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Does Agricultural Trade Competitiveness Matter? The Case of the CIS Countries

The paper aims to analyse the comparative advantage patterns of agriculture in the Commonwealth of Independent States. It is relatively understudied in the literature, especially in Central Asia. Agriculture still plays an important role in the region but in a different way than before. Despite that, the majority of the CIS countries are net food importers. Based on the revealed comparative advantage (RCA) index, country-level analysis shows that Moldova, Kyrgyzstan and Armenia have the highest Balassa indices in the region, and Belarus, Ukraine and Azerbaijan are also having some comparative advantage. Product level analysis pointed out that the region’s major agricultural export products groups are cereals. It is important to emphasise that the top five product groups have high, between 3.0-4.4, RCA values. It implies that the regional trade structure is consistent with comparative advantages. However, stability and duration tests show that these are not persistent, since survival chances fell appreciably from 2000-2003 to 2012-2015.


Introduction
The Commonwealth of Independent States (CIS) was established after the collapse of the Soviet Union. The transition from centrally planned to market economies has caused and is still causing difficulties. Agricultural production and trade have been among the most important areas affected by policy changes (Lerman et al, 2004;Csaki and Forgacs, 2008). As agriculture in these countries is still an important sector in many ways, such as agricultural value added or employment, the in-depth analysis of the sector is justified by itself. There is a lack of comprehensive analysis of CIS countries agriculture in the related literature (Kožar et al, 2016).
The time horizon of the analysis covers 16 years, from 2000 to 2015. Right before that, fundamental changes took place and the former Soviet countries faced severe distortions caused by market transition and privatisation (Buchenrieder et al., 2009). From 2000, economic growth has been accelerated, mostly driven by the energy sector, therefore agriculture became relatively less and less important in the Central Asian countries (Mogilevskii and Akramov, 2014). According to Ahrend (2004), it is particularly true for Russia between 1997-2003, where revealed comparative advantage was limited to some raw materials and energy-based products. It is the same for Kazakhstan, where only low value added raw materials showed comparative advantage, and agricultural and food industrial products showed weakening competitive position (Madiyarova et al., 2018). However, this sector still plays an important role in the CIS countries compared to the developed world. For example, in the analysed period, the share of agriculture in the gross domestic product (GDP) decreased from 5.8% to 5.1% in Russia or from 14.5% to 12.1% in Ukraine, but it was only 1.1% in the USA and decreased from 2.5% to 1.4% in the EU (World Bank WDI, 2019). It is worth mentioning that Russia and Ukraine have been able to restructure their agricultural trade flows to new markets by 2001, while other CIS countries mainly traded amongst themselves (Freinkman et al., 2004). It is important to distinguish between CIS and non-CIS countries as the ideal skills are different in the CIS: such as the importance of personal relationships, Russian fluency or lack Several studies using different types of Balassatype indices can be found at country level. One of the OECD's (Organisation for Economic Co-operation and Development) book analysed agricultural comparative advantage at the country level (Liapis, 2011). Among the CIS countries only Kazakhstan and Ukraine had agricultural comparative advantage in 1997 on the aggregated agricultural level. However, this list was even shortened to Ukraine in 2007. Liefert (2002) concluded that Russian agricultural output has comparative disadvantage compared to agricultural input in 1996-1997. He used domestic resource cost (DRC) and social cost-benefit ratio (SCB). Cimpoies (2013) used the Balassa index and found relative trade advantage for Moldova between 2007 and 2011 and 10 positive values out of the 24 agri-food products. The results indicated that Moldova has some advantage in diary, vegetable, tobacco and beverages production. On the other hand, values decreased dramatically for sugar or oilseeds due to old technologies, low quality and inefficiency. Karasova (2016) calculated cluster comparative advantage for different Ukrainian products and cereals and oilseed (mainly sunflower) were found to be highly competitive in 2014. Ishchukova and Smutka (2013) have obtained high and stable Balassa values for Russia in cereals (around 4), oilseeds (almost 3) and tobacco (around 2) sector between 1998 and 2010. It is worth mentioning that regional