Export creation of the Belt and Road Initiative: “Give-them-a-fish” or “Teach-them-to-fish”?

1 INTRODUCTION

The Belt and Road Initiative1 (BRI), unveiled by China's President Xi Jingping in 2013, is a regional cooperation initiative across Asia, Europe, and Africa based on bilateral and multilateral agreements, which aims to provide investment facilitation and reduce cross-border trade costs. The Belt and Road regions account for approximately 64% of the world's population and 30% of the world's gross domestic product (GDP) (Huang, 2016). The consensus is that the initiative has become an important part of China's reform and opening up, as well as its national development strategy. Although it has been proposed and pushed forward by China, the BRI is open and inclusive, and it is expected to make a positive step forward in promoting free trade in the face of the backlash of antiglobalization.

With a large number of agreements between China and the countries along the BRI routes, it is natural that the initiative would boost China's overseas direct investment and trade, which are the two major tasks of the initiative (Cheng, 2016). However, whether it has benefited the BRI member states' exports is still unclear.2 There is a Chinese proverb that asks, “give-them-a-fish” or “teach-them-to-fish”? This paper aims to examine whether the initiative has achieved the goal of “shared benefits”3 in terms of trade. That is, has the initiative improved the export capacity of BRI countries (“teach-them-to-fish”), rather than just expanding trade between China and other BRI countries (“give-them-a-fish”)? Moreover, we investigate whether the BRI has exerted a spillover effect on global trade. As indicated by Caliendo and Parro (2015), the North American Free Trade Agreement (NAFTA) mainly created trade within the area and even diverted trade from countries outside the agreement. We expect that the BRI can outperform the free trade areas (FTAs) in terms of trade creation, and create trade both within and outside the region.

We employ a difference-in-differences (DID) regression model to examine whether the initiative expanded the exports of countries along the routes, based on a sample of 191 countries from 2008 to 2019. To eliminate the influence of sample bias between the treatment group (BRI countries) and the control group (non-BRI countries), we further use propensity score matching (PSM) algorithms to match the two groups. By comparing changes in the exports of BRI countries with those of non-BRI countries after the signing of the initiative, we find that joining the BRI led to a 20.2% increase in the exports of its member states. This finding is robust when using different PSM algorithms.

We further investigate the origins of the export creation. The BRI not only strengthened trade connections between China and the BRI members but also expanded the export capacity of the member countries. Compared with non-BRI countries, BRI countries exported more to the BRI countries other than China through signing onto the BRI. Furthermore, much of the expansion came from exports to countries along the BRI routes, and there is no evidence of trade diversion from non-BRI countries to BRI countries. This reflects that the BRI boosted export vitality within the area. Moreover, the BRI is indeed open and inclusive, creating new trade rather than diverting trade from non-BRI countries to BRI countries.

Considering the huge export creation from China and the availability of data at the product level, we employ China's import data at the product level to examine export creation on both the intensive and extensive margins. We find that the BRI not only boosted exports of products that existed consistently throughout the sample period but also was conducive to the development of new products, as well as exploration of new markets.

We further explore potential channels for the BRI's export creation. By regressing total investment (logarithm) on the interaction term of interested, we find that there was a positive causal relationship between joining the BRI and total investment. Concretely, the BRI played a positive role in boosting infrastructure capacity, represented by electricity access, internet access, length of railways, container port traffic, and air transport freight. Moreover, private investment in BRI countries improved relative to that of non-BRI countries, due to the spillover effects of foreign investment and infrastructure construction. Improvement in both infrastructure and private investment contributed to the expansion of the export capacity of the BRI countries.

After it is confirmed that the initiative expanded the total exports of its member states, another question that arises is whether the BRI members also performed better in the global value chain (GVC). We employ the indices of GVC position and GVC participation proposed by Koopman et al. (2010), to measure countries' GVC performance. The findings show that the BRI helped its member states move up the GVC by improving their GVC position and GVC participation.

Studies have shown that national borders are harmful to trade through a combination of social and economic factors (Anderson & van Wincoop, 2003), while infrastructure connectivity can reduce the costs of trade (e.g., transport cost and customs clearance cost) and benefit cross-border trade (Bougheas et al., 1999; Limao & Venables, 2001; Limao & Venables, 2003; Martin & Rogers, 1995; Martincus et al., 2014; Martinez-Zarzoso & Nowak-Lehmann, 2003; Vigil & Wagner, 2012). A large literature investigates the effect of the BRI on China's economy because China is the sponsor of the initiative and its most important investor. The BRI has boosted outward foreign direct investment (FDI) and reduced financial constraints on related enterprises (Du & Zhang, 2018; Lv et al., 2019; Xu et al., 2019), expanded export ability, and accelerated industrial upgrading and green development in China (Lin & Bega, 2021; Liu & Xin, 2019; Wang & Lu, 2019).

