Digital Economy Development, International Trade Efficiency and Trade Uncertainty

2.1 International Trade Efficiency

International trade efficiency is an important factor affecting trade growth. Scholars at home and abroad use the HSFG model to decompose trade growth into trade potential growth and trade efficiency growth. They use trade potential to express the theoretical trade volume that can be achieved when there is no trade resistance, that is, the “frontier” level of trade, and use trade efficiency to describe the degree to which trade resistance makes the actual trade volume deviate from trade potential, so as to bring the unobservable trade cost caused by “subjective trade resistance” into the analysis. The traditional gravity model often classifies the “artificial resistance” which is difficult to quantify, such as the information cost of buyers and sellers and market system constraints, into stochastic disturbance terms, and assume that their mean value is zero. By introducing the concept of international trade efficiency, it is more realistic to incorporate these influencing factors into the loss of trade efficiency for analysis.

In their research, some scholars assume that international trade efficiency is only a function of time. Shi and Li (2009) assumed that trade efficiency only changed year from year. They used the stochastic frontier gravity model in their analysis and found that China’s trade efficiency showed a downward trend. With the introduction of HSFG model, the influence of market factors on international trade efficiency has attracted more and more attention. Some scholars use natural factors such as market size, income level and geographical distance, which are difficult to change in the short term, to determine trade potential, and analyze trade efficiency by taking human factors such as trade agreements, infrastructure level and institutional constraints into consideration. Lu and Zhao (2010) found that the increase of tariff level may reduce trade efficiency, while a high level of democracy and rule of law in the importing country could play a positive role in promoting China’s export efficiency. Tan and Zhou (2015) found that free trade agreement (FTA) and better transportation infrastructure can significantly improve the efficiency of China’s export to countries along the Maritime Silk Road, while high tariff level, long customs clearance time and low financial freedom may increase the loss of trade efficiency. In addition, some scholars have analyzed the trade potential based on factor endowment. Wu (2003) believed that factor input determines export supply, market environment determines factor allocation, factor input density and market environment determine trade potential. Taking market environment variables into consideration when studying trade efficiency, he analyzed export potential and export efficiency of different regions in China, and found that improvement of infrastructure and increase in government expenditure could improve China’s export trade efficiency. Lu and Lian (2011) used factor input to determine the export potential of different provinces, municipalities and autonomous regions in China and analyzed the impact of institutional constraints on export efficiency, finding that infrastructure improvement, government expenditure, market reform, and foreign investment could all promote the export efficiency of China.

2.2 Trade Uncertainty

In recent years, the research on trade growth has been deepened, but there is still insufficient attention to trade uncertainty and trade fluctuation. The importance of trade uncertainty lies in that intensified trade fluctuation can have a negative effect on economic growth and national welfare. Mendoza (1997) pointed out that increased trade uncertainty may reduce investment, capital accumulation, and consumption-based return on savings, thus slowing down long-term economic growth. Blattman et al. (2007) noted that increased trade uncertainty may heighten trade and investment risks, reduce the accumulation of imported capital, and produce a negative impact on economic growth.

Most of the existing studies think that demand effect and trade competitiveness are the main causes of trade fluctuation. Tang and Lin (2012) found that external demand shocks can well explain the fluctuation of export volume and price. Yu (2013) believed that the fluctuation of external demand during the financial crisis is the main reason for the increase of China’s trade uncertainty. Li (2009) used factor analysis to find that changes in trade competitiveness are the main cause of China’s trade fluctuation. Some scholars have also analyzed the impact of signing FTAs, joining international organizations, and institutional constraints of the market on trade uncertainty. Mansfield (2008) pointed out that joining the WTO and signing FTAs could restrict member countries from taking new trade protection measures and improve their policy transparency, thus reducing trade uncertainty. Wei and Zhang (2018) found that China and its trading partners’ accession to the WTO could reduce the price fluctuation of China’s imports. As for the market system, Lu and Lian (2011) used the HSFG model to analyze the influence of institutional constraints on the export stability of different provinces, municipalities and autonomous regions in China. Cui and Liu (2017) used the same method to analyze the influence of the market systems of countries along the “the Belt and Road” on China’s export uncertainty.

