Global value chains and labor markets

This study empirically investigates how backward linkages impact the skill structure of domestic labor demand by estimating a system of factor equations and measuring elasticities of factor demand. This was made possible by constructing a dataset using data on labor compensation from the Socio-Economic Accounts (SEA) along with industry-level international trade data for the period 1995-2009, covering 40 countries from the World Input-Output Database (WIOD). Based on an input-output model, an indicator that measures the pervasiveness of global value chains (GVCs), "foreign value-added in exports (FVAiX)", is calculated. Including this index in a translog cost function, this study estimates a system of variable factor demand equations, using the iterative seemingly unrelated regressions (ISUR) method. Results reveal that participating in GVCs has both positive and negative effects on demand for different skill types of labor. On one hand, there is a positive trend for high-skilled workers, regardless of the region or GDP per capita of the country. On the other hand, results indicate a widening gap between high- and low-skilled labor, suggesting an increase in inequality, especially in low-income countries.