International Labor Value Transfers Through Unproductive-Sector Trade

Abstract

This article explores a unique mechanism of international labor value transfers: unproductive-sector trade. We develop a model incorporating unproductive sectors and use data from the World Input-Output Database (2000–2014) to estimate these transfers. Analyzing trade patterns and value transfers for 16 countries, we find a growing importance of unproductive-sector trade in international value transfer. Notably, the United States and the United Kingdom have increasingly relied on this channel for labor value appropriation from other countries, while China has transitioned from a country with net value outflow to one with net value inflow, because of its decreasing net outflow of value through the productive-sector trade channel and its increasing net inflow of value through the unproductive-sector trade channel.

JEL Classification: B51, F14

Keywords

unproductive-sector trade international value transfers unequal exchange

1. Introduction

Since the 2008 global financial crisis, global economic growth has stagnated, further exacerbated by the COVID-19 pandemic. The escalation of international trade conflicts, culminating in the unprecedented trade war between the United States and China, challenges the existing international growth regime and trade system. In this context, it is crucial to analyze current international trade characteristics, especially the generation and distribution of trade gains, to gain insights into future trade evolution.

When evaluating trade gains, the mainstream neoclassical approach focuses on welfare analysis based on subjective utility and comparative advantages. In contrast, Marxian economics, using the labor theory of value, considers international labor value transfers as an indicator of a country’s trade gains or losses. Emmanuel (1972) introduced the concept of unequal exchange, identifying its mechanism in trade among productive sectors and attributing it to price/value deviations driven by wage differentials across borders. Despite its limited scope and controversies, Emmanuel’s theory offers a valuable Marxian perspective on the distribution of trade gains through labor value transfers.

However, many studies indicate that major developed countries have undergone significant deindustrialization and financialization, reducing the output share of productive sectors while increasing that of unproductive sectors (e.g., Paitaridis and Tsoulfidis 2012; Rieu and Park 2020). Additionally, international trade involving unproductive sectors has grown substantially. Consequently, it is necessary to reexamine the traditional unequal exchange theory in the context of the rising significance of unproductive sectors.

This article examines the mechanism of international labor value transfers through unproductive-sector trade, providing new insights into global trade dynamics. By developing a model that incorporates unproductive sectors and analyzing data from the World Input-Output Database (WIOD) (2000–2014), we reveal shifting patterns in value transfers across sixteen countries. Unlike existing studies, which often fail to distinguish between productive and unproductive sectors, our findings highlight the growing importance of unproductive sectors in capturing international value, especially for the United States and the United Kingdom. We also challenge the characterization of China as a net value outflow country, showing that since the global financial crisis, China has transitioned to a net value inflow country, largely because of its expanding unproductive wholesale trade sector. This study broadens the scope of unequal exchange theory, suggesting that traditional models may overlook the significant role of unproductive sectors, especially as deindustrialization and financialization have reshaped developed economies. Our analysis calls for a reassessment of international trade characteristics, particularly in light of the post-2008 global stagnation, the COVID-19 pandemic, and the rising trade conflicts, such as the US-China trade war. By incorporating unproductive sectors into the analysis, this article provides a more comprehensive understanding of contemporary trade dynamics and their implications for global economic policies and the equitable distribution of trade gains.

2. Theoretical Foundations

Evaluating trade benefits is a significant aspect of international trade research. Unlike neoclassical trade theories, which focus on comparative advantage and utility value theory (Ricardo 1817; Ohlin 1935; Krugman 1979, 1980; Melitz 2003), Marxian economics views international trade as transnational labor exchange and measures trade gains through international value transfers. The systematic and persistent occurrence of international value transfers is often termed unequal exchange.

2.1. Productive versus unproductive labor/sector

According to the Marxian labor theory of value, only productive labor in productive sectors contributes to value creation. Thus, it is important to distinguish the two types of labor and sectors. However, this distinction has been a contentious issue within Marxian economics. The most recent debate on this issue was played out mainly between Laibman and Mohun, joined by others. According to Marx (1963: 152), in principle, productive labor refers to labor that is hired by capital and generates surplus value for capital, while unproductive labor is characterized by the absence of value creation and the involvement in the redistribution of surplus value created by productive labor. This is dubbed the “analytic” definition by Laibman (1992: chapter 4), who nonetheless argued that it is impossible to establish an operational criterion to identify workers who do or do not create value or surplus value. Consequently, he suggested abandoning this distinction.

Mohun (1996), in response, developed a criterion to differentiate productive and unproductive labor based on the circuit of capital, which is also the approach found in Rubin (1973). That is, only labor performed in the production sphere that transforms productive capital into commodity capital is productive, while labor involved in the circulation sphere that either transforms capital from the money form into the productive form or from the commodity form into the money form is unproductive. This perspective does not persuade Houston (1997) and Laibman (1999). They believed that it is impossible to clearly delimit the production sphere and the circulation sphere, because, even in the traditionally identified circulation sphere, concrete labor is indispensable and use value in the Marxian sense is also being produced. Therefore, production and circulation take place simultaneously rather than subsequently. On this further issue, Mohun’s response retreated to the position that if the distinction of productive and unproductive labor was abandoned, the theoretical foundation of the labor theory of value would be endangered (Mohun 1996), which, for example, renders the Marxian theory of accumulation unconvincing in explaining the US experience of capital accumulation (Mohun 2002). Laibman’s critique on the lack of an operational criterion in differentiating productive and unproductive labor, as well as the production sphere and circulation sphere, is not adequately addressed.

Cámara (2006) argued that the previous debate has wrongly focused on the production of use-value in differentiating productive and unproductive labor—it is impossible to make this differentiation because all labor activities are productive of some kind of use-value. Instead, he proposed to take a value-oriented perspective: “The classification of productive and unproductive labour needs microeconomic foundations, based on the analysis of the valorization process of every branch of production” (Cámara 2006: 56). However, this perspective still needs to presume what counts and what does not count as a valorization process.

Thus, the proponents of the so-called analytic definition discussed above cannot escape from circular reasoning, simply because the definition itself is put forth in a circular way. Therefore, we argue that Marx’s definition of productive and unproductive labor is indeed not analytic but instead axiomatic. To us, Marx axiomatically categorized wage labor under the capitalist mode of production into two categories: one produces commodities (and services) while the other facilitates the buying and selling of the commodities produced or performs other social functions. The former is called productive labor, which creates value and surplus value, while the latter is called unproductive labor that does not create value. The line between production and other activities is, undoubtedly, not always clear. But this does not mean we should not draw the line. The usefulness of the distinction between productive and unproductive labor, taken as an axiomatic construction, should be judged according to its explanatory power of the real world, which is also within the scope of this paper.

Various scholars have provided their delimitation of productive and unproductive labor, by and large conforming to Marx’s categorizations found in his various works. The dispute concerns mainly three types of labor: supervisory labor hired by capital, labor hired by the state, and self-employed labor, as summarized by Houston (1997).

Moseley (1983) proposed that labor hired by the government or households, and circulation and supervisory labor employed by capital, are not productive. Mohun (1996) agreed with Moseley on the latter but believed that government-hired labor that produces commodities is productive, creating value and surplus value. Shaikh and Tonak (1994), on the other hand, categorized social reproduction activities into production, distribution, maintenance of social order, and personal consumption, linking only the first category to productive labor, and the remaining three being associated with unproductive labor. Savran and Tonak (1999) further highlighted the importance of transportation and storage labor within the circulation sphere, considering them to be productive. They also take education, catering, art, and other activities hired by capital as productive. Rotta (2015, 2017) classified the production of knowledge and information as unproductive activities, with their expansion dependent on knowledge rents. In this framework, activities such as advertising, research and development, publishing, and movie production were considered unproductive. Tsoulfidis and Paitaridis (2019) also classified scientific and technical services as unproductive, but they categorized information and the arts as productive activities.

