**2. Materials and Methods**

The study is performed in the case of the five countries of Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) and China in 2000–2018 (Figure 1).

**Figure 1.** Countries of Central Asia and China. Source: Authors' modification of [46].

The data are obtained from the United Nations Conference on Trade and Development (UNCTAD) [26]. SITC Commodity classification is used. The total volume of agricultural trade in both exports and imports is generalized as SITC "All food items" (SITC 0 + 1 + 22 + 4). The array of the products is built along 37 positions and include major food and agricultural commodities traded between China and the countries of Central Asia. To assess the advantages of the Central Asian economies in agricultural trade, the study employs the five-stage approach.

#### *2.1. Stage 1: Balassa Index*

Classical trade theory assumes that the pattern of international trade is determined by comparative advantage [47]. In the attempts to measure the advantages, the scholars have used various techniques, including multivariate data analysis (factor analysis, cluster analysis, and structural equation modeling), trade data on exports and imports [48,49], and descriptive approaches [50,51]. One of the commonly accepted methods to identify the advantages of a country on the global market is the Balassa index of revealed comparative advantage (RCA) [52]. It has been used by many researchers for the identification of the changes in comparative advantages worldwide [53–55]. Porter [56] implemented the RCA index to identify strong sectoral clusters in international trade. Konstantakopoulou and Skintzi [57] used it to discover comparative advantages of the EU countries by sectors and by major product categories, Amiti [58] analyzed the specialization patterns in Europe. In the case of China, Hinloopen and van Marrewijk [59] analyzed the dynamics of comparative advantage as measured by export shares, Chun [60] investigated comparative advantage by studying the correlations between the cost of labor and foreign trade, Shuai and Wang [61] made an empirical analysis of the comparative advantages and complementarity of agricultural trade, while He [62] modified RCA index to the study of the dynamics of agricultural trade patterns.

There are also abundant studies of Central Asia's comparative advantages. One of the earliest and most comprehensive ones is that by Lücke and Rothert [63] who identified the advantages of Kazakhstan, Kyrgyzstan, Tajikistan, and Uzbekistan based on the information about factor prices and transport costs, historical production patterns, and trends in the geographical and product composition of Central Asian external and interregional trade. The study, however, aimed at the suggestion of broad guidelines for the identification of potentially competitive export sectors rather than focused on the determination of comparative advantages at the industry or product level. In the case of Kazakhstan's trade, Bozduman and Erkan [64] analyzed the competitiveness of export products on a sectoral basis and found that the country was competitive in export of hydrocarbons, ores, and other raw material intensive product groups, but excluded agricultural trade from their analysis. Falkowski [65] also excluded agricultural products from the study and approached to the investigation of long-term comparative advantages of Kazakhstan and Kyrgyzstan as the members of the Eurasian Economic Union (EAEU) from a perspective of the Organization for Economic Cooperation and Development (OECD) classification of manufacturing industries based on their technology intensity.

To address the existing shortcomings, at the first stage, the authors employ the Balassa method to reveal the comparative advantage of Central Asian countries in trade in agricultural products:

$$\text{RCA} = \begin{array}{c} \frac{\text{X}\_{ij}}{\text{X}\_{it}} \\ \frac{\text{X}\_{nj}}{\text{X}\_{nt}} \end{array} = \begin{array}{c} \frac{\text{X}\_{ij}}{\text{X}\_{nj}} \\ \frac{\text{X}\_{it}}{\text{X}\_{nt}} \end{array} \tag{1}$$

where *RCA* = revealed comparative advantage; *X* = export; *i* = country; *j* = product group (domestic market); *t* = product group (international market); *n* = group of countries.

According to the Balassa method, a country *i* specializes in the export of a product *j* if the market share of a product *j* is above average or, equivalently, if the weight of a product *j* in the total export of a country *i* is higher than the weight of a product *j* in the export of the reference area [66]. Stated differently, *RCAij* > 1 means a country *i* enjoys a comparative advantage in trade in a product *j*, while *RCAij* < 1 means a comparative disadvantage.

When applying the Balassa index to the measuring of the competitiveness of the products, industries, or countries, a difference between comparative advantage and competitiveness must be considered. The OECD [67] defines competitiveness as an economy's ability to compete fairly and successfully in international goods and services markets, which, as a result, leads to a steady rise in the living standards in the long term. According to Dunmore [68], comparative advantage is a statement about international specialization and trade patterns that would arise in an undistorted

world based on the differences in relative efficiencies between countries in the absence of trade. Competitiveness, on the contrary, is a characteristic of a country on the real global market distorted by various government policies. Dynamic character of competitive advantages under the conditions of an open economy inversely to comparative advantages is stressed by Weresa [69], Carbaugh [70], Collignon and Esposito [71], and Fagerberg [72].

Accordingly, the measurement of competitiveness should include the assessment of the dynamics of comparative advantages influenced by trade policies. Due to the difference between comparative and competitive advantages, the Balassa index is not that effective in the identification of competitive positions of particular products, since it allows to identify revealed comparative advantages rather than to determine the underlying sources of such advantages [66]. Siggel [73], Costinot et al. [74], and Hinloopen and van Marrewijk [75] point out that although the Balassa method allows detecting the advantage of a country in foreign trade as compared to other economies and the world as a whole, it fails to reveal the reasons of such advantage. It does not let divide comparative advantages on natural (for example, increased competitiveness due to technological innovations or improved efficiency) and acquired ones (for instance, state subsidies or alike distorting administrative measures). Understanding the sources of comparative advantages is crucial for such sectors as agricultural production, where government interventions commonly distort market patterns and affect competitiveness. Specifically, a government may provide support for domestic agricultural producers and exporters, subsidize export, increase or decrease customs tariffs, and employ non-tariff regulations to support the competitiveness of particular agricultural products on the external market [76]. In such cases, RCA shows an advantage, but actual competitiveness is distorted [77].

In the region of Central Asia, the employment of RCA in the measurement of competitiveness results in a very rough picture of the advantages due to the following reasons. First, the static nature of the index does not allow us to consider market disturbances and react to the changes in the equilibrium in the long run [77]. In the case of Central Asian economies which are still in a state of transition from distorted (during the Soviet times) and fluctuant (in the 1990s and 2000s) economic environments, low flexibility of the index is a shortcoming. Second, RCA can be inconsistent or misleading for the countries of the region as for smaller economies it demonstrates stronger advantages than there really are [78,79].