values showed huge differences, far lower RCA values for the same product in the European Union (EU) than in CIS. One reason is geographical location, because transport cost per unit is higher for these bulk products. In terms of primary and processed products, the former ones resulted in slightly higher values (e.g., 1.2 compared to 0.9 in 2010). These results are in line with Zhemoyda and Gerasymenko (2009 (Amirbekova and Madiyarova, 2015). Khabiti (2008) obtained the same results by using RCA for 1999-2006. Mostly energy and some manufactured goods were competitive. The trade structure of the country was in line with these results, since these products were exported while uncompetitive agricultural goods were imported. Wijnands et al. (2015) carried out a comprehensive study on the competitiveness of CIS and EU agri-food chains and found low competitiveness in almost all CIS food sectors by using EU's major food producers as a benchmark. Based on relative net trade advantage (RTA), the analysed CIS countries showed high values for raw materials, especially for pork and poultry (Russia, Kazakhstan), cereals and oilseeds (Ukraine), potatoes (Ukraine and Belarus) and tomatoes (Belarus in 2013. Regarding processed products, again Ukraine performed the best (strong values for processed products out of cereals, oilseeds) followed by Belarus (above-average values for pork, potatoes and tomatoes based processed products). The overall conclusion of the study was that the major factor behind the competitiveness of CIS agri-food sector was low prices due to cheap resource endowments. It was strengthened by Maryam at al. (2018) results, where natural resource-based Russian products had a comparative advantage. Maslova et al. (2019) used an integrated indicator, including export price and export share to measure the trade performance of the Eurasian Economic Union (Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia). According to their result, the Kazakh and Russian grain production proved to be competitive due to the low domestic prices and production growth.
As a conclusion to the introduction, the major characteristics of the literature review are summarised in Table 1.
The paper focuses on the international trade patterns of the CIS countries in 2000-2015.
The analysed economies are Armenia, Azerbaijan, Belarus, Kazakhstan, Kirgizstan, Moldova, Russia and Ukraine 1 , while Uzbekistan, Tajikistan and Turkmenistan are excluded due to lack of appropriate data. The paper is structured as follows. First, the description of methods and data used is presented, followed by the main characteristics of CIS agriculture and trade. The third part of the paper analyses the comparative advantages of CIS agricultural trade together with their stability and duration. The final part concludes.
[63]  Table 1: Summary of the studies on the regional agricultural comparative advantage.

Materials and methods
The paper employs the seminal work of Balassa (1965). Balassa's measurement of revealed comparative trade advantage is based on the concept of Ricardian trade theory. The original index of revealed comparative advantage defined as follows (Balassa, 1965): where X means exports, i indicates a given country, j is a given product, t is a group of products and n is a group of countries. It follows that revealed comparative advantage (or disadvantage) can be calculated by comparing a given country's export share of its total exports with the export share in total exports of a reference group of countries. Normally "world" is the reference group. If the B index is higher than 1, the given country has a comparative advantage compared to the reference countries or, in contrast, a revealed comparative disadvantage if B is less than 1. RCA is an outstanding tool of descriptive trade statistics and can help to avoid misinterpretation of sectoral or country-level results (Deardorff, 2011).
The Balassa-index is criticised because it usually neglects the different effects of agricultural policies and exhibits asymmetric values. Trade structure is distorted by different state interventions and trade limitations. That is the reason why RCA calculation is based on exports data where this impact is smaller compared to the imports (Bojnec, 2001). The relatively long time series also helps to lower this possible distortion. Moreover, due to the asymmetric value of the B index, it extends from 1 to infinity if a country enjoys a comparative advantage, but in the case of comparative disadvantage, it varies between 0 and 1, which overestimates a sector's relative weight. Therefore, there are many other specifications of the RCA index available, but they are highly correlated (Jámbor and Babu, 2016). All in all, it can be a useful analytical tool in the detection of comparative advantages and predicting its dynamics in a changing environment, such as market changes (Hoang and Tran, 2019).