In the main analysis of this article, we adopt Savran and Tonak’s (1999) classification, which we believe is the most faithful to Marx’s treatment. It comprises three steps. The first step involves defining “activities of human beings” that apply to all modes of production. Human activities are categorized into “labor” and “non-labor”: “non-labor” consists of the activities of distributing products and incomes, as well as various types of consumption, while “labor” encompasses “productive labor in general” for production and “unproductive labor” for circulation and reproduction of social order. The second step is specific to the capitalist mode of production, where productive labor serves the need of capital valorization, with its main purpose being the production of surplus value in the form of a commodity. Consequently, productive labor under capitalism can be defined as labor that creates surplus value. The third step concentrates on “wage-labor.” It can be grouped into “wage-labor paid out of revenue” and “wage-labor employed by capital.” The former is classified as unproductive labor, while in the latter, only “wage-labor employed by capital in the field of production and transportation” is productive labor. When considering the government sector, “wage-labor” must also include “labor of state employees,” which consists of “labor for providing social services and reproducing social order” and “labor for state enterprises in production and transportation.” The former is unproductive labor, while the latter is productive labor.

Consequently, sectors are usually classified as productive or unproductive based on the dominant type of labor utilized in those sectors. However, this treatment is only an approximation because of the unavailability of more detailed data at the sector level. In reality, each productive sector has supervisory labor and circulation labor while the circulation sectors also perform some kind of production such as packaging, transportation, and storage. But the proportions of unproductive labor are supposedly small in the productive sectors and dominant in the circulation sectors, especially in the modern era when the division of labor has been highly developed. After all, most existing industrial classification systems group activities into sectors based on the functions performed.

Sectors in the national economic accounting system, such as agriculture, manufacturing, extractive industries, and transportation, are typically categorized as productive sectors. Although the transportation sector primarily facilitates the circulation of goods rather than their production, Marx argued that the transportation of goods represents a continuation of the production process within the circulation process. This change in the spatial attributes of goods effectively transforms transportation into a separate sector of production, warranting its classification as a productive sector and a specific field for the investment of productive capital.

Moreover, we also consider the education and health sectors to be productive, a practice also shared by Rotta and Kumar (2024). Marx (1963: 167) pointed out that these sectors contribute significantly to the development of human beings, which in turn enhances overall productivity and economic growth. For example, teachers’ and doctors’ services are directly related to the specialization and maintenance of labor power. Consequently, these services constitute part of the cost of reproducing labor power. While the work of doctors and teachers do not directly generate the funds used to remunerate them, it contributes to the reproduction of labor capacity and thus participates in the creation of value (Marx 1963: 167–68).

In contrast, Marx, throughout his various writings, explicitly pointed out that the fields involving commercial capital and finance capital belong to unproductive sectors. Additionally, various social services, private services, and other services are also categorized as unproductive sectors.

2.2. Unequal exchange

The term “unequal exchange” was coined by Emmanuel (1972) as a Marxian alternative to the then-popular structuralist explanation for the pervasive decline in the terms of trade for underdeveloped economies (see Ricci [2021] for a review of the structuralist approach to the phenomenon). Emmanuel argues that the institutionally determined (and thus exogenous) higher real wage rates in developed economies lead to higher prices for their exports relative to those of developing economies, resulting in deteriorating terms of trade for the latter. In other words, the value (in terms of labor) realized as the price of the exports of the underdeveloped countries is systematically less than the labor required to produce them, leading to value flowing from underdeveloped to developed countries. It is in this sense that there is unequal exchange. Emmanuel’s theory hinges on the assumptions of profit rate equalization due to perfect capital mobility and wage rate disparities due to labor immobility at the international level. This is the wage disparity mechanism of unequal exchange.

Several critiques of Emmanuel’s theory have emerged. Among them, Bettelheim (1972) and Evans (1976) questioned the treatment of wages as an independent variable in Emmanuel’s theory, while Amin (1976) questions Emmanuel’s lack of account of productivity differentials when treating differential wages. That is, the higher wages earned by workers in developed countries might be due to their higher productivity, which counters the unequal exchange argument.

A line of empirical research has developed employing Emmanuel’s (1972) concept of unequal exchange. For instance, Gibson’s (1980) examination of the United States and Peru revealed that 37.7 percent of labor embodied in the peripheral country’s exports was forfeited due to unequal exchange. Similarly, Nakajima and Izumi (1995) utilized input-output tables to gauge value transfers among the United States, Japan, and South Korea, noting waning inequality as the latter two countries experienced economic growth. Tsaliki et al. (2018) argued that Germany benefited from an absolute cost advantage over Greece, consistently transferring value from the latter. Such value transfers had a greater impact on Greece because of its smaller size of the economy.

The disparity of value and price of production arising from Emmanuel’s model based on the international equalization of the rate of profit also comes from the disparity in the organic composition of capital (OCC), which constitutes another mechanism of unequal exchange (Bauer 2000; Grossman 1992). The basic idea is that under the assumption of profit rate equalization, the price of production of goods produced with higher OCC is generally higher than the embodied value in them. The OCC in developed countries is generally higher than that of underdeveloped countries. Therefore, through international trade, value flows from underdeveloped countries to developed countries. This is the OCC mechanism of unequal exchange.

A competitive world market and the formation of a worldwide uniform rate of profit and prices of production appear to be unrealistic assumptions. However, now that exploitation is shown to exist even under competitive conditions (Cogliano et al. 2022), allowing for monopolistic pricing would only worsen North-South exploitation (Raffer 1987: 52). Veneziani and Yoshihara (2020) further trace the existence of exploitation under competitive conditions to the unequal distribution of social wealth. The persistence of unequal exchange thus has to do with the persistence of wealth inequalities, as well as other factors such as technical change and social norms (Cogliano et al. 2024).

The “monopoly capitalism” approach, led by Baran (1957), looked at unequal exchange from a noncompetitive perspective. He argues that, in the age of monopoly capitalism, oligopolistic firms in the West have the market power to set prices of their output above the competitive level while the exports of periphery countries are sold at competitive prices. In this way, Western countries can extract monopolistic rents through international trade. This is the monopoly mechanism of unequal exchange.

A series of studies also identify other factors that cause actual prices in international trade to deviate from competitive prices. For example, Foot and Webber (1983), Bryan (1995), Somel (2003), and Yoshihara and Kaneko (2016) contend that state intervention can heavily influence the pattern of economic surplus distribution and determine the outcome of unequal exchanges. Heintz (2006) found that the use of global subcontracting production modes disproportionately favors multinational corporations and consumers while leaving subcontractors and production workers without significant benefits. Finally, some scholars have explored the impact of exchange rates on international value transfer, highlighting their role in transferring value from underdeveloped to developed countries (Ricci 2021; Zhao 2021).

The literature reviewed above provides a significant foundation for understanding the transfer of value on an international scale. Notably, these works primarily address trade within productive sectors or at the total economy level, without distinguishing between productive and unproductive sectors. Considering the increasing significance of unproductive-sector trade in the current era of deindustrialization and financialization, it is the aim of this article to fill this gap in the studies of unequal exchange.