We focus on the member states that have signed the initiative, rather than just on China. In several aspects, our study differs from the existing literature, which examines trade gains and welfare changes of the member countries (Herrero & Xu, 2017; Jackson & Shepotylo, 2021; Ramasamy & Yeung, 2019; Zhai, 2018). First, we provide evidence that the BRI has achieved its goal of mutual benefit. It has taught other countries to “fish,” that is, the BRI has helped to expand the export capacity of member states both intensively and extensively, and promoted their position and participation in the GVC. Second, we show that the export expansion of member countries has come from newly created export capacity due to reduced export barriers, rather than a zero-sum game dominated by trade diversion. Third, we further explore the potential channels. In addition to the well-known channel of infrastructure investment, the initiative has exerted a spillover effect on private investment in the host countries, which has enhanced export capacity.

Our paper is also related to studies investigating the impacts of FTAs on trade creation, welfare improvement, and economic growth (Baier & Bergstrand, 2007; Caliendo & Parro, 2015; Egger et al., 2011; Grossman & Helpman, 2002; Yang & Martinez-Zarzoso, 2014). We show that the BRI outperforms the FTAs in terms of trade creation through export creation rather than export diversion. Compared with tariff reduction and removal of quantitative restrictions in FTAs, the improved connectivity among BRI countries has created trade through reduction of nontariff barriers, such as the costs of transportation, communication, and customs clearance.

The remainder of the paper is organized as follows. Section 2 provides background on the BRI initiative and its potential effect on trade. Section 3 presents the details of the estimation strategy and the data used. Section 4 verifies the export creation of the BRI and discusses its origins, intensive and extensive margins, as well as the channels. Section 5 examines the effect of the BRI in boosting the GVC position and participation of its member states. Section 6 concludes the paper.

2 THE BRI AND POTENTIAL EXPORT CREATION

The creation of the BRI was a new experiment in regional cooperation based on bilateral and multilateral agreements, announced by China in 2013. It includes the Silk Road Economic Belt and the 21st Century Maritime Silk Road, covering most of the countries in Asia, Europe, and Africa. China had signed cooperation agreements with 17 countries by the end of 2015,4 which expanded to around 200 cooperation documents with 147 countries and 32 international organizations at the end of 2021, based on this cooperation initiative. It is a vital development strategy for China and further deepens China's reform and opening up. Although it was proposed and pushed forward by China, the initiative is open and inclusive and benefits both China and the countries along the routes through reducing various trade barriers.

The primary element of the initiative is infrastructure connectivity.5 Specifically, the initiative aims to build a connective and efficient Asia-Europe market through six overland corridors,6 which will boost trade connections along the corridors through connectivity improvements in transportation, financing, currencies, and policies. China has an overwhelming advantage in infrastructure construction, which is just what the other Belt and Road countries lack. Infrastructure connectivity has also gained strong support through several other sources, such as the Silk Road Fund and the Asia Infrastructure Investment Bank. A range of cross-border projects has also been implemented, including road traffic infrastructure, energy infrastructure, communications network infrastructure, and ports. For instance, the China-Europe Railway Express connected more than 108 cities in 16 European countries by the end of 2019, with a total of 13,000 trains carrying more than 1.1 million 20-foot equivalents of goods. It has become one of the most important logistics along the routes. The convenience of customs clearance has also improved significantly, with the average inspection rate and customs clearance time decreased by 50% (World Bank, 2019). Improvement in infrastructure connection has greatly reduced the cost of trade and improved trade facilitation, both of which were expected to increase trade within the region, as well as trade between the region and other countries. The corridors were expected to boost the trade of the related countries by 2.8 to 9.7 percentage points (World Bank, 2019).

The construction of the BRI also encouraged the growth of private investment from China and other countries (Du & Zhang, 2018). FDI in BRI countries increased rapidly, accounting for 20% of global total in 2017, which was much higher than that (less than 10%) in 2000 (Chen & Lin, 2018). More importantly, FDI can produce spillover effects on local workers' skills, innovation, productivity, and production complexity (Javorcik et al., 2018; Javorcik, 2004; Liu et al., 2014; Lu et al., 2017; Zhang, 2017), which are conducive to the expansion of exports of host countries along the routes.

