Global Value Chains and the Skill Structure of Labor DemandHaruka Yane
Osaka University, JSPS Research Fellow

Abstract

Distinguishing among different types of trade flows, this study conducts empirical analysis on therole of global value chains in the skill structure of labor demand. This study uses data on labor
compensation from the Socio-Economic Accounts (SEA) along with industry-level international
trade data for the period 1995 to 2009, covering 40 countries from the World Input-Output
Database. Preliminary results from the estimation of a system of factor demands do not show any
statistically significant relation between foreign value added in a country’s exports and its domestic
labor demand. A different take on the analysis reveals that although trade in intermediate inputs
have a negative effect on low- and medium-skilled workers, the positive effect from trade in final
products on these workers outweighs this negative effect. Similarly, increase in trade in final
products has an adverse impact on high-skill labor, but the effect from an increase in intermediates
imports offsets this, contributing to an overall positive effect. The extent and direction of the impact
from increase in intermediates and final products trade on the skill composition of labor demandvary depending on the sector, region and whether the goods and services being traded are low,
medium or high technology. In order to alleviate the negative effects, workers from each skill groupshould be able to move along the value chain smoothly.

Keywords: Global Value Chains, Labor demand, Skill structure
JEL classifications: F14 Empirical Studies of Trade, F16 Trade and Labor Market Interactions

Global Value Chains and the Skill Structure of Labor DemandHaruka YaneOsaka University, JSPS Research Fellow

In recent years we have witnessed the world economy rapidly integrating throughinternational trade. Behind this phenomenon is the increasing prominence of trade in intermediates
and trade in services during the past two decades. The international fragmentation of production in
global value chains has been motivated by sourcing intermediate inputs from more cost-efficient
producers in order to enhance efficiency. As a result, domestic production has been increasingly
relying on foreign intermediate inputs. Further, rapid advances in information and communications
technology (ICT) and infrastructure growth have increased the tradability of many service activities,
thereby facilitating the sourcing of services from abroad.
This rapid globalization process has had diverse effects on individuals, households andfirms. Theoretically and empirically, it is now common knowledge that trade liberalization isassociated with both job destruction and job creation. However, the debate continues regarding towhat extent trade liberalization has impact on the labor market, and what complementary policies
may be effective to implement along with trade liberalization in order to maximize (minimize) thebenefits (costs). It is becoming increasingly important to measure the effects of trade liberalizationon the labor market, in particular wages and employment.
Global value chains have rapidly emerged as production processes have become moregeographically fragmented since the 1990s. International trade and production are increasingly
structured around these global value chains. A value chain can be simply defined as the full rangeof activities that firms and workers carry out in order to bring a product from its conception to its
end use and beyond (see Gereffi and Fernandez-Stark, 2011). The term global comes from the factthat these activities are more and more spread over multiple countries. There has been a rising trend
in the world’s ratio of foreign to domestic inputs, indicating that firms have been expanding theirpurchase and usage of intermediate inputs from abroad.

The share of world’s intermediates trade in total trade has been increasing, in contrast withthe stagnant share of world’s final products trade in total trade, as depicted in Figure 1. It also
shows how intermediates trade share in total trade in East Asia is exceptionally high, leading therising trend in trade in intermediate products.

Figure 1: Trade in Intermediates and Final Products as a Share of Total Imports
100%
80%
60%

40%20%0%

World imports in intermediates
East Asia imports in intermediates
World imports in final products

Source: Author’s calculation based on WIOD.

Moreover, services trade liberalization has reduced regulatory barriers in key sectors of theglobal logistics chain, such as transport, finance and telecommunications. Business services, forexample, are now an integral part of the global value chain. Naturally, people worry that if theircountry’s imports from their partner country increase due to a newly-signed free trade agreement(FTA), the unemployment rate might rise and/or their wages may decrease. There are concerns that
globalization leads to a greater wage gap and would worsen inequality, with people in the source
country losing their jobs (quantitatively) or having to work in worse conditions (qualitatively).
Using trade data from the World Input-Output Database (WIOD) 1, this study attempts toreveal the relationship between participation in the global value chain and change in domestic labor
1This new World Input-Output Database is available at http://www.wiod.org/database/index.htm.