Therefore, a major innovation of this article is to distinguish between two mechanisms of unequal exchange—the productive-sector trade mechanism and the unproductive-sector trade mechanism, under competitive conditions. By putting unproductive-sector trade on the table, this approach offers a new perspective in understanding the persistent center-periphery structure of the world economy and the trade relationships among countries.

2.3. Unproductive-sector trade and international value transfer

Emmanuel’s (1972) research has provided insight into how international value transfer occurs in productive sectors. However, a gap remains in our understanding of international value transfer in unproductive sectors. These sectors do not create value but instead derive value from productive sectors.

In the case of commercial capital, which Marx (1991: 395) analyzed extensively, it does not produce surplus value but rather obtains part of the surplus value created by total productive capital in the form of average profits. Consequently, the pure circulation cost of commerce does not generate any value or surplus value and can only be compensated by the markup of commodity selling prices, which is in turn compensated by the surplus value of industrial capital.

The nature of wages in unproductive sectors, such as for commercial workers, is a deduction from the total surplus value of society, as their labor performs unproductive functions. Wages for commercial workers are determined by the cost of reproducing their labor power, while their labor aims to realize the value that has already been created and does not directly contribute to creating new surplus value. This leads to an increase in expenditure and capital advanced. At the same time, the business services sector can help to speed up the turnover of capital. Therefore, the impact of business sector development on overall profitability is uncertain.

When a country exports goods or services from unproductive sectors, it results in a transfer of value from other countries. This happens because these goods or services, despite lacking embodied value, realize value through their sale, regardless of the buyer.

3. A Model of International Value Transfers With Unproductive Sectors

The measurement of international value transfers should be calculated based on a universal value standard: international values. Theoretically, international values should be measured as per one physical unit of goods. However, since most input-output tables in the real world, including the ones we are using, are cast in monetary units, the unit of international values in this article shall be hours per unit currency of goods (Marelli 1983). For example, if the international value of products from the agricultural sector is $a$ hours/$, it means that the amount of agricultural sector products that is sold for $1 contains $a$ hours of value. Value calculations only involve productive sectors while the calculations of prices of production involve both productive and unproductive sectors since all sectors participate in the international equalization process of the rate of profit.

3.1. Trade flows

Suppose for a period, we observe the trade of intermediate goods or services (referred to as “goods” hereafter unless otherwise noted) between sectors, both within and across the borders of the $N$ national or district economies (hereafter referred to as “countries” as well) in the world economy. The trade flows are denominated in the same currency and recorded as matrix:

\begin{matrix} Q_{N m \times N m} = (\begin{matrix} Q^{11} & \dots & Q^{1 N} \\ ⋮ & ⋱ & ⋮ \\ Q^{N 1} & \dots & Q^{N N} \end{matrix}) \end{matrix}

(1)

where the generic block of this matrix $Q^{h s}$ is an $m \times m$ matrix whose generic element $Q_{j i}^{h s}$ means the amount of intermediate good $j$ produced in economy $h$ sold to sector $i$ in economy $s$ . Hereafter, unless otherwise noted, $i, j = 1, 2, \dots, m; h, s = 1, 2, \dots, N$ .

Let the row sums of $Q_{N m \times N m}$ be vector ${\bar{Q}}_{N m \times 1}$ whose generic element:

\begin{matrix} {\bar{Q}}_{j}^{h} = \sum_{s} \sum_{i} Q_{j i}^{h s} \end{matrix}

(2)

is the sum of good $j$ produced in economy $h$ and sold as intermediate goods.

Similarly, the sector-economy trade of final goods is recorded as matrix:

\begin{matrix} Ω_{N m \times N} = (\begin{matrix} Ω^{11} & \dots & Ω^{1 N} \\ ⋮ & ⋱ & ⋮ \\ Ω^{N 1} & \dots & Ω^{N N} \end{matrix}) \end{matrix}

(3)

where the generic block Ω ^hs is an $m \times 1$ vector whose generic element $Ω_{j}^{h s}$ means the amount of final good $j$ produced in economy $h$ sold to economy $s$ .

Let the row sums of $Ω_{N m \times N}$ be vector ${\bar{Ω}}_{N m \times 1}$ whose generic element:

\begin{matrix} {\bar{Ω}}_{j}^{h} = \sum_{s} Ω_{j}^{h s} \end{matrix}

(4)

is the sum of good $j$ produced in economy $h$ and sold as final goods.

Let gross output be vector:

\begin{matrix} χ_{N m \times 1} = (\begin{matrix} χ^{1} \\ ⋮ \\ χ^{N} \end{matrix}) \end{matrix}

(5)

where its subvector $χ^{h}$ means the output vector of economy $h$ , whose generic element $χ_{j}^{h}$ means the gross output of sector $j$ in economy $h$ .

In equilibrium:

\begin{matrix} \bar{Q} + \bar{Ω} = χ \end{matrix}

(6)

Regarding international trade, the export of good $j$ in economy $h$ is:

\begin{matrix} E_{j}^{h} = {\bar{Q}}_{j}^{h} - \sum_{i} Q_{j i}^{h h} + {\bar{Ω}}_{j}^{h} - Ω_{j}^{h h} \end{matrix}

(7)

while the import of good $j$ in economy $h$ is:

\begin{matrix} M_{j}^{h} = \sum_{s \neq h} \sum_{i} Q_{j i}^{s h} + \sum_{s \neq h} Ω_{j}^{s h} \end{matrix}

(8)

Thus, the net export of good $j$ in economy $h$ is:

\begin{matrix} {\tilde{E}}_{j}^{h} = E_{j}^{h} - M_{j}^{h} \end{matrix}

(9)

Finally, let the net export vector be:

\begin{matrix} {\tilde{E}}_{N m \times 1} = (\begin{matrix} {\tilde{E}}^{1} \\ ⋮ \\ {\tilde{E}}^{N} \end{matrix}) \end{matrix}

(10)

with its generic block ${\tilde{E}}^{h}$ having ${\tilde{E}}_{j}^{h}$ as the generic element.

3.2. Production technique

Now eliminate the country dimension to obtain the world-sector level trade matrix $X_{m \times m}$ whose generic element:

\begin{matrix} X_{i j} = \sum_{h = 1}^{N} \sum_{s = 1}^{N} Q_{i j}^{h s} \end{matrix}

(11)

Similarly, let the world-sector level gross output vector be $x_{m \times 1}$ , where:

\begin{matrix} x_{j} = \sum_{h = 1}^{N} χ_{j}^{h} \end{matrix}

(12)

Let $A_{m \times m}$ be the circulating capital input coefficient matrix with its generic element $A_{i j}$ meaning the amount of circulating capital good $i$ needed to produce a unit of good $j$ :

\begin{matrix} A_{i j} = \frac{X_{i j}}{x_{j}} \end{matrix}

(13)

Let the sector-economy use (not depreciation) matrix of fixed capital be $Θ_{N m \times N m}$ , and the direct labor input vector $L_{1 \times N m}$ that are required to produce gross output $χ$ . Similarly eliminating their country dimension leads to matrix $K_{m \times m}$ and vector $η_{1 \times m}$ . Let $F_{m \times m}$ be the fixed capital input coefficient matrix with its generic element $F_{i j}$ meaning the amount of fixed capital good $i$ needed to produce one unit of good $j$ :

\begin{matrix} F_{i j} = \frac{K_{i j}}{x_{j}} \end{matrix}

(14)

Let $D_{m \times m}$ be the depreciation coefficient matrix with its generic element $D_{i j}$ meaning the amount of fixed capital good $i$ depreciated for the production of one unit of good $j .$ Let $Φ_{m \times m}$ be the depreciation rate matrix such that $D_{i j} = F_{i j} \times Φ_{i j}$ . Then:

\begin{matrix} D = F \circ Φ \end{matrix}

(15)

where the operator “∘” means element-to-element Hadamard product.

