As a textile product with a long history and unique charm, silk plays an important role in global economic and cultural exchanges (Loewe, 1971). With the deepening trend of economic globalization and the upgrading of the structure of the world's silk industry, the pattern of international silk trade has also undergone significant changes (Shu, 2019). Currently, nearly 70 countries and regions around the world produce silk as well as silk-processed products, the vast majority of which are developing countries, the major ones being China, India, Vietnam, Uzbekistan, Brazil and Thailand (Gu, 2001). China is the world's largest producer and trader of silk, and India is the world's second largest producer of silk and raw silk and the largest consumer of silk (Feng et al., 2009). These countries have good natural conditions for mulberry planting and sericulture as well as advanced production technology and a large number of laborers, which are the main bases for silk production and export (Popescu, 2018).

The international trade market of the silk is complex and dynamically changing. After a long period of low silk prices, silk prices have rebounded to more than 55$/kg, stimulating the recovery of the silk cocoon and raw silk trade in many countries (Popescu, 2018). Madsen (2012) show that technological improvements, such as the introduction of sericulture hybrids, can increase silk production, which in turn affects silk exports. In addition, changes in international market demand, adjustments in trade policies, and geopolitical factors also have a profound impact on silk trade (Popescu, 2018). The trade volume of silk products varies greatly among different types of products. Woven fabrics are more expensive in the export market, while the import price of raw silk and silk yarn is relatively low (Gu, 2001). As the cocoon and silk industry is a more typical labor-intensive industry, the impact of international market fluctuations on the industry is very significant, and the major silk-exporting countries have transformed their export trade mode from quantitative expansion to winning in quality and efficiency (Feng et al., 2009; Zhang et al., 2018).

Scholars have launched a series of studies on the main factors causing fluctuations in China's silk export trade. From the comparative advantages of China's silk products and international competitiveness, silk is a product with strong competitive advantages in China (Gu and Zhang, 2002). From the analysis of export trade of various products, raw materials such as silk and semi-finished products such as silk satin have strong competitive advantages in the international market, while the competitiveness of women's shirts and other silk products is weaker (Fan and Chen, 2013). The size of the international silk market and the domestic production of raw silk affect China's raw silk export trade, with the reduction in the size of the international silk market being the main reason for the serious difficulties faced by China's silk industry, and oversupply due to the rapid expansion of the size of the domestic silk industry being a secondary reason (Lin et al., 2006). The trade facilitation of the Belt and Road partners has great potential to promote the development of China's silk export trade, and it can effectively promote silk export trade goods to the international market (Ren and Gu, 2019). In addition, the GDP of silk importing countries, the geographical distance between China and silk importing countries, the bilateral real exchange rate and China's accession to the WTO also have a significant impact on China's silk export trade (Huo and Lin, 2008). Cross-sectional comparisons based on China's major textile export complexity indicators and longitudinal comparisons of China's silk industry export complexity indicators with other silk exporting countries show that China is only a major silk exporting country, not a silk technology powerhouse (Gu and Fang, 2013).

Currently, there are relatively limited studies on China's trade fluctuations in silk products. The existing literature mainly carries out qualitative research and descriptive statistical analysis to analyze the characteristics and development trends of trade in silk products between China and its major trading partners in terms of silk product production, trade product structure, and trade country characteristics (Liu et al., 2006; Feng and Teng, 2012), and only a few scholars utilize the application of econometric models to analyze China's export trade of silk products and its fluctuations from the perspectives of trade competitiveness and development potential (Gu and Zhang, 2002; Fan and Chen, 2013; Wang L. et al., 2017; Huo and Lin, 2008). The existing literature rarely uses the constant market share model to analyze the factors affecting the trade volatility of China's silk products, nor does it systematically analyze the extent to which natural silk products, silk and satin products, and secondary silk products in the silk industry chain affect their respective trade volatility.

Regression models have been widely applied to analyze the relationship between a single specific variable and export trade volatility by using time series data (Chiou-Wei and Zhu, 2002; Karagöz, 2016; Azar and Ciabuschi, 2017; Ahmadi-Esfahani, 2006). In recent years, for example, gravity models have been applied more to bilateral trade studies (Wang et al., 2022; Masood et al., 2023; Nasrullah et al., 2020; Leng et al., 2020). The trade gravity models often include dummy variables, such as common borders, common language, common religion, etc., as well as institutional indicator variables, such as whether they belong to the same preferential trade agreement or regional integration organization. Such variables that affect export trade volatility are infinite (Widodo, 2010) and most of these variables are not easily and accurately measured, therefore such models can only be used to study the few factors that affect export trade volatility.

