Trade and Labor-Allocation: Evidence from Sectoral Embodied Labor Transfer between China and Africa

Abstract

Under the influence of international trade, labor flow not only exists in the waves of international labor migration but is also embodied in international products and services. This paper focused on members of the China–Africa Cooperation Forum (FOCAC). We computed and analyzed the sectoral embodied labor transfer between China and Africa from 2000 to 2015 based on the Multiregional Input-Output Method. Our results are as follows: (1) Both China and Africa play roles as labor suppliers in the global supply chain. By ameliorating the trade structure, both China and Africa can better utilize their labor surplus. (2) China and Africa share complementarity in sectoral labor allocation. In short, the embodied labor transfer via international trade between China and Africa has, to some extent, relieved the labor shortage on both sides. (3) Africa has transformed into a net exporter of industrial labor since 2011. By analyzing the embodied labor flow from the global perspective, this paper beats a new path in depicting the effect of international trade on labor allocation, enriches the evaluation of embodied labor transfer between China and Africa, and also provides a beneficial supplement to Multiregional Input-Output analysis in the field of factor flows.

1. Introduction

International trade can boost economic growth by stimulating domestic productivity and competitiveness (Chang et al. 2009; Edwards 1998; Sakyi et al. 2014), facilitating global flow and reallocation of production factors such as capital, energy, and labor (Feenstra 2015; Goldberg and Pavcnik 2007; Matsumoto 2019). Factor endowment has long been the core of international trade, and labor, being one of the essential and special factors, shares an intricate relationship with international trade. On one hand, according to the theory of international trade based on factor endowment, nations rich in labor supply will specialize in the production and exportation of labor-intensive products (Fisher 2011; Roy 1967). Nations with different comparative advantages show different patterns in labor use, and research about the effect of trades on employment has blossomed rapidly (Auer and Fischer 2010; Balsvik et al. 2015; Bernard et al. 2006; Fatima and Khan 2019; Jiang 2015). On the other hand, opening up to international trade means a physical multi-regional and multi-industrial labor flow, hence a global reallocation of factor endowment (Autor et al. 2013; Costa et al. 2016).

The world today is a world of the intertwined, reciprocal, and migration (Cepeda-López et al. 2019). As statistics from the ILO (International Labour Organization) have shown, among the 232 million people who live outside their birth nations, nearly 65% are migrating workers. Mass labor flow has, in part, adjusted regional economic development and cultural structures, yet it does not necessarily accompany a promotion in personal welfare. Sometimes, it might even induce substantial costs for the migrators (Kasimis 2008; Rogaly 2008; Rye 2018), especially in developing countries. The friction in labor markets usually causes immense flowing costs (Artuc et al. 2015) as well as forced migration under limited freedom and extreme destitution, as described in the Human Development Report of UNDP (the United Nations Development Programme) and the World Bank Report. Furthermore, geographic flow means commuting costs, which can add to the stress on global resources and the environment.

In fact, international trade itself can trigger an embodied labor flow, which happens to be a factor with relatively high flowing costs. Embodied labor flow is, rather than in a geographic sense, a transfer and migration embodied in the production and consumption links of products and services that are traded across the globe. In this paper, we define the term embodied labor as the sum of labor invested, both directly and indirectly, in the production of one certain product or service. The term represents global labor use related to certain products and services, and thus we can depict the overall picture of whole-chain labor use from production to consumption. Concepts such as embodied energy (Camaratta et al. 2020; Chen and Chen 2011; Costanza 1980; Ji et al. 2020b, 2022; Wu et al. 2020), virtual land (Han and Chen 2018; Han et al. 2015; Ji et al. 2020a, 2023; Würtenberger et al. 2006), and embodied greenhouse gas emissions (Davis and Caldeira 2010; Huang et al. 2019; Ji et al. 2020c; Long et al. 2018; Peters and Hertwich 2006; Su et al. 2013) have been widely applied in international trade analysis.

However, research about trade-induced embodied labor flow is still rarely seen. Though the earliest study of similar ideas can date back to Bezdek’s research in 1974 about human resources, energy, and freeway trust funds, it was not until 2014 that specific and systematic labor footprint tracing sprang up. Alsamawi et al. (2014) developed a social footprint computing method based on the Input-Output model. From the consumption view, they divided the world into “owners”—those who enjoy other nations’ labor supply—and “servants”—those who supply their labor resources to other nations. They held that labor mainly flowed from developing countries to developed ones. Since then, the idea that trades could realize labor flow has slowly been accepted and rapidly developed abroad. Simas et al. (2014) quantified the relativity of bad labor conditions with international trade from the production side, differentiated the labor footprints of six specific dire labor conditions, including occupational health damage, employment of a vulnerable group, gender inequality, low-skilled employment and so on in the global production chain across seven regions. Their work revealed that labor suffering from such bad conditions mainly flows from developing countries to developed regions. Asia and Africa, in particular, have seen the most labor outflows. This research provided a brand-new perspective on revealing the social influence of globalization.