The BRI fills the gap in the construction of FTAs in the Asian area and accelerates the economic integration of related countries. It differs from FTAs in the following aspects. FTAs enhance trade through the elimination of tariffs and quantitative restrictions among member states, while the BRI is a regional cooperation initiative, which provides trade facilitation through various channels of cooperation related to economic, political, cultural, and other aspects. As stated in an official document in 2015,7 the initiative aimed to achieve win-win cooperation through policy, infrastructure, trade, financial, and people-to-people connectivity. The connectivity contributes to the facilitation of trade among Belt and Road countries. Based on this difference, it is expected that the trade creation effect may also be different between the BRI and FTAs.

3 IDENTIFICATION STRATEGY, DATA, AND VARIABLES

4 “GIVE-THEM-A-FISH” OR “TEACH-THEM-TO-FISH”?

This section provides the DID estimates of the export creation of the BRI and robustness checks using PSM algorithms. Furthermore, we discuss the origins of the export creation and answer the following three questions. In which partners have exports been created? Is the export creation extensive or intensive? Is investment an effective channel of export creation?

4.1 Export creation

The parallel trends assumption ensures that the coefficient of the interaction term reports the export creation of the BRI in its member states. We assume that the time trends of exports in the treatment and control groups were the same before countries joined the initiative. Figure 1 shows the percentage changes in exports of BRI countries (treatment group) compared with non-BRI countries (control group) after countries signed the initiative, based on the regressions of exports on a set of year dummies. The figure provides support for our DID assumption that the time trends of the two groups were highly consistent before the agreements were signed, while they have gradually diverged since countries joined the BRI group. We attribute the enlargement of the gap between the two groups to the export creation effect of the initiative, which is estimated using the DID model.

Column 1 in Table 1 shows the baseline results. The estimated coefficient of the interaction term is positive at the 1% level of statistical significance in the regression controlling the gravity factors (logarithm of real GDP, real exchange rate, urbanization rate, and logarithm of population), as well as the exporter-partner and partner-year fixed effects. This result implies that the exports of BRI members expanded after they joined the initiative. The estimate of 0.202 indicates that the BRI led to a 20.2% increase in the exports of BRI members, compared with those of non-BRI countries. The results are in line with the findings of Maliszewska and van der Mensbrugghe (2019), who projected that infrastructure improvement in the BRI area would lead to increased exports of countries along the routes, compared with those of non-BRI countries.

Table 1. Export creation of the BRI

	Export value (log)
	(1)	(2)	(3)
	All partners	China	Partners except China
Variable of interest
Silk × Post	0.202***	0.582***	0.204***
	(0.0343)	(0.179)	(0.0343)
GDP	0.932***	0.946***	0.939***
	(0.0105)	(0.0474)	(0.0105)
Real Exchange Rate	0.00543***	0.0205***	0.00529***
	(0.000862)	(0.00522)	(0.000861)
Population	−0.0571***	0.514***	−0.0633***
	(0.0106)	(0.0505)	(0.0107)
Urbanization Rate	0.00575***	0.0362***	0.00549***
	(0.000701)	(0.00395)	(0.000702)
Country × Partner FE	Yes	Yes	Yes
Partner × Year FE	Yes	Yes	Yes
Observations	166,582	1,036	165,546
R2	0.219	0.835	0.220

• Note: Silk is a dummy variable for the BRI countries, which equals 1 for BRI members (excluding China) and 0 otherwise. Post is also a dummy, which equals 1 if the country joined the initiative in year t (including the year of signing agreements), and 0 otherwise. For non-BRI countries, it always takes the value 0. Control variables are time-varying and related to exporting countries. GDP is the natural logarithm of the real gross domestic product. Real Exchanges Rate is the real effective exchange rate index based on 2010. Population is the natural logarithm of the total population. Urbanization Rate is the proportion of urban population in the total population. Column 1 is estimated on the full sample. Column 2 keeps China as the only partner, while column 3 drops China from the partner group. Standard errors clustered at the country-year level are in parentheses. *** represents statistical significance at the 1% level. Belt and Road Initiative
• Abbreviations: BRI, Belt and Road Initiative; GDP, gross domestic product.

There may exist sample bias between the treatment and control groups due to differences in economic features, which may lead to failure in identifying the causality between signing the BRI and the expansion of exports of the BRI countries. To avoid this problem, we conduct PSM algorithms to match the two groups using the means of the control variables (the logarithm of GDP, the logarithm of population, exchange rate, and urbanization rate) from 2011 to 2013. We adopted three PSM algorithms: one-to-three, radius, and kernel matching. The results in Table 2 are in line with the baseline estimates.