The CMS model is one of the main methods used internationally by scholars to study the dynamics of countries' exports and the factors that influence them (Batista, 2008; Merkies and van der Meer, 1988). It was first proposed and applied to the study of world trade by Tyszynski (1951) and refined by Fagerberg and Sollie (1987). In subsequent studies by Jepma (1989), Milana (1988), and Leamer and Stern (2017), The first-level effects were further refined to form a two-level decomposition of the CMS model. The CMS model does not attempt to explain how a particular economic variable affects the volume of export trade; it divides the fluctuations in the volume of export trade into three components, structural effect, competitiveness effect and second-order effect, each with different economic significance (Hatsopoulos and Krugman, 1987; Muhammad and Yaacob, 2008). In addition, the CMS model is able to analyze export volatility comprehensively and accurately with simple and easily available trade data (Wang Z. X. et al., 2017). In a way, the CMS model is a more “macro” analytical framework than other empirically constructed models, making it an important complement to other empirical models used to study the effects of specific variables (Widodo, 2010).

Currently, many scholars utilize the CMS model to study international trade, and most of the studies focus on analyzing the influencing factors of trade fluctuations of specific products, such as aquatic products (Dai et al., 2020), tobacco products (Ruitao et al., 2018), nuts (Aguiar et al., 2017), new energy products (Wang Z. X. et al., 2017). Scholars also take a regional perspective to study the trade between exporting countries and other countries as well as major regions (organizations) in the world, such as the Asian market (Chen and Duan, 2001), the European Union (EU), the North American Free Trade Area (NAFTA), North-East Asia and ASEAN (Widodo, 2010; Abdul et al., 2022), Central and Eastern Europe (CEE) countries (Liu and Xiao, 2018).

From 2002 to 2022, the global silk trade exhibited considerable fluctuations. Beginning in 2002, silk trade experienced rapid growth, increasing from US 3.874 billion to US 5.035 billion and reaching its peak in 2008 (Figure 1). Following this peak, the trade volume fluctuated and declined to US 3.507 billion. China, as the largest silk producer and trader worldwide, has consistently maintained a significant position in the global silk market. In 2022, China's import and export of silk products accounted for 32.6% of the global total, highlighting its integral role in the international silk industry.

Similarly, China's silk trade also demonstrated notable volatility during the same period, as shown in Table 1. After joining the World Trade Organization, China's total silk trade surged from US 1.228 billion in 2002 to US 2.130 billion in 2008, achieving an average annual growth rate of 10%. This growth significantly outpaced the global silk trade growth rate of 3.88%. However, the global financial crisis led to a 12.4% decline in China's silk product trade in 2009 compared to the previous year. Although silk exports began to recover in 2010, the growth rate remained modest at 3.92%, below the earlier 10% rate. Subsequently, factors such as the global economic slowdown and regional instability caused the total trade volume to decrease from US 1.799 billion in 2015 to US 1.386 billion in 2019, with an average annual growth rate of −8.62%. Notably, in 2014, India and the European Union surpassed China, marking a significant turning point (Huang and He, 2022). Finally, after reaching a low of US 801 million in 2020, China's silk trade volume rebounded rapidly to US 1.377 billion in 2022.

In spite of the fluctuation of silk product trade, China has maintained a long-term trade surplus position in silk product trade over the past two decades. Silk product import in 2022 accounted for only 16.1% of the total trade value, while the exports accounted for 83.9%. This trade surplus is primarily attributed to China's production volume, quality advantages, and strong demand in foreign markets.

Silk products are categorized into three major classes based on the classification criteria of the Harmonized Commodity Description and Coding System. They are natural silk products (cocoon, raw silk, waste silk, non-retail silk, yarn made from non-retail waste silk), silk and satin products, and secondary silk products (women's blouses, silk scarves and shawls, neckties).

As depicted in Figure 2, from 2002 to 2022, silk and satin products and natural silk products, with relatively small profit margins, are the main categories of China's silk products trade. The average annual trade volume of silk satin products is 656 million US dollars, with an average annual growth rate of 10.57%, while the trade of natural silk products showed a similar growth trend, with an average annual growth rate of 7.45%. Comparatively, secondary silk products, which have relatively higher profit margins, grew more slowly, at 4.86%. It is worth mentioning that the global economic crisis in 2008 caused a reduction in the scale of the international silk market, resulting in serious difficulties for China's silk industry.