The stability and durability of the RCA index are also checked in two steps. First, Markov transition probability matrices are calculated and then summarized by using the mobility index, evaluating the mobility across countries and time. Second, following Bojnec and Fertő (2008), a survival function S(t) is estimated by using the non-parametric Kaplan-Meier product limit estimator, which pertains to the product level distribution analysis of the RSCA index. Following

[64]
Does Agricultural Trade Competitiveness Matter? The Case of the CIS Countries Bojnec and Fertő (2008), a sample contains n independent observations (t i ; c i ), where i = 1 → n, and t i is the survival time, c i is the censoring indicator variable with a value of 1 if a failure occurred, e.g., there is no longer a comparative advantage, and 0 otherwise. It is assumed that there are fewer failures than the number of data (m < n). Then, we denote the rank-ordered survival times as t(1) < t(2) < … < t(m). Let n j indicate the risk of failure and let d j denote the number of observed failures at t j time. The Kaplan-Meier estimator of the survival function is then (with the convention that First, we estimate a single survival function by pooling across all products and years and then we also present results by country. Survival of export relationships is also a precondition for trade deepening and export growth, as suggested by Besedes and Prusa (2011), who also give an excellent review on the mathematical specifications of the survival tests. An even more detailed description of survival tests can be found in the book of Cleves et al. (2004) who also use Stata as the authors of this article to make the necessary calculations. As evident from their works, survival tests have a number of assumptions such as the lack of independence or censored values. Moreover, these works also well describe the way Wilcoxon and log-rank tests are run and specified.
The paper employs CIS agricultural trade data of the World Bank World Integrated Trade Solution (WITS) database at HS-6 level between 2000 and 2015 on agricultural products (chapters 1-24, see Annex 1. in the Appendix for the name of the product categories) ending up in 38,770 observations. The paper concentrates on the export side of the revealed comparative advantage index (B or RCA index) to exclude imports, which is more likely to be influenced by agricultural policy interventions.

CIS agriculture and trade
The fundamental production factor of the sector is agricultural land. Its highest share can be found in Kazakhstan (80%), Moldova (75%) and Ukraine (72%), out of which arable land is dominant in Ukraine (79%), Moldova (74%) and Belarus (66%) based on FAO (2019). In order to measure the relevance of agriculture, three indicators were used: value added as a share of GDP (%), the share of agricultural employment (%) and the size of agricultural production (million international dollar 2 ). The following diagram summarises these indicators (Figure 1).
It is evident from the Figure 1 that agriculture 2 International dollar is a theoretical currency used by FAO, World Bank, IMF or UN. It combines the exchange rate, purchasing power parity and international average prices of commodities. It shows the purchasing power that the US dollar had in the United States in the given year. Therefore, it is better for comparisons, but cannot be directly converted to other currencies simply by using exchange rates. plays an important role in the CIS region. This is especially true for Armenia where it is reflected in the high share of agricultural value added in GDP as well as the high share of employment (17.2% and 35.3% respectively). At the other end, Russian agriculture represents only 3.8% of GDP and 7.0% of employment. The case of Azerbaijan should also be highlighted here, where agriculture is a significant employer with 36.4% share, though it contributes to the national GDP only by 6.2%, implying serious labour efficiency problems. The share of agricultural employment was only 4.5% and 1.7% in the EU and USA respectively, while agricultural value added was even lower, only 1.4% (EU) and 1.1% (USA) in the same year (World Bank WDI, 2019). Generally, these indicators show decreasing trend, especially in the developed countries.
Regarding the size of agricultural production, figure  1 suggests that Russia and Ukraine have the largest production potentials, followed by Kazakhstan and Belarus. The sum of the remaining four countries' production is more or less equal to the Belarussian production.