After that, Simas et al. (2015) computed the energy and labor embodied in the EU’s imports from the consumption side and found that the EU’s embodied labor import significantly overshadows its export, and about 30% of its labor import is low-skilled labor. Gómez-Paredes et al. (2015) took India as an example to evaluate the labor problems behind different production activities across the whole supply chain, covering collective bargaining, forced labor, child labor, gender inequality, hazardous employment, and social security. This analysis elaborated on the significance of the labor footprint in depicting social sustainability.

Hardadi and Pizzol (2017) calculated the social footprint based on ILO’s statistics of employment, working time, salary, occupational accidents, and unemployment, trying to quantify their impacts on productivity and social welfare. Their work greatly broadened the social horizon of theoretical analysis and achieved a milestone in social lifecycle evaluation. Alsamawi et al. (2017) calculated the occupational safety and health footprint of labor embodied in the consumption side to derive the number of accidents behind the global supply chain, calling for an urgent improvement of labor conditions.

Research combining the labor footprint and other economic indexes have also provided many constructive conclusions. Rocco and Colombo (2016) proposed the Bioeconomic Input-Output model based on the life cycle concept, internalizing labor into economic activities as a new production sector. Their research showed that the internalization of labor has changed the sum of energy embodied in products and services. Sakai et al. (2017) computed Britain’s emission and employment footprint, trying to figure out their relationship, driving factors, and sectoral components. This research provided a new angle for understanding the relationship among trading, environment, and development.

Based on the existing literature, we find that, for one, research on embodied labor flow, compared with that on other embodied factors (for example, energy and water), is still relatively new and booming. For another, there has not been any embodied labor flow research on two specific economies under economic globalization so far. All current and past research focuses on the state level rather than differentiating down to sectors. In addition, our limited documentary tracing has shown that there has not been any research on the embodied labor transfer relationship between China and Africa.

As populous economies, labor is of great significance to the economic development of China and Africa. By participating in global trade, China increases its global labor supply (Xu et al. 2018). However, with the deepening of the Reform and Open, the climbing of labor costs, and the depletion of its demographic dividend, China calls for an impending structural revolution. In Africa, over 50% of the population works as farmers, and the proportions involved in other occupations are all significantly lower than the global rate as reported by the ILO. Labor is a restraint on Africa’s economic development in two ways. First, Africa suffers from both a lack of labor and a relatively low-skilled labor supply. Second, compared with other production factors such as capital, land, and technology, the formation and development of labor requires a longer cycle and harsher conditions, which is more likely to become a potential bottleneck in Africa’s development. Existing discussions about China’s impact on Africa’s labor market in the context of international trade mainly focus on two topics: institutional impact and employment opportunities. For instance, Adolph et al. (2016) proposed a theoretical assumption called the “Shanghai Effect”, claiming that China’s exportation might affect Africa’s labor standard. Some researchers hold the idea that the massive inflow of cheap Chinese textiles and household electronic appliances has resulted in the shrinkage of relevant African sectors and mass unemployment (Peh and Eyal 2010; Kaplinsky and Morris 2008; Konings 2007).

According to World Development Indicators, the population growth rate of Sub-Sahara Africa reached 2.542% in 2022, while for EU countries this indicator is only 0.043%. Considering a broader global background with anticipated rapid population growth in Africa and the depopulation trends observed in Europe, as well as the increasing influence of China in the Silk Road Economic Belt region and even in the world, the future resolution of international labor flow will be paramount (Cepeda-López et al. 2019). Both China and Africa have been comprehensively and significantly affecting the quantity and spatial distribution of global production factor flow, and labor is undoubtedly an indispensable link in the chain. We estimated sectoral embodied labor transfer of trade under the Multiregional Input-Output (MRIO) framework, aiming to evaluate the sectoral labor allocation between China and Africa, to respond to existing discussions and to provide a new angle for both parties’ industrial cooperation and labor structural betterment. A discussion on the impact of embodied labor flow on labor allocation within the big picture of economic globalization will not only enrich the field of embodied factor studies but also beat a new path in terms of labor issues between China and Africa.

2. Methods and Data

2.1. Methods

Multiregional Input-Output (MRIO) analysis reflects the relationship between intermediate input and final demand among all regions and sectors within the global supply chain (see Appendix B for more details about the MRIO method). Exportation of a nation is seen as an inflow of other nations’ intermediate input and final demand. Importation is treated as an outflow of other nations’ intermediate input and final demand. Based on the MRIO and the employment sheet of the corresponding region, we can systematically compute labor use via global trade to arrive at the total sum of labor flow induced by the final demand embodied in the global supply chain. When simulating the global economy with the MRIO accounts, we can view the world as a world of m regions, each with n sectors.