demand. In measuring the foreign value added content in exports (FVAiX), this study follows
Amador, Cappariello and Stehrer (2015). The ratio of value added to gross output in country 𝑠 isdenoted by 𝑣 𝑠 , a 1 × 𝑁𝐶 vector, where 𝑁 is the number of sectors and 𝐶 the number of countries.
The Leontief inverse of the global input-output matrix is expressed as 𝐿 = (𝐼 − 𝐴)−1 , withdimension 𝑁𝐶 × 𝑁𝐶 , where 𝐴 denotes the global coefficients matrix. Country 𝑟 ’s exports isdenoted by a vector 𝑒 𝑟 with dimension 𝑁𝐶 × 1. Pre-multiplying the Leontief inverse by the vectorof value added coefficients and post-multiplying with exports vector gives us the FVAiX:
𝐹𝑉𝐴𝑖𝑋 𝑠𝑟 = 𝑣 𝑠 𝐿𝑠𝑟 𝑒 𝑟(1)

Hence, this indicator captures the value added content in country 𝑟’s exports in which
imported intermediates are used. Using this as a measurement for global value chain prevalence,
this study assesses the effect global value chains have on the skill structure of labor demand.
Based on recent literature, the consensus view is that trade has played a role in observed changes
in relative labor demand. However, the conclusion is still mixed with regard to the major reasons
for rising wage inequality.
Foster-McGregor et al. (2013) estimate the relationship between offshoring and the skill
structure of labor demand using the WIOD for 40 countries over the period 1995-2009. They
estimate a system of variable factor demand equations, and their results indicate that while
offshoring has had a negative effect on all skill (low, medium and high) levels, the largest impacts
have been observed for medium-skilled workers. This is notable in a sense that it is consistent withthe recent trend towards the shrinking of the middle class in the North (see Costinot and Vogel,2010).
Table 1 shows preliminary results from an analysis on how Japan’s neighboring countries’
contribution to value added have had an impact on its wage shares by skill type. In this simple
model, there are two sectors: manufacturing and services. It is assumed that the cost functions canThe core of the database is a set of harmonized national supply and use tables, linked together with bilateral trade
data in goods and services. These two sets of data are then integrated into a world input-output table. See Timmer(2012) for the detailed framework and calculations.

be approximated by a translog function and is twice differentiable, linearly homogenous andconcave in factor prices. Time subscripts are omitted for simplicity.
𝑙𝑛𝐶𝑖 (𝑤, 𝑥, 𝑧) = 𝛼0 + ∑𝐽𝑗=1 𝛼𝑗 𝑙𝑛𝑤𝑖𝑗 + ∑𝐿𝑙=1 𝛽𝑙 𝑙𝑛𝑥𝑖𝑙 + ∑𝑅𝑟=1 𝛾𝑟 𝑧𝑖𝑟 +121

11∑𝐽𝑗=1 ∑𝐽𝑘=1 𝛼𝑗𝑘 𝑙𝑛𝑤𝑖𝑗 𝑙𝑛𝑤𝑖𝑘 + ∑𝐿𝑙=1 ∑𝐿𝑚=1 𝛽𝑙𝑚 𝑙𝑛𝑥𝑖𝑙 𝑙𝑛𝑥𝑖𝑚 + ∑𝑅𝑟=1 ∑𝑅𝑠=1 𝛾𝑟𝑠 𝑧𝑖𝑟 𝑧𝑖𝑠 +1212∑𝐽 ∑𝐿 𝛿 𝑙𝑛 𝑤𝑖𝑗 𝑙𝑛𝑥𝑖𝑙 + ∑𝐽𝑗=1 ∑𝑅𝑟=1 𝛿𝑗𝑟 𝑙𝑛𝑤𝑖𝑗 𝑧𝑖𝑟 + ∑𝐿𝑙=1 ∑𝑅𝑟=1 𝛿𝑙𝑟 𝑙𝑛𝑥𝑖𝑙 𝑧𝑖𝑟
2 𝑗=1 𝑙=1 𝑗𝑙
2
2(2)Where 𝐶𝑖 depicts the total variable cost in sector 𝑖 = 1, … , 𝑁; 𝑤𝑖𝑗 denotes factor prices for factor
𝑗 = 1, … , 𝑘, … , 𝐽 ; 𝑥𝑖𝑙 denotes fixed inputs and outputs for 𝑙 = 1, … , 𝑚, … 𝐿 ; and 𝑧𝑖𝑟 is thetechnological change or the demand shifters for 𝑟 = 1, … , 𝑠, … 𝑅. The variable factors are lowskilled, middle-skilled and high-skilled labor and intermediate inputs. The five necessary
restrictions for the aforementioned assumptions to hold are:∑𝐽𝑗=1 𝛼𝑗 = 1 and ∑𝐽𝑗=1 𝛼𝑗𝑘 = ∑𝐽𝑘=1 𝛼𝑘𝑗 = ∑𝐽𝑗=1 𝛿𝑗𝑙 = ∑𝐽𝑗=1 𝛿𝑗𝑟(3)First derivatives of the translog cost function with respect to factor prices yields the costshare of factor 𝑗 in total variable costs. Rather than estimating a single cost share equation, thisstudy estimates a system of demand equations by iterating Zellner’s method (ISUR), andcontrolling for time-invariant sector-specific fixed effects. Constructing a panel dataset for period
1995-2009, this study focuses on the relationship between the Asian production network andJapan’s domestic labor demand. As shown in the preliminary results, the variable of interest,𝐹𝑉𝐴𝑖𝑋, is not statistically significant at the 10% level. There is, however, a hint of a crowding outof the middle-skilled group, compared to low- and high-skilled workers, which is consistent withthe recent literature.
The WIOD’s Socio-Economic Accounts (SEAs) that cover high-, medium- and low-skilledlabor compensation, that were used for this analysis, as well as hours worked are worth looking
into. In Figure 2, it is clearly shown that during the period 1995-2009, hours worked by high-skilledworkers have increased relative to hours worked by medium- and low-skilled workers. Although
hours worked by medium-skilled workers do not show that much fluctuation, the decline in hours
worked by low-skilled workers is striking. This set of graphs signifies a possible replacement of
low-skilled labor by either high-skilled labor or the traditional foreign offshoring of less-skilled
activities.