Let vector $l_{1 \times m}$ be the direct labor input per unit of gross output:

\begin{matrix} l_{j} = \frac{η_{j}}{x_{j}} \end{matrix}

(16)

Then, we call the tuple ${F, A, D, l}$ a production technique. Note that it is defined on the sector level without the country dimension.

3.3. Productive and unproductive sectors

Let the first $n$ of the $m$ sectors be productive sectors while the rest unproductive sectors. Call sectors 1 through $n$ Department I while sectors $n + 1$ through $m$ Department II. Then the matrices and vectors defined above can be written in block form:

\begin{matrix} A = (\begin{matrix} A_{I} & A_{I I} \\ A_{I I I} & A_{I V} \end{matrix}), F = (\begin{matrix} F_{I} & F_{I I} \\ F_{I I I} & F_{I V} \end{matrix}), D = (\begin{matrix} D_{I} & D_{I I} \\ D_{I I I} & D_{I V} \end{matrix}), l = (l_{I}, l_{I I}), x = (\begin{matrix} x_{I} \\ x_{I I} \end{matrix}) \end{matrix}

(17)

Other matrices and sectors are partitioned in this way where appropriate.

3.4. Labor values

Let $λ_{1 \times m}$ be the labor value vector. Labor values of the productive department are determined according to:

\begin{matrix} λ_{I} = λ_{I} (A_{I} + D_{I}) + l_{I} \end{matrix}

(18)

Assuming $A_{I} + D_{I}$ is “productive,”¹ we have:

\begin{matrix} λ_{I} = l_{I} {(I - A_{I} - D_{I})}^{- 1} \end{matrix}

(19)

where, hereafter, $I$ is the identity matrix with proper dimensions. The unproductive sectors do not create labor values, so that:

\begin{matrix} λ_{I I} = 0 \end{matrix}

(20)

3.5. Prices of production

Let $p_{1 \times m}$ be the vector of prices of production, $b_{m \times 1}$ the consumption vector needed for the reproduction of one unit of labor power, $r$ the general rate of profit. Prices of production of all sectors are determined according to the internal rate of return method (Roemer 1979: 386):

\begin{matrix} - (p F + p A + p b l) + \sum_{t = 1}^{\infty} \frac{1}{{(1 + r)}^{t}} [p - (p D + p A + p b l)] = 0 \end{matrix}

(21)

where the first term on the left-hand side is the initial investment in period 0, while the second term is the sum of all future discounted profit streams.²

Equivalently, because $\sum_{t = 1}^{\infty} \frac{1}{{(1 + r)}^{t}} = \frac{1}{r}$ :

\begin{matrix} p = r (p F + p A + p b l) + (p D + p A + p b l) \end{matrix}

(22)

where the first term on the right represents average profits and the second term cost of production. Note that average profit is a markup over initial investment including fixed capital ( $p F$ ) and working capital ( $p A + p b l$ ). Rearranging equation (22) yields:

\begin{matrix} p = p [r F + D + (1 + r) (A + b l)] \end{matrix}

(23)

Let $M = r F + D + (1 + r) (A + b l)$ . With $F, D, A, l, b$ all being given, $M$ is then a function of $r$ , so that the price equation becomes:

\begin{matrix} p = p M (r) \end{matrix}

(24)

By further assuming matrix $D + A + b l$ is productive and $M$ indecomposable, it can be proved that there exists a unique positive solution ${p, r}$ to the above price equation system with $p$ unique up to multiplication of scalars.³ To obtain absolute prices of production, we use the normalization “total values equal total prices of production,” that is:

\begin{matrix} λ x = p x \end{matrix}

(25)

3.6. International value transfers

The prices of production represent the labor value realized in the sale of the goods, which could deviate from the labor value contained in the goods. That is to say, $p \neq λ$ in general. Therefore, there could be unequal exchange in terms of labor values. For example, when the price of production of a good is higher than its value, the seller of the good has trade gains in terms of labor values since the labor values realized in the sale is higher than the labor values embodied in the good, that is, the socially necessary time to produce it; and the buyer suffers a trade loss. When this trade happens within a country, the gains and losses of the sellers and the buyers cancel each other out domestically. However, if this happens internationally, the trade gains of one country are the losses of another country, and labor values are thus transferred from the buyer’s country to the seller’s country. Therefore, the net trade gains of country $h$ in terms of labor value are:

\begin{matrix} T^{h} = (p - λ) {\tilde{E}}^{h} \end{matrix}

(26)

which can be further decomposed into net trade gains from productive- and unproductive-sector trades respectively:

\begin{matrix} T_{I}^{h} = (p_{I} - λ_{I}) {\tilde{E}}_{I}^{h} \end{matrix}

(27)

\begin{matrix} T_{I I}^{h} = (p_{I I} - λ_{I I}) {\tilde{E}}_{I I}^{h} = p_{I I} {\tilde{E}}_{I I}^{h} \end{matrix}

(28)

because $λ_{I I} = 0$ .

4. Data and Estimation

The data in this paper mainly come from the World Input-Output Tables (WIOT) and the accompanying Socio-Economic Accounts (SEA) from 2000 to 2014 in the WIOD (Timmer et al. 2015). The WIOT contains a total of fifty-six sectors, which we reclassify into thirty-seven productive and nineteen unproductive sectors.

We take the following sectors as productive sectors: agriculture, mining and quarrying, manufacturing, construction, public utilities, logistics and transportation, postal activities and telecommunications, scientific research and development, education, human health, and some other sectors. Unproductive sectors include the following: wholesale and retail, financial service activities, real estate activities, legal and accounting activities, management consultancy activities, computer information services, administrative and support service activities, public administration and social security, and some other sectors.⁴ Since there is a lack of consensus in the literature regarding the classification of productive and unproductive sectors, we also perform a robustness check by using a different classification, as detailed in online appendix.

The main task of our estimation is to calculate the labor values of products or services from the productive sectors according to equation (19) and the prices of production of products or services from all sectors according to equation (23). The variables involving trade flows directly correspond to data in the WIOT. The estimation of the production technique and other variables, however, concerns several issues.

First, in the SEA, the labor time data of various sectors in China are missing and thus need to be imputed. We first obtain sector-level average annual wages from the China Labor Statistics Yearbook, and the sector-level total annual labor remuneration data in SEA. Based on these data, we estimate the number of workers in each sector in China. Then, considering that there are 52 working weeks and 11 public holidays per year in China, workers on average work 49.8 weeks per year. And then, we obtain the sector-level weekly labor hour data from the China Labor Statistics Yearbook. Finally, the sector-level number of hours worked is the product of the estimated number of workers and the average annual working hours.

In addition, because of lack of data on the complexity of labor at the worldwide sector level, we must make the strong assumption that all labor is homogeneous, although in theory, complex labor creates more value than simple labor within the same period of laboring time. To address this limitation, we perform a robustness check by allowing the complexity of labor across countries to be different while that within a country is assumed the same. This is done by using the country-level human capital index from the Penn World Table (version 10.0) (Feenstra et al. 2015). The results are reported in online appendix.