2.3 Digital Economy and International Trade

The influence of DED on international trade has become a hot topic in academic circles. Existing studies generally believe that the application of Internet and ICT can significantly increase the scale of international trade (Freund and Weinhold, 2004; Shi, 2016; Abeliansky and Hilbert, 2017). Some scholars have made analysis from the enterprise level and found that the application of Internet and ICT can enhance the export tendency of enterprises (Li et al., 2015; Yue and Li, 2018). Theoretical mechanism analysis is mostly carried out from the perspective of trade cost, and it is believed that the application and development of ICT can reduce the fixed and variable costs in trade, and then promote the growth of trade. Sun et al. (2017) proposed that the application of Internet and ICT can effectively overcome the information barriers in trade and reduce the search and matching costs in trade. Sheng et al. (2011) held that the development of communication technology reduces the communication cost in trade. Li and Li (2017) believed that the use of Internet can reduce the cost of recommending new products and exploring new markets. Pan and Xiao (2018) pointed out that Internet can promote global division of labor based on specialization and strengthen market competition, thus forcing enterprises to transform and upgrade and reducing production costs of export enterprises.

3.1 DED and International Trade Efficiency

From the perspective of trade cost, this paper analyzes how importing countries’ DED affects China’s export trade efficiency, focusing on the impact of their DED on the cost caused by “artificial resistance”. The following discusses how the development and application of digital technology in importing countries can reduce trade costs in two stages: the establishment of trade relations and the performance of trade contract.

In the stage of establishing trade relations, due to the existence of information barriers, the matching between two trade parties needs certain costs, including search cost, communication cost and credit cost. Existing studies mainly consider the impact of exporting countries’ ICT application on information barriers, but in fact, the establishment of trade relations is a two-way process, where importing countries’ DED also affects exporting countries’ cost of obtaining the market information of importing countries. First of all, the development of Internet and e-commerce platform in importing countries can expand the searchable range of trade information and reduce the cost of searching such information for both the buyer and the seller. The development of search engines also makes the matching of supply and demand information of specific products more efficient. The application of digital technology in importing countries enables enterprises in exporting countries to reduce the cost of displaying and promoting their products through online marketing. Secondly, the development of ICT in importing countries can reduce the communication costs of both parties, and the Internet enables buyers and sellers to communicate in real time without spatial and temporal constraints, thus avoiding the human and the financial costs caused ty traditional “face-to-face” trade negotiations and improving the communication efficiency. Credit cost refers to the cost paid by both parties to obtain each other’s credit information. In the era of digital economy, the credit evaluation system based on the digitalization of transaction behaviors has increased the methods and scope of credit evaluation. Countries all over the world have discussed how to build an effective credit evaluation system and relevant standards. The development of Internet and data processing technology has provided new channels for international cooperation and credit information sharing, and reduced the credit cost of both the buyer and the seller.

In the stage of trade contract performance, due to the widespread existence of tariff and non-tariff barriers, enterprises in exporting countries need to pay institutional costs, especially various compliance costs. In the era of digital economy, all countries are advancing the process of informationization of government affairs, and the development of e-government based on the “Internet plus” strategy is attracting wide attention. The provision of online services in importing countries, such as the construction of IT-based customs clearance platforms, streamlines trade-related compliance procedures, shortens the time of handling such procedures, and improves the processing efficiency, thus reducing the compliance costs of exporters. E-commerce platforms and mobile banking also reduce the cost of payment. Therefore, we put forward the following hypothesis.

Hypothesis 1: The improvement of DED level in importing countries reduces trade resistance and improves trade efficiency.

3.2 DED and Trade Uncertainty

From the perspective of competition, an importing country’s DED intensifies its own market competition, which may increase the uncertainty of China’s export. First, the Internet and e-commerce platforms in the importing country expand the searchable scope of trading partners, and then increase the number of existing and potential competitors. Secondly, existing studies generally find that investment in information infrastructure improves a country’s productivity and innovation capacity. Importing countries’ DED, therefore, can increase the productivity of their own domestic enterprises, and at the same time, reduced information exchange cost and learning cost may promote their innovation and R&D activities. As a result, their homogeneous or even upgraded products can further intensify the market competition in importing countries. On the one hand, intensification of competition continuously reduces the price of products; on the other hand, China’s export products, usually with low value-added, are rather prone to substitution, so there is very limited room for price reduction. In addition, the domestic production cost is rising, and the dynamic market competitiveness of China’s export products is insufficient. Therefore, the intensification of market competition in importing countries is very likely to increase the uncertainty of China’s exports.