Based on the MRIO balance, the total production of region s sector j ($x_j^s$) consists of two different sections: its production of intermediate input toward other regions and sectors ($z_{ji}^{sr}$) and its production applied in final demands of other regions and factors ($f_j^{sr}$). The balancing equation is as follows:

$$x_j^s=\sum _{r=1}^m\sum _{i=1}^n{z}_{ji}^{sr}+\sum _{r=1}^m{f}_j^{sr}$$

(1)

Rewrite the equation in the matrix form:

$$X=Z+F=AX+F$$

(2)

The matrix can be expressed as follows:

$$\left[\begin{array}{c}{x}^1\\ x^2\\ ⋮\\ x^m\end{array}\right]=\left[\begin{array}{c}{A}^{11}{A}^{12}{A}^{13}\cdots A^{1m}\\ A^{21}{A}^{22}{A}^{23}\cdots A^{2m}\\ ⋮\\ A^{m1}{A}^{m2}{A}^{m3}\cdots A^{mm}\end{array}\right]\left[\begin{array}{c}{x}^1\\ x^2\\ ⋮\\ x^m\end{array}\right]+\left[\begin{array}{c}{y}_{1i}\\ y_{2i}\\ ⋮\\ y_{mi}\end{array}\right]$$

Then we can get the key equation:

$$X={(I-A)}^{-1}F$$

(3)

$X$ refers to the total production matrix ($X={{[x}_j^s]}_{1\times mn}$), $Z$ refers to intermediate input matrix ($Z={{[z}_{ij}^{rs}]}_{mn\times mn}$), $A$ refers to the sectoral input coefficient matrix ($A=Z,A={{[a}_{ij}^{rs}]}_{mn\times mn}$), and $F$ is the matrix of final demand ($F={{[f}_j^{sr}]}_{1\times mn}$).

The total labor embodied in final demand equals direct labor intensity times total production, the equation being:

$$Q_f=L{\widehat{X}}^{-1}{(\mathrm{I}-A)}^{-1}F$$

(4)

$$\left[\begin{array}{c}{q}^{11}{q}^{12}\cdots q^{1m}\\ q^{12}{q}^{22}\cdots q^{2m}\\ ⋮\\ q^{1m}{q}^{2m}\cdots q^{mm}\end{array}\right]=\left[\begin{array}{c}{l}^1/x^1\\ 0\\ \cdots \\ 0\end{array}\begin{array}{c}0\\ l^2/x^2\\ \dots \\ 0\end{array}\begin{array}{c}\cdots \\ \cdots \\ \ddots \\ \cdots \end{array}\begin{array}{c}0\\ 0\\ \cdots \\ l^m/x^m\end{array}\right]\left[\begin{array}{c}{b}^{11}{b}^{12}\cdots b^{1m}\\ b^{12}{b}^{22}\cdots b^{2m}\\ ⋮\\ b^{1m}{b}^{2m}\cdots b^{mm}\end{array}\right]\left[\begin{array}{c}{f}^{11}{f}^{12}\cdots f^{1m}\\ f^{12}{f}^{22}\cdots f^{2m}\\ ⋮\\ f^{1m}{f}^{2m}\cdots f^{mm}\end{array}\right]$$

Hence, the embodied labor flow from region r to region s equals:

$$q^{rs}=\sum _k{l}^r{\widehat{x}}^{r-1}{B^{rk}}^{-1}{f}^{ks}$$

(5)

$L$ refers to total employment ($L={{[l}_j^s]}_{1\times mn}$), $\widehat{X}$ is the diagonal matrix of total production matrix $X$ ($\widehat{X}=\mathrm{d}\mathrm{i}\mathrm{a}\mathrm{g}(X)$), and $B={(I-A)}^{-1}$ is the Leontief inverse matrix and reflects the direct and indirect input required in each unit of the final demand ($B={[b_{ij}^{rs}]}_{mn\times mn}$).

We can calculate the labor requirement embodied in the final demand of region s, the labor embodied in the final demand (LEF):

$${LEF}^s=\sum _{ijrt}{l}_i^r{\widehat{x}}^{r-1}{b}_{ij}^{rt}{f}_j^{ts}$$

(6)

Likewise, the labor force (LF) of region s equals:

$${LF}^s=\sum _{j=1}^n{l}_j^s$$

(7)

Thus, the labor inflow embodied in the final demand (LEFI), the labor outflow embodied in final demand (LEFE), and the net labor inflow embodied in final demand (LEFTB) of region s are as follows:

$${LEFI}^s=\sum _{ijrt,t\ne s}{l}_i^r{\widehat{x}}^{r-1}{b}_{ij}^{rt}{f}_j^{ts}$$

(8)

$${LEFE}^s=\sum _{ijrt,t\ne s}{l}_i^r{\widehat{x}}^{r-1}{b}_{ij}^{rs}{f}_j^{st}$$

(9)

$${LEFTB}^s={LEFI}^s-{LEFE}^s$$

(10)

2.2. Data Source

The Eora database has the most extensive coverage of African nations as well as a long time-span, both facilitating a consistent and comprehensive analysis of the embodied labor transfer between Africa and China. In this paper, we matched the members of the FOACA and those within the Eora global MRIO database to select China and 50 African nations (in later parts the term “African countries” refers to all 50 African participants, and the country list is displayed in

Table A1. Economic and geographical indicators of fifty African participants in FOCAC.