China's export trade of silk products has declined continuously since 2012, with a large degree of volatility. Between 2013 and 2022, there was a notable decrease in the trade value of silk and satin products, declining from 888 million US dollars in 2013 to 388 million US dollars in 2022. During this period, the trade trends of silk and satin and natural silk products were similar, both showing a decline year by year. The decline in silk and satin products was faster, especially after 2017, with an average annual trade balance of only 28.61 million US dollars.

The target markets for Chinese silk products are highly concentrated, with a limited number of import and export trading partners. The main trading partners are India and Pakistan in South Asia, Japan and South Korea in East Asia, and Italy, Germany, and France in Europe. These nations constitute the most significant markets for both imports and exports.

Table 2 displays the top eight countries or regions to which China's silk products were exported in 2022. India stands out as China's largest market for silk, with an export value of 145 million US dollars and accounting for 15.26% of China's total silk export value. For silk and satin products, Italy and Pakistan are the main export destinations, with export values of 108 million US dollars and 54.58 million US dollars, respectively, and accounting for approximately one-third of the total export value. Secondary silk products are mainly sold to developed countries such as the United States, Japan, Germany, and France. The United States, in particular, is China's foremost market for secondary silk products, accounting for 16.88% of the total export value.

The main partner countries and the trade value of China's silk products import are depicted in Table 3. India, Italy, and Uzbekistan are the largest sourcing countries of China's silk product imports, accounting for over 60% of China's total silk product imports. In 2022, the market concentration of silk products imported to China was notably high, primarily centered around India, Uzbekistan, South Korea, and Malaysia. The import value of silk products from each of these countries to China exceeds 10 million US dollars, contributing to a cumulative import share of 42.78%. Italy holds the position of being the largest exporter of silk and satin products to China, constituting 26.44% of the total imports, and is followed by Japan, India, and South Korea, with import values all exceeding 1 million US dollars. The import concentration of China's secondary silk products is the highest, with Italy and France being the key sourcing countries, with import values of 72.8 million US dollars and 54.98 million US dollars, respectively. The combined import share of these two countries reaches 45.34%. This high concentration is attributed to the superior quality and brand premium associated with silk processed products manufactured in Italy and France.

As can be seen from the analysis in the previous section, the trade volume, product structure and market structure of China's silk products trade have shown tremendous fluctuations. However, descriptive analysis does not explain the causes of trade fluctuations. Silk trade involves a variety of silk product categories and a large number of trading partner countries, and the data presents the characteristics of multi-dimensionality and complexity. Therefore, the constant market share (CMS) model is adopted to explore the influencing factors behind the fluctuation of China's silk trade with other countries in a more comprehensive and in-depth manner from a more macroscopic perspective.

In this paper, the 23 countries that account for more than 90% of China's total exports of silk products are considered as a whole, without taking into account the changes in market demand among the exporting countries. Therefore, this study builds on the model constructed by Jepma (1989) and refers to the model settings of previous scholars (Liu and Xiao, 2018; Wang Z. X. et al., 2017; Bagaria and Ismail, 2019; Capobianco et al., 2017). The model setup of Capobianco constructs the CMS model by dividing the export growth of silk products into two levels and simplifying the second level of decomposition appropriately.

The decomposition formula of the first level model is as follows:

Where q represents the export value of silk products from China to other countries or regions, Q_i represents the import value of the i-th category of silk products by China from other countries or regions, and S_i represents the proportion of China's export value of the i-th category of silk products to the total import value of the i-th category of silk products by other countries or regions. The superscript 0 denotes the base (initial) year, and Δ represents the change between the terminal and base years.

At the second level decomposition model, structural effects can be further decomposed into two items:

The competitive effect can be decomposed into:

The second-order effect can be decomposed into:

Hence, the decomposition formula of the second level model is as follows:

These decomposed effects calculated in above models are depicted in Figure 3.

The definitions of each effect decomposition of the model are shown in Table 4.

The data for the silk product trades were obtained from the United Nations Commodity Trade Statistics (UN Comtrade) database. Specific categories of products were defined by referring to the HS1996 statistical standard classification codes. The production technology and end-users are very different among different silk products. Meanwhile, different types of silk products also have different tariff policies, trade barriers and market competition situation. We therefore divide the silk products into three categories, they are atural silk products, silk and satin products, secondary silk products. The selected categories include a portion of Chapter 50 (5001–5006) as natural silk products, encompassing silk cocoon (5001), raw silk (5002), waste silk (5003), non-retail silk (5004), non-retail waste silk woven into yarn (5005), and retail waste silk woven into yarn (5006). Category 5007 of Chapter 50 is silk and satin products. A part of products from Chapter 62 are secondary silk products, including women's shirts (620610), scarves and shawls (621410), and ties (621510).