Moreover, the fixed capital matrix $F$ and the depreciation matrix $D$ are not directly available in the WIOD. We estimate them together in the tradition of Sraffa (1960) and Okishio and Nakatani (1975), using relevant information in the WIOD. The detailed estimation process is reported in online appendix.

Finally, we do not directly estimate worker’s consumption vector $b$ , but instead estimate the sector-by-sector consumption requirement matrix $b l$ , which is needed to calculate the prices of production in equation (23). By assuming all wages are spent, we first span total wages (scalar) of each sector in each country into a vector of wages spent on products from each of the $m$ sectors, using as weights the column “final consumption expenditure by households” recorded in the WIOT. This yields an $N m \times N m$ matrix. By summing up these sector-level consumption across countries, we arrive at an $m \times m$ consumption matrix. Further dividing each column of this matrix by the corresponding gross output of that sector, we arrive at $b l$ .

5. Analysis of Results

Our analysis of the results thus estimated from the above process is grounded through the presentation of two significant ratios pertaining to the trade balance and international value transfers of each country. This is represented through a two-dimensional coordinate system, as depicted in figure 1.

The horizontal axis represents the ratio of net export to gross output of a country, both measured in labor values, which is:

\begin{matrix} \frac{p {\tilde{E}}^{h}}{λ χ^{h}} \end{matrix}

(29)

for country $h$ with the notations introduced in section 3 (note that $p$ is price of production measured in labor hours). We measure exports and imports, and thus net exports, in terms of value (i.e., hours of labor) rather than monetary terms to provide an analysis that is focused on the labor exchanged between countries and reveal the underlying value flows and transfers. A positive (negative) ratio as defined above denotes a state of trade surplus (deficit) in terms of labor values.

The vertical axis represents the ratio of a country’s net value inflow to its gross output, both measured in labor values, which is:

\begin{matrix} \frac{T^{h}}{λ χ^{h}} \end{matrix}

(30)

for country $h$ . A positive (negative) ratio signifies that a country has inward (outward) labor value transfers through international trade in net terms. The utilization of ratios, rather than levels in this diagram, is to account for the differing sizes of economies.

The coordinate system is divided into four quadrants based on these ratios. Countries in the first and second quadrants experience a net value inflow, while countries in the third and fourth quadrants suffer a net value outflow. Countries in the first and fourth quadrants have a trade surplus, while countries in the second and third quadrants have a trade deficit, in terms of labor values.

In the subsequent analysis, we selected sixteen countries for the study. The selection prioritizes countries with large volumes of international trade as well as some countries that are traditionally labeled as peripheral countries. They include Germany (DEU), South Korea (KOR), Italy (ITA), China (CHN), Spain (ESP), the United States (USA), the United Kingdom (GBR), France (FRA), Japan (JPN), Australia (AUS), Canada (CAN), Brazil (BRA), Indonesia (IDN), India (IND), Mexico (MEX), and Turkey (TUR). The result of all the forty-three countries (or districts) in the WIOD are available on request.

By evaluating the coordinate locations of different countries, we can reveal their respective standings in international trade and international value distribution. Furthermore, this evaluation is carried out across time, thereby enabling us to understand the evolution of countries’ positions in international trade. To ensure brevity, we have included the coordinate charts of 2000, 2005, 2010, and 2014 in figure 2, while the two ratios in all years (2000–2014) are reported in tables 1 and 2.

Table 1.

The Ratio of Net Export (Hours) to Gross Output (Hours), Percentage.

	DEU	KOR	ITA	CHN	ESP	USA	GBR	FRA	JPN	AUS	CAN	BRA	IDN	IND	MEX	TUR
2000	3.1	3.3	1.0	0.8	−2.1	−3.0	−0.2	1.4	1.8	0.1	4.1	−0.4	3.0	−0.1	−0.1	1.2
2001	4.1	3.2	1.2	0.7	−1.7	−2.9	−0.5	1.4	1.4	0.0	4.0	−0.2	2.5	−0.2	−0.2	4.6
2002	6.2	3.0	1.0	0.9	−1.4	−3.4	−0.9	1.7	1.8	−1.1	3.4	1.2	1.9	−0.1	−0.1	3.5
2003	5.8	3.3	0.8	1.0	−1.5	−3.7	−0.6	1.4	2.1	−1.3	2.9	1.5	2.1	−0.2	0.0	2.2
2004	6.8	4.3	0.9	1.2	−2.2	−4.1	−0.8	1.1	2.4	−1.4	3.2	2.1	1.4	−0.6	−0.3	1.7
2005	7.0	3.6	0.7	2.0	−2.6	−4.4	−0.7	0.6	2.1	−1.2	2.7	2.1	1.5	−0.9	−0.2	1.2
2006	7.1	2.9	0.4	2.5	−2.8	−4.4	−0.5	0.4	2.3	−1.2	2.0	1.8	1.8	−0.6	0.0	0.9
2007	8.1	3.0	0.8	2.9	−2.8	−3.8	−0.6	0.0	2.6	−1.7	1.7	1.1	1.5	−0.7	−0.1	0.6
2008	7.8	3.6	0.7	2.7	−2.3	−3.6	−0.4	0.0	2.0	−0.6	1.2	0.3	0.5	−0.8	−0.5	1.0
2009	7.0	5.3	0.6	1.8	−0.7	−2.3	−0.7	−0.2	1.4	−1.1	−0.7	0.1	1.0	−1.0	0.0	2.3
2010	7.3	4.7	0.0	1.8	−0.6	−3.0	−1.4	−0.4	2.2	−0.3	−1.1	−0.4	0.8	−0.7	0.1	0.3
2011	7.0	4.6	0.3	1.6	−0.3	−3.1	−0.5	−0.8	1.0	−1.1	−0.8	−0.3	1.0	−0.6	−0.1	−0.9
2012	8.1	5.2	1.7	1.6	0.5	−3.0	−0.9	−0.5	0.3	−1.6	−1.2	−0.6	0.0	−0.6	0.1	0.6
2013	7.5	5.9	2.2	1.5	1.1	−2.8	−1.2	−0.5	0.0	−1.3	−1.1	−1.0	0.0	0.3	0.2	0.2
2014	8.1	5.7	2.6	1.8	0.6	−2.8	−1.3	−0.4	−0.2	−1.6	−0.6	−1.2	0.1	0.3	0.1	1.4
Average	6.7	4.1	1.0	1.7	−1.3	−3.4	−0.7	0.3	1.5	−1.0	1.3	0.4	1.3	−0.4	−0.1	1.4

Note: DEU = Germany; KOR = South Korea; ITA = Italy; CHN = China; ESP = Spain; USA = the United States; GBR = the United Kingdom; FRA = France; JPN = Japan; AUS = Australia; CAN = Canada; BRA = Brazil; IDN = Indonesia; IND = India; MEX = Mexico; TUR = Turkey.

Table 2.

The Ratio of Net Value Inflow to Gross Output (Hours), Percentage.

