1. Introduction
The recent years witness the progress of incorporating corporate finance considerations into the study of international trade. Before that, trade theory was mainly interpreted the base of trade from the perspectives of factor endowment differences, transnational differences in productivity and economies of scale. The new new trade theory dives deep into the firms’ export behavior from macro scope and industrial level to firms heterogeneity, which lays a preliminary foundation for the study of the combination of corporate finance and firms’ export. As the external financial market is incomplete, the financing of enterprises will always be subject to various constraints. Considering that export enterprises have a greater demand for capital than those selling in domestic market, it is inevitable that when the financing of enterprises is restricted, it will affect the export volume [
1,
2,
3].
Last few years, one of the fundamental changes in international trade is the rise of global value chains (GVCs), and the increasingly fragmentation of production. The enterprise only participates in one or several production ties of manufacturing. Through this process, the value of products exported also includes the value of intermediate imported from abroad, and the value created by the enterprise itself only accounts for a small part. Therefore, the measurement of a country’s trade interests and division of labor status should shift from export volume to domestic value-added (DVAR). The WIOD (world input-output database) project launched the input and output data of countries and sectors in 2012. In this way, it is possible to calculate the added value trade. Thus,.the research on global value chain has emerged including some representative studies e.g., [
4,
5,
6].
Although the calculation of domestic value added is an ascendant research. Existing research on how financial conditions effect value-added trade is quite limited. Especially at the micro-firm level, the research on how a firm’s financial constraint affects its DVAR is still not enough. Following this direction, this paper attempts to push forward the previous research on the combination of corporate finance and international trade to explore the relationship between financial constraints and an enterprise’s value-added trade. So, this study consists of two kinds of literatures, one is the literatures on corporate finance and international trade. And the other is the literatures on GVCs (Global Value Chain) accounting. The following part summarizes these two literatures respectively.
The theoretical contribution of incorporating corporate finance to the study of international trade was mainly made by Chaney [
7] and Manova [
1], who introduce financial friction into Melitz [
8] heterogeneous firms model. Through equilibrium analysis, it is concluded that the existence of financial friction will affect the export of enterprises, but they depict financial friction in different ways. Chaney [
7] mainly demonstrates from the perspective of internal liquidity, namely cash flow, while Manova [
1] mainly focuses on the perspective of external financing constraints. Based on the above theoretical research, scholars use national data to carry out empirical tests. Greenaway [
9] used the data of British manufacturing enterprises, Muuls [
10] used the data of Belgian enterprises, and Minetti and Zhu [
2] studied Italian enterprises. They all find that enterprises subject to financing constraints were less likely to export, hence their exports decreased. With the increasing importance of China in the global export market, some scholars began to pay attention to the study of export and financing constraints of Chinese enterprises. Manova et al. [
11] apply Chinese firm-level data and find that foreign-funded enterprises have better export performance due to less financing constraints. Feenstra et al. [
12] conclude three main reasons why export enterprises are more vulnerable to financing constraints through constructing theoretical models. They used the database of China’s industrial enterprises to confirm the conclusions of theoretical research. Based on further study in China, Manova and Yu [
3] find that the capability of financing would also affect the choice of trade mode for enterprises. Generally speaking, enterprises with weaker financing capacity tend to integrate into GVCS by means of processing trade, which generates much lower profits and domestic added value than general trade. Although this study touches the issues of trade patterns and value chains, it does not account for the value added related to GVCS. Therefore, it is undoubted that this paper is a further step forward on the basis of their research.
Recently, the study on the calculations of value added in global value chain goes from macro perspective into micro-enterprise perspective. In terms of methods, it extends from the domestic input-output table to the transnational input-output table. For the specific case of China, recent studies have computed the value added of processing trade and general trade, respectively. Hummels et al. [
13] propose the use of vertical specialization to measure the foreign components of exports. Based on a country’s input-output table, exports can be divided into domestic value added and foreign value added. However, Hummels et al. [
13] ’s method doesn’t distinguish processing trade, which could account for half of China’s foreign trade exports. Imports under processing trade are used exclusively for the production of exports, companies could only earn modest processing fees. The value added in processing trade is quite limited. If the real value added in processing trade is considered to calculate China’s trade surplus with the United States, this surplus would be reduced by 40% [
1]. Given these shortcomings, Koopman et al. [
4] revise the accounting method of Hummels et al. [
13] to distinguish processing trade from non-processing trade and recalculate them using the input-output table, finding that the previously calculated vertical specialization rate was underestimated.