For the segmentation of export markets, 29 countries or regions were selected based on the volume of silk product trade with China. India, the United States, Italy, Romania, Germany, Singapore, Japan, and South Korea are the eight countries with the largest trade values and these countries account for over 90% of China's silk product exports in total. These 29 countries or regions were grouped together as “other countries”.

Due to China joined the WTO in November 2001 and started to fully implement its obligations and enjoy corresponding rights in 2002. For the silk trade, this led to a new rule environment and closer integration with the global market, making 2002 a significant starting point for analyzing the changes in silk trade. Therefore, the research period of this paper is 2002–2022 and is divided into four phases:

2002–2009, marked by rapid export growth. Following China's accession to WTO, the process of global economic integration and further opening of national markets has accelerated significantly, and China's trade in silk products has shown an upward trend. 2010–2014, The far-reaching effects of the international financial crisis and the contraction of world trade have led to unstable demand for silk products in the international market, and the scale of China's silk exports has declined, followed by a slow recovery trend. 2015–2019, Export trade continues to shrink stage, Europe and the United States and other major economies, weak economic growth, consumer confidence suffered a setback, the demand for silk and other non-essential goods to reduce the demand for silk, resulting in China's silk products exports continued to shrink. 2020–2022, The epidemic led to the contraction of global silk trade, but the rapid recovery of China's export trade and the development of emerging markets to promote the recovery of China's silk products export trade.

In this section, the decomposed causes of China's export fluctuations of silk products to other trading partner countries are estimated. From 2002 to 2022, the total growth of China's exports of silk products to other countries is 69.25 million US dollars. In general, the competitiveness effect promotes the export growth most obviously, and the structural effect and the second-order effect have the inverse pulling effect on the exports of silk products.

Next, we explore the factors affecting the fluctuation of the export of silk products from other trading partner countries to China. From 2002 to 2022, the export growth of silk products from other countries to China was −27.25 million US dollars, of which the total export amount declined by 93.96 million US dollars during the period of 2010–2014, and gradually resumed the growth in the latter two phases. Among the four phases, the structural effect promoted export growth most obviously, while the Competitive effect played a negative pulling role on export growth in general, and the specific decomposition of the model effect is shown below.

Based on the above analysis, we put forward the following policy recommendations from the perspectives of government, enterprises and producers.

First, the government aspect. Governments must establish a favorable macroeconomic environment to support international silk trade. As the world's second-largest economy and a central hub for silk commerce, China should actively advance the Belt and Road Initiative and free trade zone strategies. This entails developing more open and transparent policy frameworks and facilitating access to relevant information channels for member countries' silk industries and import/export businesses. Additionally, optimizing the structure of silk trade is essential. Silk-exporting nations should not only strengthen their comparative advantages in silk product exports but also stay informed about changes in information demand within agricultural markets. Promptly adjusting export product structures can help mitigate the effects of high national market shares and trade barriers.

Second, the enterprise aspect. To enhance international competitiveness and foster export growth in China's silk industry, it is necessary to transition silk raw material exporters into high value-added silk product exporters. This involves bolstering technological innovation in silk fabric production, processing, and design, thereby increasing China's comparative advantages in silk product design and branding. Building on robust product design, enterprises should intensify the brand marketing of pure silk products to establish the international reputation of Chinese silk brands. This will strengthen the position of China's silk industry within the global silk value chain.

Third, the producer aspect. Promoting standardized breeding practices is crucial. Producers should actively comply with the quality inspection standards set by silk enterprises to ensure the stability and consistency of cocoon quality. Establishing stable partnerships with silk companies and signing long-term purchase agreements can help mitigate the impact of market price fluctuations on producers' revenues. Furthermore, producers should adjust their breeding scales and variety structures in accordance with buyers' demands to achieve effective alignment with production requirements.

This study still has certain limitations that could be further expanded upon in the future. First, not all of China's partner countries of silk product trade are analyzed. We selected 29 countries and regions, accounting for over 90% of China's silk product exports, as the research objects. Second, the research data in this work are sourced only from the UN Comtrade database and double-check with other databases. Due to the situation where some countries have not reported trade data, there may be slight discrepancies in the data of the total global silk product exports during the model computation process. Finally, more specific analyses could be conducted at the level of China with individual countries or international organizations in the future.