	DEU	KOR	ITA	CHN	ESP	USA	GBR	FRA	JPN	AUS	CAN	BRA	IDN	IND	MEX	TUR
2000	4.8	4.2	0.7	−0.3	0.0	2.5	4.1	2.6	4.8	−9.4	−5.0	−3.0	−4.6	−0.8	0.0	−4.1
2001	4.2	4.3	0.4	−0.3	−0.2	2.3	5.0	2.9	4.6	−8.7	−5.2	−4.7	−3.8	−0.8	0.8	−4.6
2002	4.2	4.2	0.4	−0.4	−0.4	2.4	5.2	2.6	4.7	−8.1	−4.6	−5.4	−3.0	−1.0	0.7	−3.1
2003	4.4	4.1	0.4	−0.5	−0.5	2.4	5.3	2.5	4.8	−5.6	−3.7	−5.6	−2.9	−0.7	0.1	−2.3
2004	4.7	4.3	0.5	−0.2	−0.4	2.5	5.7	2.4	5.1	−7.2	−3.7	−6.6	−3.0	−0.9	−0.1	−2.2
2005	4.6	3.7	0.5	−0.6	0.1	2.9	6.6	2.5	5.3	−6.0	−2.7	−5.7	−3.8	−0.6	−0.5	−2.5
2006	4.8	3.8	0.6	−0.6	0.0	2.9	7.3	2.3	5.6	−5.5	−2.4	−5.2	−3.4	−0.3	−0.5	−2.6
2007	4.7	3.6	0.1	−0.6	0.1	2.6	6.9	2.2	5.6	−4.0	−2.1	−4.9	−2.9	0.5	−0.2	−1.6
2008	4.5	4.7	0.2	0.1	0.2	2.2	7.0	1.9	5.7	−4.7	−2.7	−4.8	−3.2	0.6	0.1	−1.0
2009	3.6	3.3	−0.1	0.0	−0.1	1.9	8.3	1.7	4.0	−3.8	−1.3	−4.9	−2.3	0.5	−1.0	−2.5
2010	3.2	2.9	0.0	0.2	0.2	2.0	8.5	1.3	4.1	−3.6	−0.9	−4.3	−2.1	0.7	−0.9	−1.8
2011	2.9	3.6	0.3	0.4	0.6	2.1	8.6	1.5	4.2	−3.8	−1.1	−4.4	−2.1	0.9	−0.9	−1.8
2012	2.9	3.1	0.0	0.3	0.5	2.0	8.4	1.5	4.1	−3.3	−0.9	−4.7	−2.0	0.4	−0.8	−2.7
2013	2.6	3.3	−0.3	0.2	0.3	2.0	8.9	1.1	4.6	−3.4	−0.9	−4.8	−1.9	−0.1	−0.7	−3.3
2014	2.7	3.8	−0.2	0.2	0.2	2.1	8.0	1.5	4.9	−2.8	−1.6	−4.9	−1.9	0.2	−1.1	−3.8
Average	3.9	3.8	0.2	−0.1	0.0	2.3	6.9	2.0	4.8	−5.3	−2.6	−4.9	−2.9	−0.1	−0.3	−2.7

5.1. The first quadrant

Given the potential variability in the position of these countries within the coordinate system over time, our analysis starts with the latest data available in the database, namely, the year 2014. Countries situated in the first quadrant in 2014 encompass China, Germany, South Korea, Spain, and India, which realized a trade surplus as well as a net inflow of international value that year.

Germany and South Korea have notable similarities, such as consistently maintaining a trade surplus with a net value inflow since 2000. Displayed in table 1, the average annual trade surplus of Germany for the years between 2000 and 2014 accounted for 6.7 percent of its gross output in terms of labor values, while for South Korea the annual average was 4.1 percent. Additionally, both countries have experienced an upward trend in this ratio. This growth is attributed to Germany’s rapid increase in trade surplus from 2000 to 2007, and South Korea’s significant boost in trade surplus after 2008, as evidenced in table A1 in online appendix. Table 2 reflects that both countries have maintained a relatively high ratio of net value inflow to gross output in terms of labor values for a lengthy period, with an annual average of 3.9 percent for Germany and 3.8 percent for South Korea in the years between 2000 and 2014.⁵

The trade structures of China, Spain, and India have undergone changes over time, resulting in their shifts between quadrants on the coordinate system. Spain had near-zero net value transfers in 2000 and experienced a net value outflow in 2001–2004. After 2005, Spain shifted to a position with net value inflow. India became a net value inflow country in 2007, and China became a net value inflow country in 2008.

In addition, Spain and China briefly experienced net value outflow in 2009 and reversed their positions in 2010. India experienced net value outflow in 2013 and reversed to the position with net value inflow in 2014. China and India, as developing countries, have different reasons for the transition. China relies mainly on the rapid growth of net exports in the wholesale trade sector to realize net value inflow, while India relies mainly on net exports in the computer information services sector.⁶ China has maintained a trade surplus throughout this period, with the peak ratio of trade surplus to gross output in labor values being 2.9 percent in 2007. Despite a decline, China’s trade surplus ratio remained above 1.5 percent. Spain, after moving from having a trade deficit to having a trade surplus, had its trade surplus accounting for a relatively modest 0.6 percent of its gross output in labor values in 2014. The trade surplus ratio for India was 0.3 percent in 2014.

It is worth noting that our approach, which indicates that China has transitioned from a country with net value outflow to one with net value inflow, contrasts with existing literature on China. This transition was mainly due to its decreasing net outflow of value through the productive-sector trade channel and its increasing net inflow of value through the unproductive-sector trade channel, as evidence in figure 3. Both Ricci (2019), who does not differentiate between productive and unproductive sectors, and Su and Liang (2021), who consider only productive sectors, report that China has consistently been a country with net value outflow. This contrast reveals that differentiating between productive and unproductive sectors in analyzing the international transfer of value provides different, and perhaps more accurate, insights into countries like China’s changing position in the distribution of international values.

Among these five countries in the first quadrant in 2014, China and Germany share comparable characteristics in terms of trade through productive sectors. Notably, both have sustained significant trade surpluses in productive-sector trade, as shown in table 3. The yearly trade surplus averages for these two countries were 15.5 billion hours and 18.4 billion hours, respectively. Nevertheless, by examining their individual trade scenarios more closely, subtle differences can be discerned.

Table 3.

Import and Export of China and Germany, Billion Hours.

	Trade in Productive Sectors						Trade in Unproductive Sectors
	China			Germany			China			Germany
Year	EXP	IMP	NEX	EXP	IMP	NEX	EXP	IMP	NEX	EXP	IMP	NEX
2000	26.4	23.2	3.1	61.1	51.6	9.5	3.6	1.7	1.9	6.6	7.0	−0.4
2001	27.5	24.9	2.6	61.8	49.4	12.4	4.0	1.8	2.2	6.5	6.9	−0.4
2002	31.7	28.2	3.5	62.8	45.9	16.9	4.7	2.2	2.5	7.0	6.3	0.7
2003	39.5	35.1	4.4	68.5	51.3	17.3	4.5	2.3	2.2	7.3	6.8	0.6
2004	51.0	43.8	7.2	75.9	55.8	20.2	4.7	2.6	2.1	8.8	7.2	1.6
2005	63.0	48.7	14.3	78.2	57.8	20.4	5.3	3.0	2.3	8.9	7.4	1.5
2006	72.9	52.9	20.0	80.4	60.4	20.0	6.0	3.2	2.8	9.1	7.3	1.7
2007	79.2	54.3	24.9	85.2	62.5	22.8	6.9	3.7	3.2	9.2	7.4	1.8
2008	84.7	58.2	26.5	85.8	64.0	21.8	8.5	4.4	4.2	9.7	7.5	2.2
2009	73.1	55.1	18.0	68.3	51.2	17.0	8.7	4.3	4.4	9.8	7.6	2.1
2010	91.2	72.0	19.2	72.1	53.6	18.5	10.2	4.7	5.5	9.4	8.6	0.8
2011	95.5	78.9	16.6	74.8	56.3	18.6	11.4	5.0	6.4	9.1	8.9	0.3
2012	101.1	81.1	20.0	71.5	51.6	20.0	12.7	5.8	7.0	9.1	8.7	0.4
2013	106.4	83.8	22.6	72.7	53.0	19.7	11.7	6.5	5.1	9.5	10.0	−0.4
2014	109.5	80.4	29.1	73.1	52.0	21.1	12.1	7.1	5.0	9.8	10.2	−0.4
Average	70.2	54.7	15.5	72.8	54.4	18.4	7.7	3.9	3.8	8.7	7.8	0.8

Note: EXP = export, IMP = import, NEX = net export. The unit of trade surplus is translated from currency to labor hours by international price of production.