GDP Ranking	Country	Per-Capita Income	Location
1	Nigeria	Low-middle income	Coastal
2	Egypt	Low-middle income	Coastal
3	South Africa	High-middle income	Coastal
4	Algeria	High-middle income	Coastal
5	Angola	Low-middle income	Coastal
6	Morocco	Low-middle income	Coastal
7	Sudan	Low-middle income	Coastal
8	Ethiopia	Low income	Inland
9	Kenya	Low-middle income	Coastal
10	Ghana	Low-middle income	Coastal
11	Tanzania	Low income	Coastal
12	Tunisia	Low-middle income	Coastal
13	Cote d’Ivoire	Low-middle income	Coastal
14	DR Congo	Low income	Coastal
15	Cameroon	Low-middle income	Coastal
16	Libya	High-middle income	Coastal
17	Rwanda	Low income	Inland
18	Zambia	Low-middle income	Inland
19	Zimbabwe	Low income	Inland
20	Senegal	Low income	Coastal
21	Mozambique	Low income	Coastal
22	Botswana	High-middle income	Inland
23	Gabon	High-middle income	Coastal
24	Mali	Low income	Inland
25	Mauritius	High-middle income	Island
26	Namibia	High-middle income	Coastal
27	Chad	Low income	Inland
28	South Sudan	Low income	Inland
29	Burkina Faso	Low income	Inland
30	Madagascar	Low income	Island
31	Guinea	Low income	Coastal
32	Congo	Low-middle income	Coastal
33	Benin	Low income	Coastal
34	Rwanda	Low income	Inland
35	Niger	Low income	Inland
36	Somalia	-	Coastal
37	Malawi	Low income	Inland
38	Mauritania	Low-middle income	Coastal
39	Eritrea	-	Coastal
40	Sierra Leone	Low income	Coastal
41	Togo	Low income	Coastal
42	Liberia	Low income	Coastal
43	Burundi	Low income	Inland
44	Lesotho	Low-middle income	Inland
45	Djibouti	Low-middle income	Coastal
46	Cape Verde	Low-middle income	Island
47	Central African Republic	Low income	Inland
48	Gambia	Low income	Coastal
49	Seychelles	High income	Island
50	Sao Tome and Principe	Low-middle income	Island

in Appendix A) as our samples, covering a period of 16 years from 2000 to 2015. These 50 African nations cover all four income levels—high income, higher-middle income, lower-middle income, and low income. Geographically, these 50 nations cover all inland, coastal, and island types.

The International Labor Organization (ILO) Database supplied us with labor data of the three industries of the major nations, yet lacks detailed sectoral statistics for most African countries. Taking data availability into consideration, we bracketed the origin labor data into three categories: Agriculture labor, Industrial labor, and Service labor. The sectoral labor employment is derived by comparing and merging the ILO and IMF databases, with a unit of thousand. The Eora global MRIO database consists of 189 regions and 26 sectors. To match the labor employment data of the three industries, we bracketed the 26 sectors of the Eora Input-Output table into Agriculture, Industry, and Service correspondingly.

3. Results

3.1. Labor Force and Embodied Labor in Final Demand of China and Africa

3.1.1. Labor Force and Labor Use of China and Africa

Figure 1 depicts the labor force (LF) and labor use (LEF) of China and Africa from the year 2000 to 2015, the latter being the total labor embodied in the final demand. Apart from the above, we could also calculate each nation’s embodied-employment labor ratio (LEF/LF). The ratios of both China and Africa revealed a climbing trend, which gradually approached 1. This indicated a mounting desire for labor from other regions to meet their final demand.

Firstly, according to the total amount and ratio, we found that both economies’ labor force overweighed their embodied labor. This means that they had more labor resources than the labor used in their final demand, by reference acting as labor suppliers within the global value chain, which is consistent with previous research (Simas et al. 2015; Alsamawi et al. 2014). Moreover, China exceeded Africa both in labor force and embodied labor in demand. During our research period, the labor force in China remained relatively stable within the range of 712.98 to 764.96 million. Embodied labor in China’s final demand showed a mild climbing trend with fluctuations, reaching a growth peak of 7.38% between the years 2008 and 2009. Africa revealed a powerful growing tendency, for its labor force and embodied labor in demand were increasing year by year with a growth rate of 54.59% and 73.32%, respectively.

Figure 2 reveals the sectoral proportion of labor embodied in the final demand (see the details in

Table A2. Proportion of embodied labor in final demand in China, 2000~2015 (unit: thousands of people).

Year	Labor Embodied in Final Demand	Labor Embodied in Final Consumption	Final Consumption (Household)	Final Consumption (Non-Profit Institutions)	Final Consumption (Government)	Others (Gross Fixed Capital Formation etc.)
2000	559,202	358,533	263,740	7397	87,396	200,670
2001	573,612	364,743	263,805	7420	93,518	208,869
2002	577,723	366,524	264,020	7453	95,051	211,199
2003	572,515	355,534	253,446	7257	94,830	216,981
2004	562,776	343,602	245,667	7162	90,773	219,174
2005	562,098	341,754	243,796	7157	90,801	220,345
2006	557,888	338,659	241,174	7204	90,281	219,229
2007	569,497	335,771	241,720	7328	86,722	233,726
2008	584,142	342,282	245,404	7487	89,391	241,860
2009	634,359	369,468	262,849	7921	98,698	264,891
2010	631,978	363,213	258,765	8071	96,377	268,765
2011	638,812	362,705	260,197	8327	94,182	276,106
2012	647,663	370,710	266,912	8584	95,214	276,952
2013	660,252	378,961	267,334	8634	102,993	281,290
2014	663,361	375,028	265,884	8683	100,462	288,333
2015	666,767	363,596	260,139	8557	94,910	303,171

and

Table A3. Proportion of embodied labor in final demand in Africa, 2000~2015 (unit: thousands of people).