The role of agriculture can also be measured by its share in total exports. It is evident from Table 2 that agriculture gives the most significant share in total exports in Moldova (44% in 2012-2015), followed by Ukraine (32%) and Armenia (26%). In other words, almost half, a third and a quarter of export revenue came from agriculture in these countries, respectively. Besides, it shows an increasing trend in Armenia due to the remarkable expansion of agricultural exports to total exports in the last four years, as well as in Ukraine, where the total exports declined by 30% from 2014 to 2015, while agricultural exports decreased only by 13% (World Bank Wits, 2019). In the case of Ukraine, this process was accelerated by the signed DCFTA 3 resulting 3 Deep and Comprehensive Free Trade Agreement.
in even lower EU trade barriers and increased investment supports after the global crisis (Borodina and Krupin, 2018). On the other hand, agricultural exports gave less than 7% of total exports in 2012-2015 in Russia, Kazakhstan and Azerbaijan. In the case of Russia, the embargo increased the agricultural performance due to the higher, strategic self-sufficiency, preferential agricultural credits and higher producer prices (Kalinina, 2017). This process was further strengthened by the governmental import substitution policy that came into force in 2010 and targeted high self-sufficiency rates like 95% for cereals, 90% for milk and dairy products or 85% for meat and meat products planned to be reached by 2020 (RPA, 2009). In light of these significant impacts, it seems to be very hard for exporters to regain the Russian agri-food markets in the future if at all. However, it should be kept mind in that only a small share of agricultural products are traded, e.g. 16.5% for the cereals (FAO, 2019), which is the major product of the region, meaning that most of the countries feed themselves.
As to CIS agricultural exports, continuous growth can be seen in every country, though to a different extent (Table 3). On the one hand, countries like Azerbaijan and Ukraine increased their agricultural exports more than seven times from 2000-2003 to 2012-2015, while on the other hand, respective growth in Moldova was "only" 2,5 times. However, it should be clearly seen that the magnitude of the Russian and Ukrainian agricultural export is much larger than any other countries in the region.
Analysing the agricultural trade balance gives further insights into the patterns described above (Table 4). First, the CIS region has traditionally been a net importer of agricultural goods. However, due to the notable expansion of Ukrainian exports as well as the huge decline in the Russian agricultural imports, the region achieved a surplus in 2014 and 2015 (1.1 and 9.4 billion USD, respectively).  These processes are part of the international specialisation, where countries try to concentrate on the production of goods in which they have absolute advantage (e.g., land abundant) or relative advantages compared to the other sectors of the economy.
As to agricultural exports by product, cereals were the most important agricultural commodities of the region, providing one-third of its exports (Table 5). Cereals were followed by animal or vegetable fats and oils, dairy products, fish and oilseeds in the period analysed. These product groups gave almost two-thirds of the value of agricultural exports of the region in 2012-2015, suggesting a high and increasing concentration of exports.
In the case of cereals, it should also be kept in mind that the average cereals yield in the region is much lower than in the major producers or trade partners. E.g. it was 5.5 t/ha in the EU, 5.    [67]

Revealed comparative advantages of CIS agriculture
The performance of CIS agriculture in international trade can be measured by calculating the Balassa indices described above. Moldova, Kyrgyzstan and Armenia had the highest Balassa indices in most of the years analysed, while Belarus, Ukraine and Azerbaijan enjoyed some comparative advantage at the same time (Table 6) When analysing comparative advantages by products, further specialisation patterns became available (Table 7). It is apparent that all of the most important product groups identified in Table 5 had a comparative advantage in all periods analysed, though to a different extent. On the one hand, the very high comparative advantages of animal or vegetable fats and oils, as well as oilseeds, seem to have diminished significantly, while that of cereals declined only modestly. On the other hand, the comparative advantages of dairy and fish products have somewhat increased from 2000-2003 to 2012-2015.