As shown in table 3, it is evident that China’s productive sector exports, except for the decline experienced in 2009 due to the global financial crisis, have experienced rapid growth over the years. Particularly after 2002, there has been a considerable increase in the export scale, reaching 109.5 billion hours in 2014, which is four times the figure recorded in 2000. Furthermore, there has been notable growth in the import scale of the productive sectors, albeit at a slower pace than that of exports.

As a result, there has been a continuous increase in China’s productive-sector trade surplus, from 3.1 billion hours in 2000 to 29.1 billion hours in 2014. According to figure 3, China’s net value outflow, through the productive sectors, reached a peak in 2007 at 8.9 billion hours and has continued to be a net value outflow country. This highlights that China was at an inferior position of global value distribution after its accession to the WTO, despite the rapid growth of its trade surplus during that period.

Germany has also consistently maintained a significant trade surplus in its productive-sector trade. In the year 2000, this trade surplus amounted to 9.5 billion hours and grew to 22.8 billion hours by 2007. However, the global financial crisis of 2008 dealt a significant blow to it, and by 2014, Germany had yet to fully recover to its pre-crisis level. Notably, unlike China, the majority of Germany’s net inflow of value stems from trade in the productive sector, as evidenced by figure 4.

Although China and Germany have both maintained significant and increasing trade surpluses within their respective productive sectors, they have exhibited distinct patterns in terms of value transfer. For instance, in 2014, China’s trade surplus within the productive sector was roughly 1.4 times greater than Germany’s; however, China experienced a net value outflow of 0.9 billion hours, while Germany experienced a net value inflow of 7.1 billion hours (as calculated from table 3, figure 3, and figure 4). While China saw a trade surplus, its trade gains were at a lower level. Upon investigation of this phenomenon, it appears that the value transfers achieved through trade within productive sectors is mainly determined by the deviation between the international price of production and international value, which is in turn influenced by sectoral heterogeneity (as indicated in figures 3 and 4). Therefore, it is apparent that the trade structure of a given country plays a pivotal role in the extent of the transferred international value. While China is a large trading country, it is not yet a strong trading power.

5.2. The second quadrant

In 2014, the United States, the United Kingdom, France, and Japan were classified as countries within the second quadrant. Both the United States and the United Kingdom have maintained a persistent trade deficit, with net inflow of value, as evidenced by tables 1 and 2. The US trade deficit represented a relatively significant portion of its gross output in labor values, peaking at 4.4 percent in 2006 before declining to 2.8 percent in 2014, with an annual average of 3.4 percent. In comparison, the ratio of net value inflow to gross output in labor values in the United States was relatively low, with an annual average of 2.3 percent from 2000 to 2014. The United Kingdom’s trade deficit ratio averages at 0.7 percent, significantly lower than that of the United States. However, its annual average of net value inflow shows an upward trend year after year, with a remarkable 8.9 percent in 2013. It is noteworthy to mention that both countries experienced a decline in value transfers contributed by the productive-sector trade, as unproductive sectors took over as the main channel for value transfers, as demonstrated in figures 5 and 6. Although the productive-sector trade initially entailed a higher value inflow in both the United Kingdom and the United States, the level of this transfer has shown a rapid decline since 2006, prompting a structural change in their international value transfers after 2010.

For the case of the United States, the productive sector has continuously experienced a trade deficit, with a decrease in both import and export values throughout the inspection period from 2000 to 2014; imports fell faster, which ultimately resulted in a reduced deficit from 47.7 billion hours to 35.3 billion hours. Conversely, the US trade surplus in the unproductive sector persisted over the years, with exports remaining above 20 billion hours and imports around 15 billion hours. The size of the surplus fluctuated, dropping to 5.9 billion hours in 2003 before rising to 9.6 billion hours in 2014. As a result, the United States’ overall trade deficit showed a decreasing trend throughout this period, from 39.9 billion hours to 25.7 billion hours. Regarding value transfers, as figure 5 shows, the United States experienced net international value inflow in both productive- and unproductive-sector trades, although the trend was opposite for each. While the net inflow of international value in the productive sector showed a downward trend, dropping from 24.9 billion hours in 2000 to 9.1 billion hours in 2014, the unproductive-sector trade exhibited an upward trend, rising from 7.9 billion hours in 2000 to 9.6 billion hours in 2014. The shift in the pattern of international value transfers in both types of sectors indicates the increasing importance of unproductive-sector trade for the United States, with the net inflow of international value in the unproductive sector surpassing that of the productive sector in recent years.⁷

The above finding regarding the growing prominence of the unproductive sector in the US economy is consistent with the findings by Rotta (2015, 2017), who analyzed productive and unproductive accumulation in the US economy from 1947 to 2011. Rotta’s research revealed that unproductive accumulation expanded more rapidly than productive accumulation over this period. Specifically, the accumulation pattern that characterized the 1947–1979 phase, which prioritized productive accumulation, shifted after the 1980s, giving way to a model that emphasized unproductive accumulation.

Considering the United Kingdom, it is observed that the trade deficit within the country’s productive sector has experienced a gradual increase over time, expanding from 4.4 billion hours in 2000 to 10.5 billion hours in 2014. Conversely, there has been a notable surge in the trade surplus of the United Kingdom’s unproductive sectors, as the surplus rose from 4.0 billion hours in 2000 to 8.3 billion hours in 2014. Regarding value transfers in the United Kingdom, which is comparable to the circumstances in the United States, value transfers through the productive sector and unproductive sector channels have also exhibited a reversed trend, evidenced in figure 6. Specifically, in 2000, the net value inflow in the unproductive sector of the United Kingdom was equivalent to 74.5 percent of the net inflow value of trade in the productive sector, and this ratio has continued to increase to reach 104.8 percent in 2010 and 148.2 percent in 2014.⁸

France and Japan also have the capacity to achieve net value transfers, albeit with distinct characteristics that differentiate them from the United States and the United Kingdom. As displayed in table 1, both countries have undergone a shift from trade surplus to trade deficit, with France’s trade surplus ratio dropping from 1.4 percent in 2000 and transforming into a trade deficit by 2008. Japan’s trade surplus, on the other hand, has consistently decreased year after year since 2008, eventually resulting in a deficit by 2013. Nevertheless, it is worth noting that Japan’s net value inflow relative to gross output in labor values has not dwindled, with an average of 4.8 percent annually, as table 2 shows. This can be attributed to Japan maintaining a significant trade surplus in the productive sector earlier on, which has since declined and turned into a deficit, though. Additionally, Japan’s net value inflow scale remains relatively high because of the importation of commodities whose international prices of production are lower than their international values, thus allowing for net value inflows despite the trade deficit (evidence available on request).