Year	Labor Embodied in Final Demand	Labor Embodied in Final Consumption	Final Consumption (Household)	Final Consumption (Non-Profit Institutions)	Final Consumption (Government)	Others (Gross Fixed Capital Formation etc.)
2000	212,889	176,166	133,717	13,013	29,434	36,723
2001	220,423	181,691	137,261	13,837	30,593	38,732
2002	226,810	186,747	140,877	14,306	31,564	40,063
2003	233,933	192,477	144,893	14,962	32,622	41,456
2004	240,191	197,084	148,652	15,168	33,263	43,107
2005	248,032	203,434	153,429	15,783	34,222	44,598
2006	255,949	208,903	157,671	16,372	34,861	47,046
2007	265,195	216,355	163,264	17,041	36,050	48,840
2008	283,701	230,431	173,766	17,385	39,280	53,270
2009	295,197	239,965	180,061	17,857	42,047	55,233
2010	300,193	243,439	182,525	18,313	42,601	56,754
2011	303,467	245,822	184,418	18,860	42,544	57,645
2012	315,005	254,023	190,114	19,630	44,278	60,983
2013	326,152	263,908	196,450	20,596	46,862	62,244
2014	334,018	267,871	199,669	20,846	47,356	66,147
2015	343,810	276,289	206,415	21,514	48,361	67,521

in Appendix A). The final demand can be classified into two parts: final consumption and others (such as total fixed assets and investments). Final consumption consists of three categories, namely household final consumption, government final consumption, and non-profit institutional serving households’ consumption. During the study period, labor embodied in the final consumption made up 55~65% of the total embodied labor with a steady decrease. As for Africa, the rate was over 80% with a decreasing trend at the same time, although the decreasing rate was lower than that of China. In both economies, among all embodied labor in final consumption, the household final consumption contributed the most to the proportion, accounting for more than 70%. Compared to China, Africa utilized more labor to meet its needs for household final consumption.

3.1.2. Sectoral Contribution of Labor Force and Embodied Labor of China and Africa

Figure 3 reveals the sectoral contribution of the labor force and embodied labor of China and Africa. China’s total labor force has remained stable, yet the sectoral structure has transformed significantly. Labor force in the agricultural sector plunged while that in the service sector soared. During the years 2005 and 2006, the labor force in the agricultural sector first shrank to a size smaller than that in service. Then in the year 2008, it was even lower than the industrial sector, the lowest of all three. Since 2005, the service sector has become the sector consuming the most substantial fraction of the total labor force. Until 2015, the sectoral proportions of the labor force in the agricultural sector, industrial sector, and service sector were 20%, 27%, and 53% respectively. Among all the three sectors of China, the industrial sector had the largest amount of embodied labor, followed by the service sector and agricultural sector in that order. Embodied labor in the industrial sector and service sector climbed steadily while that in the agricultural sector kept decreasing. Until 2015, sectoral proportions of embodied labor in the agricultural sector, industrial sector, and service sector were 14%, 40%, and 46% respectively.

As for Africa, among all three sectors, the agricultural sector contributed to the majority of the labor force, followed by the service sector and the industrial sector. The labor force in the agricultural sector took up about 60% at its peak. The quantities of labor in the service and industrial sectors were relatively low, yet climbing steadily. As for the sectoral contribution of labor use embodied in the final demand, the service sector ranked first among all three sectors of Africa, followed by the industrial sector and agricultural sector. Labor embodied in the agricultural sector mostly remained stable, while that of the other two sectors increased consistently.

3.1.3. Total Labor Force and Embodied Labor of African Countries

In Figure 4, the x-axis and y-axis reflect the total labor force and total embodied labor in final demand of the 50 African countries from the year 2000 to 2015. As depicted in the figure, most African countries have a relatively small scale of both labor force and labor use, all less than 200 million. Nigeria, Egypt, DR Congo (the Democratic Republic of Congo), South Africa, Kenya, and Tanzania stand out from the crowd. The quantities of South Africa’s and Kenya’s embodied labor in their final demand surpass their own labor force, by 18.99 and 7.76 million, respectively. Nigeria, Egypt, DR Congo, and Tanzania all have a domestic labor force higher than labor embodied in the final demand, especially Nigeria and Tanzania, with a surplus of 134.12 and 145.26 million, respectively. Although Ethiopia enjoys a large-scale domestic labor force, its tiny labor use is absorbed in the final demand, indicating a giant gap between a large labor supply and a small labor demand.

