We use different gravity models for our analysis. However, we deviate from the “classic” analysis of gravity model which is based on international trade.

    Research areas

  • Skill bias migration, GVC position index, Gravity model, PPML, GPML