Although the input-output table can reflect the division of labour between countries and industries, it can only be used to calculate domestic value added in national or industry levels. The heterogeneity of enterprises would be ignored. Since in the same industry, firms could have quite different sizes and competing abilities, the calculation results would be biased. Upward et al. [
14] is the first to calculate the domestic value added at the firm level, they use the databases of China’s Customs Import and Export Trade and of China’s Industrial Enterprises, divide processing trade and general trade respectively, and find that the domestic value added of processing trade is much lower. Kee and Tang [
5] also usemicro-data to calculate the domestic value-added rate (DVAR) at the enterprise level and analyse the reasons for the increase in China’s domestic value added in recent years, which has also shown that the DVAR of processing trade is much lower than that of general trade. Hence, whether value added at the industry level is calculated using a non-competitive input-output table [
15,
16] or micro-enterprise data [
5,
14], the results all show that the value added in processing trade is much lower than that in general trade.
This paper mainly studies the impact of financing constraints on firms’ domestic value added trade, and further investigates how the easing of financing constraints promotes the Chinese enterprises’ position in global value chain and what kind of mechanism to accomplish it. This paper push forward the previous literatures on the study of combination corporate finance and international trade theory. That is to say, we push the previous research on the effect of financial constraints on firms’ export volume, to the research of the firms’ domestic added value. The accounting of DVAR, especially the accounting of DVAR at the firm level, is recently ascending.
This paper used a large micro firm-level production data compiled by China’s National Bureau of Statistics, with import and export trade data collected by China’s General Administration of Customs. Chinese industrial enterprises data covers more than 95% of China’s total output in the manufacturing sectors. This is the most comprehensive and internationally recognized micro-database for the study of China’s economy. The China Customs Import and Export Database, which records all import and export transactions of Chinese enterprises is widely used by Chen et al. [
17] and so on. We devote a great amount of time in merging of these two micro-databases. By using the samples provided by these two databases for empirical research, our conclusions could more truly and accurately reflect China’s economic reality. Secondly, this paper constructs the financing constraint indexes comprehensively. We use three kinds of different indexes to measure the financing constraint of enterprises. The multiple scoring method selects seven financial indicators, such as liquidity and liquidity ratio, and constructs them through scoring ranking. The SA index excludes all financial indicators that influence each other and only uses exogenous variables such as enterprise size and age to construct the index. The index of interest expenditure fully considered the “Chinese characteristics” of indirect financing of Chinese enterprises.
In addition, different from the previous methods of calculating the domestic added value at the national or industrial level, this paper endeavors to calculate the domestic added value from the firm level. The empirical study found that the easing of financing constraints significantly increased the domestic added value of Chinese enterprises, and played a more significant role in China’s private enterprises. We also analyses the two mechanisms by which relaxing financial constraints could promote global value chain upgrading: one is directly transfer enterprises’ trade mode from processing trade to general trade, the other is allowing enterprises to climb up in the global value chain. Generally speaking, this paper is of great value for understanding how the current global value chain distribute and what elements lead to this phenomenon, for understanding the mechanism and channels of upgrading enterprises’ position in the global value chain, especially understanding and explaining the emerging global value chain phenomenon from a financial perspective.
The rest of this paper is structured as follows. The second section provides a theoretical analysis of the mechanism by which financial constraints could affect trade mode selection and value chain upgrading. The third section calculates domestic value added at the enterprise level and introduces the data and variables. The fourth section uses the micro-level enterprise data to conduct empirical tests and presents the robustness test and analysis of possible mechanisms. The last section concludes.
2. Theoretical Analysis
According to new trade theory that considers firms to be heterogeneous, financial constraints are an important factor affecting the exports of enterprises [
1,
7]. Export firms face higher entry costs than those in the domestic market. Long-term fixed costs such as those incurred in establishing distribution networks abroad and paying for advertising and marketing need to be paid in advance before companies can enter international markets. Further, compared with sales in the domestic market, transportation to other countries takes longer and is more capital-intensive, which requires higher liquidity. Therefore, regardless of the financial constraints of enterprises, whether the fixed costs and variable costs of international trade can be paid affects not only whether enterprises can export, but also the volume of trade exported.