From a policy point of view, the key to promoting the growth of international trade through DED in importing countries is low-cost and high-efficiency data transmission. Yet, the rules and policies for cross-border data transmission are significantly different from country to country. In recent years, network security incidents have occurred frequently. While all countries are promoting DED in their own territories, some of them are beginning to impose restrictions on cross-border data transmission for the sake of protecting citizens’ privacy and national data security. For example, the Russian government requires domestic and foreign companies to store the personal

data of its citizens within Russia; the General Data Protection Regulations adopted by the European Union in April 2016 prohibits the transmission of its citizens’ personal data to third-party countries that cannot provide adequate protection. Different countries have different rules for cross-border data transmission and for the use of such data, and the conflict of interest between government and enterprises in data use makes the formulation of relevant policies remain in the exploratory stage, which also brings uncertainty to digital technology-based trade growth.

From the perspective of demand, while reducing trade costs and increasing market openness, importing countries’ DED also makes them more vulnerable to the impact of world economic fluctuations, thus affecting the uncertainty of China’s exports through the demand effect. Mansfield (2008) pointed out that the improvement of market openness may increase the uncertainty of employment, wages and corporate profits. The resulting demand fluctuation is likely to increase the uncertainty of China’s export trade. Therefore, we put forward the following hypothesis.

Hypothesis 2: The improvement of DED level in importing countries may increase the uncertainty of China’s export trade.

4.1 Model Specification

In this paper, the HSFG model is used to verify the two hypotheses, and basic structure of the model is as follows:

Wherein, e x p i t ∗ stands for the trade potential of China’s export to country i in year t; exp_it for the actual volume of China’s export to country i in year t; u_it is a trade inefficiency term used to describe the loss of trade efficiency caused by trade costs. Since trade costs cannot be completely eliminated, it is assumed that the trade inefficiency term obeys the law of truncated semi-normal distribution, that is, u i t ∼ N + μ i t , σ u 2 . v_it is a random error term in the general sense. v i t ∼ i i d N 0 , σ v 2 is assumed and u_it and v_it are mutually independent. X_it is an explanatory variable for determining trade potential. Based on the existing research as reference and using the traditional gravity model, here the trade potential is determined by natural factors that are basically unchanged in the short term, such as economic scale, geographical distance and common language, that is:

Wherein, GDP_et and GDP_it represent the gross domestic product of China and that of the importing country in year t, respectively, to measure the economic scales of the two sides; pop_it stands for the importing country’s population in year t, to measure the size of China’s export market; ^[1] d is the geographical distance between the two countries; comlang indicates whether the importing country and China share a common language.

In this paper, we use the mean value of trade inefficiency term μ_it to measure the loss of trade efficiency caused by “artificial resistance”; and use variance σ u 2 to measure the trade uncertainty caused by changes in “artificial resistance”. We include the importing country’s DED index into the estimation equation of the mean and variance of trade inefficiency term, and introduce the relevant institutional indicators of the importing country as control variables for analysis, that is:

Wherein, NRI_it is the DED level of country i in year t, which is the core variable in this study; suf_it is the customs clearance efficiency of country i in year t; tari_it is the weighted average tariff of country i in year t; trans_it is the trade transportation infrastructure level of country i in year t; and fta_it indicates whether country i has an effective FTA with China in year t. The year effect is controlled in the estimation equations of mean and variance. On the one hand, we control the influence of difficult-to-observe factors that change year from year but that do not change from country to country, such as the periodic fluctuation of the world economy. On the other hand, we control the influence of China’s DED and market changes.

4.2 Test Method

In this paper, the maximum likelihood estimation (MLE) method is used to estimate the HSFG model constructed, and the corresponding log likelihood function is:

Wherein,

Wherein, ∅ (•) and Φ (•) represent the density function and cumulative distribution function of standard normal distribution, respectively.