Figure 2: Hours worked by sector (year 1995=100)
Agriculture160
140
1201008060402001995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Hours worked by low-skilled labor

Hours worked by medium-skilled labor

Hours worked by high-skilled labor

Low-skilled labor compensation

Medium-skilled labor compensation

High-skilled labor compensation

Manufacturing1801601401201008060402001995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Hours worked by low-skilled labor

Hours worked by medium-skilled labor

Hours worked by high-skilled labor

Low-skilled labor compensation

Medium-skilled labor compensation

High-skilled labor compensation

Services
200
1801601401201008060402001995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Hours worked by low-skilled labor

Hours worked by medium-skilled labor

Hours worked by high-skilled labor

Low-skilled labor compensation

Medium-skilled labor compensation

High-skilled labor compensation

Source: Author’s calculation based on WIOD SEA.

Table 1 : SUR estimation results

𝑤𝐿𝑆
𝑤𝑀𝑆
𝑤𝐻𝑆𝑤𝐼𝐼
𝐾𝐺𝑂
𝐹𝑉𝐴𝑖𝑋

Obs.

(1)

(2)

(3)

𝑆𝐿𝑆

𝑆𝑀𝑆

𝑆𝐻𝑆

0.032812***-0.0084803***

0.0079017***(0.0006433)(0.0007472)(0.0012364)-0.0351033***

0.1413692***-0.1086694***(0.0030015)(0.0034867)(0.0057611)

0.0147123***-0.0210669***

0.1438633***(0.0017689)(0.0020548)(0.0033931)-0.0137395***-0.10375***-0.047401***(0.0017062)(0.0019824)(0.0033448)-0.0023595***-0.0129762***-0.0177739***(0.0005648)(0.0006562)(0.0010953)

0.0036245***0.0029765***0.0185238***(0.0009065)(0.0010532)(0.0017731)

0.0014706-0.0000998

0.001089(0.000635)
140(0.0007378)
140(0.0012473)
140

Notes: The set of equations are estimated by ISUR. Standard errors are reported in parentheses.
Full set of time and sector dummies are included in the estimation.
***,**,* Significant at the 1, 5 and 10 percent level respectfully.

ReferencesAmador, João, Rita Cappariello, and Robert Stehrer. 2015. "Global Value Chains: A View fromthe Euro Area." Asian Economic Journal 29 (2): 99-120.
Costinot, Arnaud, and Jonathan Vogel. 2010. "Matching and inequality in the world economy."
Journal of Political Economy 118 (4): 747-786.
Foster-McGregor, Neil, Robert Stehrer, and Gaaitzen J. de Vries. 2013. "Offshoring and the skill
structure of labour demand." Review of World Economics 149: 631-662.
Gereffi, G., and K. Fernandez-Stark. 2011. Global Value Chain Analysis: A Primer. Center on
Globalization, Governance & Competitiveness (CGGC), Duke University, North
Carolina, USA.
Timmer, Marcel P., ed. 2012. "The World Input-Output Database (WIOD): Contents, sources andmethods." WIOD Working Paper No. 10.