Moreover, scholars have explained the relationship between financial constraints and enterprise exports from various perspectives. Manova and Yu [
3] find in their research of China that the strength of enterprises’ financing ability also affects their choice of trade mode. Compared with general trade, processing trade requires less capital. Therefore, those enterprises with weaker financing capacity tend to integrate into the GVC by choosing the processing trade mode. Processing trade generates lower firms’ profits and domestic value added than general trade, which makes China locked into the lower end of the GVC for a long time. Therefore, the financial constraints of enterprises should first be eased to upgrade China’s position in the GVC to transform enterprises’ low value-added trade (e.g., processing trade).
The OECD’s [
18] research shows two mechanisms through which reducing financial constraints could upgrade Chinese enterprises’ position in the GVC. First, from the perspective of trade mode, easing the financial constraints of enterprises could promote their transformation from processing trade to general trade, which can create more domestic value added but, at the same time, requires more capital investment. Second, from the perspective of the value chain position of enterprises, the enhancement of financing ability could transform Chinese enterprises from simple assemblers to suppliers of parts and capital goods (i.e., from processing and assembly at the bottom of the value chain to intermediate manufacturers in the middle and upper positions).
First, general trade involves more domestic production links and more domestic value added in export products. The raw materials, materials, and parts required for processing trade production all come from abroad, and only simple assembly or welding and other processing procedures are carried out in China. In processing trade, the domestic process and raw materials required for product production are less, which leads processing trade to have low domestic value added. In terms of capital demand, enterprises need to pay in advance for product design, raw materials, import tariffs, and product sales in general trade, meaning that they need more adequate capital in advance than under processing trade.
Processing trade is divided into two modes: processing with pure assemble and processing with imports. Pure assemble means that the raw materials are provided by foreign enterprises. Domestic enterprises do not need to pay for imports; rather, they only need to assemble based on the requirements of foreign enterprises, which then send the finished products. In this mode, domestic processing companies do not need to pay for raw materials or bear the risk of selling the finished products. Therefore, processing trade involves low cost, low risk, and low capital demand. In processing with imports, domestic enterprises pay for imported parts and then assemble and process them before exporting. In this mode, although domestic enterprises need to pay the import cost of raw materials in advance, the parts and raw materials they import are duty-free because of the favourable tax rebate policies provided by the Chinese government on processing trade. Moreover, the amount of capital they need to pay in advance is less than that under general trade. Hence, enterprises engaged in general trade need more investment than those engaged in processing trade. Therefore, firms that are financially constrained will be more inclined to engage in processing trade and only switch to general trade once their financial constraints ease because general trade has a higher profit margin and its DVAR is also significantly higher than that of processing trade [
4,
16].
The second mechanism is reducing financial constraints to promote the upgrading of the value chain. Ju and Yu [
19] show that those enterprises in the upstream value chain have stronger production capacity and profitability as well as higher domestic value added. At the same time, the capital intensity of enterprises is also higher. Chen [
20] also shows that most enterprises in the lower value chain position in China are engaged in processing trade such as assembly. Therefore, if enterprises could rise to the upstream value chain and produce more intermediate goods, it would be possible to upgrade the value chain. Compared with downstream assembly, if enterprises want to climb upstream and produce intermediate goods, they need to buy more machinery and equipment to organize production, and accordingly demand for capital increases. Therefore, easing financial constraints could also prompt a shift from downstream assembly to upstream parts producers.
Following Antràs et al. [
21], we construct the so-called ‘upstream index’ to measure the positions of enterprises in the value chain. This index represents the distance between the production links of enterprises and final consumption. Specifically, we construct the upstream index in the following way. First, the upstream index of the industry is constructed. According to Leontief’s input-output table, in a closed economy, the total output of an industry is equal to the consumption of the final product of the industry and the intermediate products produced by other industries, which can be written as follows:
where
q = 1, 2, 3……N represents the national economy,
Y represents the final output of the industry,
F represents the final product of the industry, and
represents the consumption of intermediate products in the
industry by producing a unit of
industry products.
On this basis, Antràs et al. [
21] propose a method of calculating the average distance (upstream) between the output and final consumption of an industry in the value chain. They multiply consumption in each stage in Equation (1) by the distance between it and final consumption, and then sum the output consumption of this stage as the weight:
where
represents the average distance between the industry and final consumption;
≥ 1, and only if the industry’s output is all final consumption,
= 1. If
is larger, the output of the industry is mainly intermediate goods, far from final consumption; if
is smaller, the industry’s output is closer to the final consumer:
Considering the imports and exports in open economies and taking inventory into account, is updated as shown in Equation (3). Substituting Equation (3) into (2), the upstream degree of the domestic industry in an open economy can be obtained.