4.3 Data Source and Descriptive Statistics

4.3.1 Description of the Core Variable

In this paper, the World Economic Forum’s networked readiness index (NRI) is used to measure the DED level of an importing country. As shown in Figure 1, the index is based on three sub-indexes: environment, readiness and application, which respectively evaluate the ICT development environment, the interest and ability to use ICT and the practical application of ICT by major interest groups. Through an analysis of the NRIs of 115 sample countries from 2007 to 2015 (the reference period), it is found that there are obvious differences in DED between countries of different income levels and between different regions. As shown in Figure 2, DED levels in high-income countries are always higher than those in middle- and low-income countries, and their average NRIs are 4.89, 3.56 and 2.93 respectively. Figure 3 describes the differences in NRI between different regions: Africa obviously lags behind other regions, with an NRI growth rate of only 3.52% in the reference period; the NRI of America is higher than that in Africa, with a growth rate of 8.08% in the reference period; the NRI of Asia is at the middle level, but grows rapidly at a rate of up to 12.3% in the reference period, which is significantly higher than that in any other region; the NRI of Europe is lower than that in Oceania, with a growth rate of 8.07% in the reference period. Oceania in this paper only includes two countries, New Zealand and Australia, and their NRI has always been at a high level, with a growth rate of 7.32% in the reference period. It is noteworthy that China’s NRI rose from 3.68 to 4.20 in the same period, up 14.1%, significantly higher than the world’s average level, which fully reflects the progress made by China in DED in recent years.

Figure 1

Composition of NRI

Figure 2

Average NRIs of Countries with Different Income Levels

Figure 3

Average NRIs of Different Regions

5.1 Estimation Results of the HSFG Model

Table 2 reports the estimation and test results based on different models. Among them, Models (1) ~ (4) are the estimation results by adding, one by one, the variables in Formula (3) that affect trade potential after controlling the year effect. It can be seen that NRI, which represents DED level, has a significant negative impact on trade inefficiency terms and a significant positive impact on trade uncertainty, indicating that importing countries’ DED can significantly improve China’s export trade efficiency yet increase trade uncertainty. Model (5) is the estimation result without controlling the year effect. The likelihood ratio statistics LR1 and the corresponding P values of Models (4) ~ (7) indicate that there is a trade inefficiency term, and that it is more reasonable to use the HSFG model for estimation. Through likelihood ratio statistics LR2, the corresponding P value and the log likelihood value, it can be found that unconstrained Model (4) is obviously superior to Models (6) ~ (8) to which different constraints are added, showing that the model in which the mean and variance of trade inefficiency term are both heterogeneous is more reasonable in structure. Therefore, the following analysis will be based on Model (4).

It can be seen from the estimation results of trade potential in Model (4) that the economic scales of China and the importing country, lnGDP_e and lnGDP_i, and the importing country’s population lnpop_i have a positive impact on trade potential, and the impact is significant at the level of 1%, indicating that the higher the income level of both parties and the larger the export market are, the greater the trade potential will be. The coefficient of geographical distance lnd is significantly negative at the level of 1%, indicating that the farther the distance is, the smaller the trade potential will be. The coefficient of comlang that means whether the two countries have a common language is significantly positive at the level of 1%, indicating that two countries with a shorter cultural distance have greater trade potential. These findings are in line with the estimation results of traditional gravity models.

The estimation results of trade inefficiency verify Hypothesis 1 proposed in this paper. The coefficient of NRI that represents the importing country’s DED level is significantly negative at the level of 1%, which shows that the importing country’s DED can significantly reduce the loss of trade efficiency and improve China’s export efficiency. Improved DED level of the importing country facilitates the establishment of its trade relations with China, and at the same time reduces a series of costs faced by China in the export process, thus improving the efficiency of China’s export trade. In addition, the coefficient of fta representing whether there is an FTA is significantly negative at the level of 5%. The existence of an effective FTA between China and the importing country can significantly reduce tariff and non-tariff barriers in trade, reduce efficiency losses and help improve China’s export efficiency.