5.3. The third and fourth quadrants

In 2014, Australia, Canada, and Brazil were identified as the countries located in the third quadrant. These countries share similar characteristics as they have consistently experienced net value outflows. Throughout the inspection period, Australia and Canada have transitioned from the fourth quadrant to the third quadrant. Brazil, with slight variations, was in the third quadrant in 2000–2001, moved to the fourth quadrant in 2002, and back to the third quadrant again in 2010. Notably, as seen in tables 1 and 2, Australia records an average ratio of net value outflow to gross output in labor values of 5.3 percent annually, while the ratios for Canada and Brazil were 2.6 percent and 4.9 percent.

Italy, Mexico, Indonesia, and Turkey were in the fourth quadrant in 2014. Italy continued to run a trade surplus, but value transfers had progressively worsened, with a gradual shift from a net value inflow position to a net value outflow position. In 2000, Italy had a trade surplus of 2.3 billion hours, with a net value inflow of 1.6 billion hours. In 2014, Italy’s surplus widened to 4.3 billion hours, but with a net value outflow of 0.3 billion hours. Mexico was by and large in balance both in terms of trade and value transfers and recorded an average ratio of trade deficit to gross output in labor values of 0.1 percent annually, and that of net value outflow to gross output in labor values of 0.3 percent. Indonesia and Turkey have maintained a persistent trade surplus, with net outflows of value, which demonstrates their disadvantaged position in international trade. In the context of the continued net value outflow, the trade surplus of the two countries has also gradually declined.

Given the contentious nature of classifying productive and unproductive labor and sectors, we have performed a robustness check by modifying our classification according to a reviewer’s comments. The results, available in online appendix, are similar to the main results reported above.

We have also addressed the issue of assuming homogeneous labor across sectors and countries by using the country-level human capital index to adjust for labor complexity across countries. The results, reported in online appendix, are also similar to the main results.

6. Conclusion

This article explores a unique mechanism of international labor value transfers through unproductive-sector trade, providing significant insights into global trade dynamics. By developing a model that incorporates unproductive sectors and analyzing data from the WIOD (2000–2014), we uncover new patterns in value transfers among 16 countries. Unlike existing literature, which typically overlooks the distinction between productive and unproductive sector channels, our findings highlight critical shifts in global value transfers. While prior studies (e.g., Ricci 2019; Su and Liang 2021) have identified advanced economies like the United States, the United Kingdom, France, Germany, Japan, and South Korea as net value inflow countries, we show that unproductive sectors have become an increasingly important channel for capturing international values, especially for the United States and the United Kingdom. Rotta and Kumar (2024) rightly observed the relocation of productive activities from advanced economies to China, while unproductive activities are rising in countries whose weights are falling in the global economy, like the United States, Western Europe, and Japan. Regarding China, which has often been characterized as a persistent net value outflow country, we nonetheless demonstrate that this was true only before the global financial crisis. Since then, China has shifted to a net value inflow country, largely because of growth in its unproductive wholesale trade sector. These findings call for a more nuanced understanding of China’s evolving role in the global economy.

This study also contributes to the unequal exchange theory by broadening its scope beyond trade in productive sectors. Our results suggest that the traditional focus may overlook key dynamics in the modern global economy, especially as deindustrialization and financialization have reshaped developed countries, reducing the share of productive sectors and amplifying the role of unproductive sectors in international trade. Our analysis also underscores the need to reassess trade characteristics in light of post-2008 global stagnation and the disruptions caused by the COVID-19 pandemic, as well as rising trade conflicts, such as the US-China trade war.

In conclusion, this study offers a fresh perspective on trade gains through labor value transfers, emphasizing the critical role of unproductive-sector trade. By incorporating unproductive sectors into the analysis, we provide a more comprehensive understanding of contemporary trade dynamics. Future research should continue to explore these patterns and their implications for global economic policies and the equitable distribution of trade gains.

However, there are some limitations to this study. First, we assume a competitive world market in all sectors, but factors like monopoly and unfair competition, especially in the North-South context, may skew observed inequalities. This assumption is relaxed as part of planned research. Second, our assumption that all labor in productive sectors is productive is theoretically flawed, as it ignores supervisory labor, which is unproductive. This limitation, based on sector-level data availability, is addressed with more granular data in planned studies. Finally, the assumption of homogeneous labor across sectors and countries is problematic, as labor is generally heterogeneous. While we adjusted for labor complexity using the human capital index as a robustness check, this issue persists and is addressed in planned work with improved data.

Supplemental Material

sj-docx-1-rrp-10.1177_04866134251315864 – Supplemental material for International Labor Value Transfers Through Unproductive-Sector Trade

Supplemental material, sj-docx-1-rrp-10.1177_04866134251315864 for International Labor Value Transfers Through Unproductive-Sector Trade by Xiaonan Qiao, Xin Li and Junshang Liang in Review of Radical Political Economics

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors received financial support by the National Social Science Foundation of China (grant numbers: 22&ZD055; 20BJL046) and the Liberal Arts Development Fund of Nankai University (grant number: ZB22BZ0210).

ORCID iD

Junshang Liang

Supplemental Material

Supplemental material for this article is available online.

1

See : 22) for a definition of productiveness of a matrix.

2

As pointed out by a reviewer, initial investment of circulating capital might not be equal to its flow in one round of production. The accurate estimation of it, however, requires information of the rates of turnover at the sector level, which is not available in the data we are to use or elsewhere. Therefore, we leave it for future improvement once the said data are available.

3

The crux of the poof lies in proving that there exists a positive $r$ such that $M (r)$ can have unity as the dominant eigenvalue. When $r = 0$ , the productiveness of $D + A + b l$ ensures that the dominant eigenvalue of $M$ is less than 1. When $r > 0$ , because $M$ is increasing in $r,$ and the dominant eigenvalue of $M$ is increasing in $M$ by the Perron-Frobenius theorem, we can always find a sufficiently large $r$ such that the dominant eigenvalue of $M$ exceeds unity. Then, by continuity and increasingness, there exists a uniquely positive $r$ such that $M (r)$ has unity as the dominant eigenvalue. By the Perron-Frobenius theorem, the eigenvector $p$ is positive (because of indecomposability) and unique up to multiplication of scalars. A detailed proof is available on request.

4

By the WIOD sector code, the productive sectors include A01, A02, A03, B, C10–C12, C13–C15, C16, C17, C18, C19, C20, C21, C22, C23, C24, C25, C26, C27, C28, C29, C30, C31_C32, C33, D35, E36, E37–E39, F, H49, H50, H51, H52, H53, I, J61, M72, P85, Q. Unproductive sectors include G45, G46, G47, J58, J59_J60, J62_J63, K64, K65, K66, L68, M69_M70, M71, M73, M74_M75, N, O84, R_S, T, U.

5

For the level data used to construct the value transfer ratio, see .

6

If the computer information services sector is classified as productive sector, conclusion about India would change. See for details.

7

The trade data discussed here are available on request.

8

The trade data discussed here are available on request.

Author Biographies

Xiaonan Qiao is Professor at the School of Economics, Nankai University, China. His research interests include Marxian economics and its mathematical methods, modern capitalism, and China’s economy.

Xin Li is a PhD student at the School of Economics, Nankai University, China, specializing in political economy.

Junshang Liang is Assistant Professor at the School of Economics, Nankai University, China. His research focuses on the application of quantitative methods in the study of Marxian political economy.

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