3.2. The Feature of Embodied Labor Transfer between China and Africa

3.2.1. Embodied Labor Transfer between China and Africa

Figure 5 reveals the total and net flow of embodied labor transfer from China and Africa to each other derived by their final demand (see

Table A4. Embodied labor transfer between China and Africa, 2000~2015 (unit: millions of people).

Labor Flow from China to Africa	Agriculture	Industry	Service	Labor Flow from Africa to China	Agriculture	Industry	Service
2000	580	716	380	2000	2669	210	198
2001	547	694	389	2001	2777	226	219
2002	539	703	419	2002	3103	248	241
2003	606	859	513	2003	3134	297	285
2004	682	982	627	2004	3472	351	342
2005	706	1070	749	2005	3789	394	399
2006	766	1230	914	2006	4323	462	483
2007	785	1349	1109	2007	5081	578	586
2008	740	1344	1144	2008	5321	573	557
2009	580	1132	982	2009	5924	616	539
2010	593	1226	1117	2010	7327	798	750
2011	587	1295	1248	2011	7775	958	928
2012	550	1288	1284	2012	8015	991	949
2013	501	1215	1266	2013	8373	1035	1010
2014	450	1175	1307	2014	8761	1139	1149
2015	384	1077	1312	2015	8792	1177	1257

in Appendix A for details). The result shows a turning point in 2008. Before 2008, embodied labor flow from China toward Africa outstripped that of vice versa, meaning that Africa utilized more of China’s labor to meet its final demand than China utilized the labor of Africa. After 2008, China transformed into a net importer of embodied labor, which means that China mobilized more African labor to meet its demand. This phenomenon can be partly attributed to the steady increase of net labor inflow of all three sectors from Africa toward China. The exportation of embodied labor from China toward Africa showed a climbing tendency from 2000 to 2008, with a significant drop affected by the global financial crisis in 2009, a short rebound, and finally a faint drop again during 2012~2015. From 2000 to 2015, the labor embodied in China’s imports from Africa mounted consistently with considerable growth, especially during the years 2009~2010, with a growth rate reaching 25%. During our study period, China realized a net labor import and the net amount continued to increase.

Figure 6 depicts the embodied labor transfer between China and the African countries. The bubbles represent the fifty African countries. The x-axis and y-axis reflect the net outflow of embodied labor from China to Africa and the net inflow of embodied labor from Africa to China. The size of the bubble symbolizes the amount of net embodied labor flow. As depicted in the picture, the relationship between China and African countries varied significantly. South Africa, Egypt, Nigeria, and Algeria were all giant net importers of embodied labor. China exported 3.96, 2.13, 1.89, and 1.27 million embodied labor toward these four countries, respectively. Ethiopia and Angola are great net exporters, especially Ethiopia, which had a shocking 21.06 million of net embodied labor outflow toward China during the sixteen years, much greater than any other African country. By scale, the biggest embodied labor flow appeared for the net exporters Ethiopia and Angola, and the net importer South Africa.

Figure 7 depicts the labor transfer between China and the African countries with prominent embodied net labor flows on a map (unit: million) in order to capture the geographical characteristics. Obviously enough, most of Africa’s net inflow and outflow of labor are coastal countries, except for Ethiopia. As shown in the picture, South Africa, Egypt, and Algeria were all stable net importers, bearing 3.8, 1.9, and 1.2 million, respectively, of China’s embodied labor outflow during the 16 years, while Ethiopia, Angola, and Tanzania were the net exporters, supplying China with 20.9, 3.8, and 1.2 million, respectively, of embodied labor during 2000 to 2015. Ethiopia was the paragon of all net exporters, whose outflow outstripped all others, mounting from about 0.6 million in 2000 to about 3.5 million in 2015, an almost six times increase in size. Recently, more and more countries have transformed into China’s net exporters, Cameroon, for example.

3.2.2. Sectoral Distribution of Embodied Labor Transfer between China and Africa

Figure 8 reflects the changes in the sectoral distribution of embodied labor transfer from 2000 to 2015. From the sector distribution of embodied labor transfer, China and Africa differentiate in labor utilization. For one thing, China’s embodied labor exportation toward Africa mainly assembled in the industrial and service sector, with the industrial sector always playing a leading role. The service sector, on the other hand, overtook the agricultural sector in 2005 and the industrial sector in 2012, and finally became China’s largest source of embodied labor outflow toward Africa. Both the total amount and the proportion of embodied labor flow in the agricultural sector have declined considerably, indicating that Africa is in massive need of China’s industrial and service labor to meet its demand. For another, labor in the agricultural sector took up the largest proportion of embodied labor flow from Africa to China, while the embodied labor flow in the industrial sector and service sector were of a relatively similar size.

The net flow of labor between China and Africa derived by the final demand was from Africa to China, which can be mainly attributed to the huge net supply of embodied labor in the agricultural sector from Africa to China. In other words, China has mobilized an enormous amount of Africa’s agricultural labor to meet its final demand. As for the industrial and service sectors, China acted as a net embodied labor exporter toward Africa, indicating that Africa was utilizing China’s industrial and service labor to meet its final demand. Since 2008, China’s net outflow of embodied labor in the industrial and service sectors has been gradually reducing, while the labor supply of the industrial and service sectors has been increasing in the global value chain. Especially after 2012, embodied labor flow in the service sector was a net flow from Africa to China, indicating a turning point in the final demand, China’s utilization of African service labor exceeded Africa’s utilization of Chinese service labor.