The estimation results of trade uncertainty verify Hypothesis 2 proposed in this paper. The coefficient of NRI that represents the importing country’s DED level is significantly positive at the level of 1%, indicating that DED in the importing country may aggravate the trade fluctuation of China’s exports to that country. The importing country’s FED reduces trade cost, and intensified competition from third-party countries and the importing country itself increases the uncertainty of China’s exports. Secondly, with the continuous development and application of digital technology, the trade market is being digitalized, and related policies and enterprises’ adaptation are uncertain. The emergence of new issues such as network security and cross-border privacy protection, and the reshaping of interest patterns lead to frictions between countries, for which international coordination is necessary and ongoing. As can be seen, while global DED brings new opportunities to international trade, it is also reshaping the trade pattern and bringing new challenges to China’s exports. At the same time, the coefficient of weighted average tariff tari is significantly negative at the level of 5%, which shows that increased tariff level in the importing country may reduce the uncertainty of China’s exports. As a trade barrier, the importing country’s tariff may increase trade cost, and its effect is opposite to that of DED. Trade transportation infrastructure level trans is significantly negative at a level of 1%, and can reduce the uncertainty of China’s exports, the reason for which may be that a higher level of trade transportation infrastructure in the importing country is conducive to China’s diversified market expansion in that country, thus reducing the risk and fluctuation of trade.

5.2 Differences between Countries with Different Income Levels

According to the classification standard of the World Bank, importing countries are divided into high-income countries and low/middle-income countries ^[1] for group-by-group regression, and the results are shown in Columns (1) and (2) of Table 3. It can be found that the impact of DED in importing countries with different income levels on trade inefficiency term is significantly negative at the level of 1%, which is consistent with the overall estimation results. And through the coefficient, it can be found that DED in low/middle-income countries can significantly improve the efficiency of China’s export to these countries. Estimation results of the trade uncertainty are basically consistent with the overall estimation results, and DED in all importing countries with different income levels increases the trade uncertainty of China’s export. In the reference period, the average trade efficiency of China’s export to low/middle-income countries is always lower than that to high-income countries, and DED can effectively reduce the difference in trade efficiency between high-income countries and low/middle-income countries. It can be seen that global DED is conducive to creating a fairer trade environment and providing new opportunities for low/middle-income countries to improve their market attractiveness.

5.3 Robustness Analysis

5.4 Analysis of Trade Efficiency

After estimation of Model (4), the trade efficiency of China’s exports to 115 sample countries is obtained according to Formula (9).

Figure 4 shows the distribution of trade efficiencies of China’s exports to sample countries from 2007 to 2015 (the reference period). It can be seen that most of the trade efficiencies are between 70% and 90%. In this period, China’s average export efficiency is 73%, specifically, 72.5% in 2007 and 73.5% in 2015. It can be seen that in these nine years, China’s export trade efficiency improved on the whole, but the increase was very limited. At the same time, the efficiency of export to some countries is still very low, and the trade potential is far from being fully realized. For example, the average trade efficiency of China’s exports to Chad is only 25.2%, which shows that there is still much room for improvement in global trade efficiency.

Figure 4

Distribution of Trade Efficiencies

Figure 5 is a sequence diagram of China’s export efficiency. It can be found that there are obvious differences in the efficiency of China’s exports to countries with different income levels. The average efficiency of export to high-income countries in the reference period is about 81.5%, which is always higher than that of low/middle-income countries and that of all samples. The average efficiency of export to middle-income countries is 71.4%, while that to low-income countries is always the lowest, about 52.9%. At the same time, it is found that in 2009, the efficiency of China’s export to sample countries as a whole and that to countries with different income

Figure 5

Sequence Diagram of Trade Efficiency

levels both decreased significantly, which may be caused by the deterioration of global economic environment caused by the international financial crisis and other factors. In addition, the efficiency of export to high-income countries showed a downward trend on the whole, from 84.2% in 2007 to 78.7% in 2015, a decrease of 6.5 percentage points. In recent years, trade protectionism has been on the rise. Under the influence of “anti-globalization”, high-income countries have introduced a series of protectionist measures, which have increased the cost and decreased the efficiency of China’s export. The efficiency of export to middle-income countries increased by 4.6%, and that to low-income countries increased most obviously, up 27.5 percentage points from 2015 to 2007. In recent years, the information infrastructure of low/middle-income countries has been continuously improved, and their DED has made China’s export efficiency continuously improve. Since the Belt and Road Initiative (BRI) was put forward, China has continuously strengthened connectivity and economic cooperation with BRI-participating countries. The construction of transportation infrastructure and trade cooperation have created a better business environment for these countries, which not only reduced the loss of trade efficiency of China’s export, but also enabled participating countries to reap abundant benefits from cooperation.