Table 2. Robustness checks: Export creation of the BRI for all partners

	Export value (log)
	(1)	(2)	(3)
	One-to-three matching	Radius matching	Kernel matching
Variable of interest
Silk × Post	0.105**	0.139***	0.208***
	(0.0492)	(0.0465)	(0.0392)
Baseline Control	Yes	Yes	Yes
Country × Partner FE	Yes	Yes	Yes
Partner × Year FE	Yes	Yes	Yes
Observations	119,895	140,460	148,191
R2	0.208	0.230	0.199

• Note: Variables are the same as in Table 1. We conduct PSM algorithms to match the treatment and control groups using the means of control variables (natural logarithm of GDP, natural logarithm of population, exchange rate and urbanization rate) from 2011 to 2013. Column 1 is one-to-three matching. Column 2 is radius matching. Columns 1 to 2 are matching with 0.05 caliper. Column 3 is kernel matching. Standard errors clustered at the country-year level are in parentheses. ** and *** represent statistical significance at the 5% and 1% levels, respectively.
• Abbreviations: BRI, Belt and Road Initiative; GDP, gross domestic product; PSM, propensity score matching.

5 MOVING UP THE GLOBAL VALUE CHAIN

So far, we have confirmed the export creation effect of the BRI in its member states, and we wonder whether there was also an improvement in their GVC performance. According to the TiVA statistics, foreign value added embodied in the exports of the BRI members was 24% in 2015, 4 percentage points low er than in 2000. This reflects the improvement in export capacity and participation in the GVC. We expect that the BRI accelerated this process.

We define and calculate the GVC position index and GVC participation index for all the countries in our sample, according to Koopman et al. (2010). The details of these two indices are described in our previous paper (Che et al., 2020). Based on the decomposition of the value added of exports, GVC position is measured by the relative value of participation in the upstream and downstream of the GVC, with a positive value for upstream participation (raw materials) in a specific industry and a negative value for downstream participation (final goods).

Figure A1 shows the difference in estimated coefficients between the BRI countries (treatment group) and non-BRI countries (control group), based on the regressions of GVC position on a set of year dummies. It confirms that the time trends of the two groups were consistent before the agreements were signed, and they have diverged significantly since countries signed the initiative. We further employ the same DID framework (Equation 1) to estimate the effect of the BRI on its members' GVC position. Column 1 in Table 8 reports the results. The coefficient of the term of interest is negative and significant at the 1% level of statistical significance, indicating that the BRI led to upgrading exports, moving from upstream (dominated by raw materials) to downstream with improvement in product complexity and value added.

GVC participation reflects the intensity of a country's participation in a sector in the GVC, and we expect that the BRI enhanced the GVC participation of its member states. Accordingly, Figure A2 verifies the parallel trends assumption and column 2 in Table 8 shows the estimates related to the GVC participation index, with basic controls and fixed effects at the country and year levels. The estimated coefficient is significantly positive, implying that the BRI caused deeper participation in the GVC for its members and strengthened the trade links between the BRI countries and non-BRI countries. This finding is consistent with that of Zhang et al. (2021), who show that free trade agreements benefit exports in both simple and complex value chains.

6 CONCLUSION

We have examined the export creation of the BRI in its member states, based on a DID strategy. We found that signing the BRI boosted the exports of its members by 20.2%, compared with the non-BRI countries. Our results are robust when using PSM algorithms to match the treatment group (BRI countries) and control group (non-BRI countries). Export creation mainly came from China (considered as “give-them-a-fish”), which is the sponsor and main investor in the initiative. Export creation also originated from the BRI countries other than China (expansion of export capacity, which is “teach-them-to-fish”), and there was no evidence of export diversion from non-BRI countries to BRI countries. Both the intensive and extensive margins contributed to the export expansion of the BRI member states. We explored the investment channels for the BRI's export creation and found that the BRI exerted significant spillover effects on infrastructure capacity and private investment, both of which are conducive to export creation. Furthermore, joining the initiative was conducive to moving up the GVC (measured by GVC position and participation) for the BRI members.

Infrastructure connectivity was the primary task of the BRI and the main reason behind the export creation. The connectivity along the BRI routes is ongoing, and it is expected that the export creation of the BRI will be further enhanced in the long run.

AUTHOR CONTRIBUTIONS

Yu Chen: data curation; formal analysis; investigation; methodology; software. Yan Zhang: conceptualization; formal analysis; methodology; project administration; supervision; validation; visualization. Lin Zhao: conceptualization; formal analysis; validation; visualization; writing–original draft; writing–review & editing.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

ETHICS STATEMENT

None declared.