Unstable competitive patterns were already justified by the results above. In order to further test its stability, the Markov transition probability matrices were used. It indicates relatively low mobility of the Balassa index for Kazakhstan, Azerbaijan, Russia and Armenia, implying stable patterns of comparative (dis)advantages. Besides these countries, more than 70% of product groups with a comparative advantage remained persistent for Kyrgyzstan, Moldova and Belarus, while the lowest mobility measures pertained to Ukraine, implying highly changing competitive potentials ( Figure 2).
The duration tests also verified the changing structure of agricultural trade-based competitiveness.
As it was described in the methodology section, the Kaplan-Meier estimator of the survival function was run on our panel dataset and the results confirm that in general, the survival times are not persistent over the period analysed (  [68]  across regional countries can be checked by using two non-parametric tests (Wilcoxon and log-rank tests). Results of the tests show that the hypothesis of equality across survivor functions can be rejected at the 1% level of significance, meaning that similarities in the duration of comparative advantage across most important regional agricultural exporters are absent (Table 8).
From a trade policy perspective, it is important to know and to interpret correctly these results. Political and economic regionalisation is creating new trade patterns, acting towards harmonization of member states' trade policies. The Eurasian Customs Union and preferential trade agreements with the EU play a key role in realizing comparative advantages on the agri-food markets. Most of the CIS countries are relying heavily on Russia in their agricultural trade, while some of them were able to diversify their export markets (Kožar et al., 2016). In either case, identifying the changing nature of competitive potentials is key to future success.

Conclusion
The analysis of the CIS region with different versions of Balassa indices is topical and can be found in many studies. One of their common points is that revealed comparative advantages are limited to mostly raw materials due to the resource endowments, especially in Kazakhstan and Russia.
On the country level, high RCA values can be noticed for Belarus, Moldova and Ukraine.
According to the basic indicators (value added, employment or contribution to the total exports), agriculture still plays an important role in the region, especially in Armenia, Kyrgyzstan and Moldova.
As to the share of the sector in total exports,

Does Agricultural Trade Competitiveness Matter? The Case of the CIS Countries
Moldova, Ukraine and Armenia led the way with almost half, third and quarter of every foreign exchange earned via export was coming from agriculture in these countries, respectively. Most of the analysed CIS countries are net importers of agricultural goods, but Belarus became net exporter while Moldova was able to maintain its export surplus during the analysed period. Ukraine is showing continuous and significant growth in agricultural exports, which, strengthened by the huge decline in Russian agricultural imports, transformed the CIS region from a net importer, into a net exporter of agricultural goods. The major agricultural export commodity of the region is undoubtedly cereals, providing almost a third of total agricultural exports. Taking into consideration the relatively low regional yields, it indicates a great potential for further growth in cereals production.
Regarding country-level revealed comparative advantages, Moldova, Kyrgyzstan and Armenia had the highest Balassa indices in the majority of the years analysed for agricultural trade. Belarus, Ukraine and Azerbaijan had some comparative advantage at the same time. These values reflect on the importance of agriculture in the economies of these countries, which is proportionally related to the size of natural resources, like in case of Azerbaijan or Kazakhstan. All of the most important product groups had RCA values above 1 in all periods analysed, implying that the export of agricultural products of the CIS countries corresponds with their revealed comparative advantages. Cereals, animal or vegetable fats and oils, and oilseeds had decreasing values, while dairy products and especially fish were facing increasing revealed comparative advantages. However, it has not turned out to be persistent according to stability and duration tests run on our panel dataset, implying highly changing competitive potentials and fierce regional competition on the agri-food markets. These results are in line with the existing literature, as mostly raw materials have a comparative advantage which generally shows a decreasing trend. Further research might be carried out to analyse and understand the possible reasons behind the results presented above, as well as to compare CIS to other neighbouring countries in this regard. On the agricultural policy level, using revealed comparative advantages can help to better understand the country's export specialisation and international trade performance, which can be the key to future success.