At the firm level, Chor et al. [
22] and Ju and Yu [
19] measure the upstream index of enterprises’ integration into the GVC through exports to reflect the position of an enterprise in the GVC. Specifically, the upstream index of each enterprise is obtained by mapping the upstream degree of the industry to a single enterprise with the exports of each enterprise’s sub-industry as the weight to measure the embedded position of the enterprise in the GVC. Since the industries in the World Input-Output Databaseare classified according to the ISIC 4.0 standard, whereas imported and exported products in the Chinese customs database are classified according to the HS8 standard code, this study match the two schemes according to the HS Combined to ISIC rev3 schemes provided by WITS (World Integrated Trade Solution) and the ISIC rev3–ISIC rev3.1/ISIC rev3.1–ISIC rev4 schemes provided by the United Nations Statistics Division. After the industry matching is completed, the upstream degree of the enterprise can be expressed as the weighted average upstream degree of the export products of different industries:
where
represents the upstream index of enterprise
i embedded in the GVC through exports in year
t,
represents the total exports of enterprise
i in year
t, and
represents the import volume of enterprise
i in the
jth industry in year
t.
represents the upstream index of the
jth industry in year
t. This indicator allows us to verify whether reducing financial constraints promotes enterprises into an upstream position of the value chain.
6. Conclusions
Our research shows that financial constraint is the key element in the upgrading of Chinese enterprises’ global value chain position. This study adopts Chinese Industrial Enterprises Database and China Customs Import and Export Database to calculate the DVAR at the micro-enterprise level, while taking the heterogeneity of enterprises into full consideration and distinguishing processing trade enterprises from general trade enterprises. In terms of constructing the variables for financial constraints, we adopt three methods (comprehensive scoring method, SA index method and single financial indicator method) to measure firm’s financial constraints.
The study find that reducing financial constraints can significantly promote the position of Chinese enterprises in the GVC. Since Chinese banks show ‘ownership discrimination’ hence state-owned enterprises have priority in gaining loans from banks, while private-owned enterprises usually suffer from severe financing difficulties and high financing costs. We choose to divide our samples into state-owned enterprises (SOE), private-owned enterprises (POE) and foreign-owned enterprises (FOE) in order to study the effect of ownership. Our results show that financial constraints have no effect on SOEs, but it’s a crucial factor that restricts the upgrading of POEs’ positions in the global value chain.
We also investigate the channels through which financial constraints affect the GVC upgrading of Chinese enterprises. We find that an increase in financing capacity can shift enterprises from processing trade to general trade, which demands more capital. It also helps enterprises shift from simple processing and assembly to intermediate product production, which again requires more capital to purchase the necessary machinery and equipment. The transformation from processing trade to general trade and from processing and assembly to intermediate goods production improves both the profit and the DVAR of enterprises, thus promoting China’s position in the GVC.
Well, we mainly study financial constraints from the static perspective rather than dynamic M&A. As Kopecky et al. [
29] shows, in short term, enterprises could optimize their firm values through modifying debt structure if there is no takeover market. However, when we consider dynamic firm takeover, the modification of debt structure only has minor effect on firm value. Similarly, if we consider M&A, firm with less financial constraints could acquire those firms with severe financial constraints. In this case, the financial constraint problem could also be solved. However, whether this long-term, dynamic solution works the same way and has the same effect on firms DVAR as the debt structure adjustment, is a topic worth studying by future researches.
In view of the conclusions of this study, we have the following policy implications: firstly, Government should realize that if they want to upgrade domestic enterprises’ positions in the global value chain when opening up, they would have to improve domestic level of financial development and mitigate domestic firms’ financial constraints. For developing countries, it is particularly necessary to encourage the development of private financial institutions, introduce foreign financial institutions, promote competition in financial markets, and break the monopoly of funds by state-owned commercial banks. Limited financial resources can only be allocated to the most efficient enterprises through competition among various financial institutions. Second, China’s financial institutions and the Chinese government should fundamentally reverse the credit discrimination against private enterprises and avoid the continuous flow of capital to the “zombie enterprises”, but to the most efficient enterprises. Only in this way can we alleviate the financing constraints of enterprises, especially the financing constraints of private enterprises, and provide financial support for Chinese enterprises to push their way up the global value chain.