3.2.3. Sectoral Contribution of Embodied Labor Transfer between China and Typical African Countries

To further explore the sectoral feature of embodied labor transfer between China and African countries, we selected the four examples with the most remarkable scale—Ethiopia, South Africa, Nigeria, and Egypt to analyze in detail their respective total amounts and sectoral structures of their embodied labor flows with China (as depicted in Figure 9). Firstly, we calculated the embodied labor transfer between China and Egypt, South Africa, Nigeria, and Ethiopia between 2000 and 2015. We found that, for Egypt, Nigeria, and South Africa, China acted as a net labor exporter, while for Ethiopia, China acted as a net importer. The flow of embodied labor transfer between China and South Africa and that between China and Egypt shared similar trends: the net labor inflow into China mounted since 2000, reaching the apex in 2013 and dropped slightly in the following two years. Meanwhile, China’s labor inflow to Egypt and South Africa showed a decreasing trend, hitting the bottom in 2003 and 2009 and reaching the peak in 2007 and 2008. The embodied labor flow from Nigeria into China kept climbing before 2011, then declined, and slowly went up again after 2013. The embodied labor flow from China to Nigeria mounted with fluctuations, reaching the peak in 2013 and dropping slightly afterward. Ethiopia’s embodied labor inflow to China far outnumbered all three countries with a rapid growth rate over five times theirs, while China’s labor flow into Ethiopia was relatively low, although mounting.

Secondly, we analyzed the sectoral contribution of embodied labor transfer. During the study period, the proportion of China’s embodied labor flowing into the four countries increased gradually in both the industrial sector and the service sector. While the proportion of labor in the agricultural sector climbed first and then fell, the embodied labor flow from South Africa to China mainly remained in the industrial and service sectors. The flow from Egypt, Nigeria, and Ethiopia to China concentrated on the agricultural sector, though the flow of the industrial and service sectors was slowly climbing.

This result is quite consistent with the previous research of Eisenman (2012) who holds the view that China’s comparative advantage in capital-intensive production and Africa’s abundant natural resource endowments are two of the key factors for China-Africa trade. Agriculture in Ethiopia has long been occupying the largest proportion of embodied labor outflow. Though the industrial and service sectors may have low embodied labor outflow, the growth rate was considerable. This phenomenon denotes the fact that China has utilized a gigantic amount of Ethiopia’s agricultural labor, and its reliance on Ethiopia’s industrial and service labor is also mounting. South Africa was the largest embodied labor net importer, with the flowing trend of its three sectors intercepting one another with time. The embodied labor inflow in the agricultural sector decreased with fluctuation while the inflow of the other two sectors increased with fluctuation. Net embodied labor inflow in the service sector reached the same level as that of the industrial sector at around 2011 and then outstripped the latter after 2011, denoting that Africa’s demand for China’s agricultural labor was declining while that for China’s industrial and service labor was ascending.

4. Sectoral Labor Allocation behind the Embodied Labor Transfer between China and Africa

4.1. Complementarity of Embodied Labor Transfer between China and Africa

The embodied labor flow between China and Africa can in part reflect their complementarity of sectoral labor utilization. On the one hand, Africa supplied more agricultural labor resources, which exceeded its own final demand, and has realized a net outflow of embodied agricultural labor to China. In other words, China mobilized Africa’s surplus agricultural labor. On the other hand, through global trade, Africa was able to take advantage of China’s vast supply of industrial labor to relieve its own massive demand in the early stage of industrialization.

This phenomenon was the result of a rational choice, tallying with the comparative advantages of both sides. Africa had a small demand for agricultural resources, with a supple stock and a comparative advantage in production factors. Meanwhile, its industry—especially manufacturing—lagged behind and was in dire need of medium- and high-level industrial capacity to meet the needs of domestic production and consumption. The labor transfer embodied in trade provided Africa with such an opportunity to utilize China’s industrial labor resources to realize its own industrialization, which not only ameliorated its own employment status and addressed its shortage of industrial and service labor supply, but also alleviated China’s shortage of agricultural labor. As for the sectoral embodied labor transfer trend, although agriculture ranked first among all Africa’s three sectors in embodied labor outflow, the other two sectors—industry and service—both showed a climbing trend. The service sector, in particular, even became a net exporter of labor to China after 2012. This was strong evidence of Africa’s growing capacity to export industrial products and China’s increasing use of African labor in the service sector. Therefore, the labor market and industrialization level of Africa was not hampered. Quite the opposite; by the labor flow embodied in trade, both China and Africa could exert their comparative advantage and realize labor allocation betterment.

4.2. China’s Utilization (Amelioration) of Africa’s Labor Surplus (Shortage)

Trade accompanied a massive embodied labor flow. Agriculture labor occupied a significant proportion of the embodied labor transfer between China and Africa. Via trade, Africa’s surplus agricultural labor resources were utilized, while its labor shortage in the industrial and service sectors was relieved.

We further derived the sectoral contribution of the net inflow (outflow) of embodied labor between China and Africa to the utilization of labor surplus (shortage) in Africa from 2000 to 2015. Such a contribution ratio could be calculated through the following equation:

$$R=LEFTB/(LF-LEF)$$

(11)

Table 1. Contribution ratio of China’s utilization (amelioration) of Africa’s labor surplus (shortage) through embodied labor transfer.

Year	Total Labor Force	Agricultural Sector	Industrial Sector	Service Sector
2000	0.94%	0.20%	8.58%	1.58%
2001	0.75%	0.36%	7.87%	1.41%
2002	0.56%	0.60%	7.41%	1.43%
2003	0.70%	0.72%	8.91%	1.76%
2004	0.68%	0.78%	9.35%	1.94%
2005	0.73%	1.06%	9.45%	2.26%
2006	0.71%	1.39%	10.49%	2.69%
2007	0.33%	2.12%	10.88%	3.03%
2008	0.30%	2.55%	15.38%	3.48%
2009	1.13%	3.68%	11.64%	2.05%
2010	2.36%	4.95%	10.26%	0.54%
2011	3.02%	5.50%	8.25%	−0.15%
2012	3.28%	5.78%	7.78%	−0.08%
2013	3.78%	6.08%	6.06%	−0.86%
2014	4.40%	6.66%	3.98%	−1.29%
2015	4.64%	6.81%	2.29%	−1.50%

reveals China’s total and sectoral contribution ratio of utilization (amelioration) of Africa’s labor surplus (shortage). The embodied labor transfer between China and Africa could make use of Africa’s redundant agricultural labor, alleviate its labor shortage in the industrial and service sectors, and show a tendency to improve Africa’s industrial and service development. As can be seen from Table 1, both the total amount of Africa’s surplus labor utilized by China and the ratio of Africa’s agricultural sector mounted consistently, while that of the industrial and service sectors first climbed and then fell. Until 2015, China utilized 4.64% of Africa’s labor surplus. China’s net imports of Africa’s embodied agricultural labor as well as the contribution ratio of the agricultural sector kept climbing and the ratio reached 6.81% in 2015. The contribution ratio of the industrial sector reached its peak in 2008 then plunged for a while. China’s contribution to Africa’s service sector turned negative as a result of its net imports of embodied labor from Africa in 2011.

5. Conclusions and Implications

5.1. Conclusions

Labor flow embodied in trade directly reflects the industrial development and employment status of relevant nations, and exerts a significant impact on labor flow and allocation among countries. We applied the MRIO method to calculate the embodied labor transfer of the agriculture, industrial, and service sectors between China and fifty African participants in FOCAC from 2000 to 2015. According to our results, we arrived at the following conclusions:

• Both China and Africa play roles as labor suppliers in the global value chain. By promoting trading structure and rationalizing economic layouts, both China and Africa can provide employment opportunities to their surplus labor without the need of geographic migration. The embodied labor flow via trade can cast new lights on exerting both economy’s comparative advantages and realizing optimal cross-regional and cross-sectoral labor allocation.
• China and Africa share certain complementarity in cross-sectoral labor usage, which, to some extent, can alleviate the bottleneck of labor they face in their economic development. Trade is a choice based on the comparative advantages of both sides. China’s mass utilization of Africa’s redundant agricultural labor in the global production chain can not only alleviate Africa’s employment plight but also relieve its own predicament of a constantly decreasing supply of agricultural labor. Meanwhile, providing Africa with China’s industrial and service labor can make up for the current lack of industrial and service labor supply in Africa to some extent.

5.2. Implications

Based on our study, we could arrive at the following inspirations:

Firstly, reallocation of labor does not necessarily mean cross-regional geographic migration. It can also be achieved by rationalizing economic industry layout, improving trade structure, and adjusting the embodied labor flow via trade. Since labor is one critical production factor, migration is an important yet not indispensable way to optimize resource allocation. Moreover, embodied labor flow could avoid the economic and social burdens such as commuting, living, and emotional costs that would have been inevitable in cross-regional labor migration.

Secondly, this study provides a supplement to existing studies on the effect of trade on Africa’s labor market, offering a new lens to evaluate such impact. Apart from studying the impact on labor standards and employment, this paper has proven that trade benefits both economies by advantage complementarity and labor allocation betterment. Trading with China not only proffers vast employment opportunities for Africa’s immense agricultural labor but also helps China harness Africa’s demographic dividend to tackle its own predicament of decreasing labor.

Lastly, based on our analysis of the embodied labor flow between China and Africa, we state that the allocation of labor resources between China and Africa can be further optimized. While strengthening the trade link with China, the optimized transfer of embodied labor in the agricultural, industrial, and service sectors should be guided according to the characteristics of each sector. China should maintain intimate contact with Africa in agricultural trade to fully utilize its advantages in arable land and labor resources, raise the added value of industrial products, strengthen the link in service trade, and increase service export to tackle the labor surplus in China’s service sector and labor shortage in Africa’s corresponding sector.