Competitiveness and Cereal Self-Sufficiency in Western Balkan Countries

Abstract

Crises like the COVID-19 pandemic, the Russian-Ukrainian war, and challenges associated with sustainable development have emphasized the need for local food to increase the food system’s resilience. Therefore, this research analyzes the food self-sufficiency ratio (SSR) and revealed comparative advantage (RCA) of cereals in Western Balkan countries (Serbia, Bosnia and Herzegovina, Montenegro, Albania, and North Macedonia) and compares them with the same indicators for all European countries. The methodological framework of this research examined the food self-sufficiency and macro-level competitiveness for cereals in Western Balkan countries, as well as in Europe. The results of the research showed that all European countries have higher self-sufficiency in cereals (109.12%) and higher revealed comparative advantage (2.21) compared to the group of Western Balkans countries (71.89%; 1.53), which have lower values of the mentioned indicators. The results of econometric modeling for the Western Balkan countries showed that GDP per capita negatively influences the SSR of cereals, and agriculture value added per worker and area harvested under cereals positively influence the SSR of cereals. When it comes to the influence on the RCA of cereals in the Western Balkan region, the critical influence is GDP per capita, political stability, and agriculture value added per worker, all of which positively influence the RCA.

1. Introduction

Multiple ecological, economic, and political risks, crises like COVID-19, and challenges associated with sustainable development have indicated the necessity of greater resilience of agri-food systems [1,2,3]. The combination of the COVID-19 pandemic and the Russian-Ukrainian war led to the most prominent food crisis since World War II. This caused an increase in food insecurity by bringing as many as 1.7 billion people into food insecurity, the level of which is currently at a new peak [4].

The active spread of COVID-19 through the European continent in the first six months of 2020 and the measures for the suppression of COVID-19 resulted in supply, demand, and global production network disruptions. This pandemic affected practically all areas of economic undertakings [5]. Various scientific studies have predicted that if the crisis continues, it will harm consumer incomes, with long-term negative consequences [6,7]. In Central and Eastern European countries, the impact of the COVID-19 pandemic was delayed and weaker than in older European Union (EU) member states. One of the characteristics of the Central and Eastern European countries is that they are specialized in advanced manufacturing and services [8], which makes them more dependent on imported inputs [7,9,10]. According to research by Erokhin & Gao [11], COVID-19 has a more significant influence in upper-middle-income economies than in the least developed countries in the group of 45 analyzed developing countries.

In addition to COVID-19, the war between Russia and Ukraine has had a significant negative impact on food systems and food security. The war between Russia and Ukraine caused changes in global trade, production, and consumption, affecting prices [7]. Crises destabilized the 2023 and 2024 crop cycles, leaving 205 million people with acute food insecurity in 45 countries worldwide [8]. Fertilizer prices have tripled since early 2020 and remain volatile, significantly affecting supply and food production in many less developed countries. Also, the Farm to Fork Strategy published in May 2020 aims to increase the EU food system’s social, environmental, and economic sustainability by covering all stakeholders (farmers, consumers, retailers, and processors). To accelerate the transition called for by the Farm to Fork Strategy, the European Commission proposed to develop a legislative framework for sustainable food systems (SFSs) before the end of 2023 [12]. One of the primary goals of this strategy is to decrease the usage of chemical inputs, especially mineral fertilizers.

One of the essential food sources in the world is cereals, contributing 50 percent of calories and as much as 54 percent in developing countries [9]. Certain Western Balkan countries depend on Russian and Ukrainian exports of cereals, vegetable oils, and fertilizers and are exposed to the indirect impact of disruptions in global trade [13,14]. The countries of the Western Balkan are exposed to the risk of international shocks since the EU is their leading partner in exports and imports [7]. From 2017 to 2021, 81 and 83.1% of Western Balkan exports were exported to the EU, and Western Balkan countries imported between 50.9 and 63.9% of their goods from the EU [15]. For the agriculture of Western Balkans countries in recent years, it is characteristic that there has been a decline in farmland, aging, decline of the rural population, migration from rural areas, and land abandonment [16]. So, although Western Balkan countries use almost half of the utilized agricultural area (UAA) for agriculture, while the EU uses 38.4% of its territory, agriculture productivity in Western Balkan countries lags behind that of the EU [13]. The Russia-Ukraine war created negative terms-of-trade shocks and supply chain disruptions, which affected the agricultural sector of the Western Balkans. Adverse effects were most evident in commodity and energy trade disruption, increased food and input prices, and inflationary pressures.

The crisis, therefore, emphasized the need for food self-sufficiency in all countries. According to the FAO (1998), “the concept of food self-sufficiency represents the extent to which a country can meet its food needs from its own domestic production” [17]. The concept of food self-sufficiency refers to the ability of a household, region, or country to meet consumption needs from its production instead of imports [18,19]. The need for sustainable, healthy, and local food that would increase the resilience of the food system in the EU is also emphasized in the European Farm to Fork Strategy. International organizations also emphasize the need to strengthen the resilience of food systems and reduce their ecological and carbon footprint [20]. As stated in the European Commission’s report [21], food supply is not an issue in Europe today since it is mainly self-sufficient in vital agricultural products. The EU is a major exporter of wheat and barley and is largely self-sufficient in animal products, including dairy and meat. However, there are significant differences between EU countries regarding food supply.

The current crises have highlighted long-term structural deficiencies in the global food system, which is inadequate for ending poverty and food insecurity [19,22]. Although the importance of food systems has been emphasized during recent years at several international summits, the UN Food Systems Summit in September 2021, the UN Climate Change Conference (COP26) in November 2021, and the Nutrition for Growth Summit in December 2021 [23], food systems management has been primarily marginalized [24]. Therefore, there needs to be an increasing focus on food systems management, which is crucial in determining whether people have an adequate, nutritious, and sustainable diet [24].

As stated by Jambor & Babu, one of the main reasons for food insecurity is low productivity and the agricultural sector’s competitiveness [25]. In Europe, the EU enlargement process has led to significant heterogeneity, which has affected the development and competitiveness of the EU. This process has also led to large differences between EU countries. The EU has increased competitiveness by creating world markets representing an effective platform for organizing joint learning and improving local practices among countries. However, the EU single market has increased competition between countries and significant differences between the older countries and the newly integrated Eastern European countries [26]. Also, the Common Agricultural Policy (CAP) of the EU and high amounts of support have enabled EU member states to increase competitiveness and self-sufficiency. The policy of the Western Balkan countries is directed towards harmonizing with the EU’s requirements. However, there have been numerous changes in the market for agricultural and food products over a long time, which have had implications for their competitiveness [27]. The competitive position of Western Balkan countries in world markets depends significantly on access to global resources and participation in international trade [28].

Therefore, this research aims to analyze self-sufficiency and revealed comparative advantage for cereals in European countries, focusing on Western Balkan countries, which is important in crisis situations. The paper is organized so that the first part is the introduction. The second part presents an overview of the literature on the theoretical basis of food self-sufficiency and revealed comparative advantage. The research methodology used in the paper is described in the third part, and the fourth part includes a presentation of the results. The fifth part is a discussion of the results, while the conclusion consists of the implications of the crisis on food self-sufficiency and revealed comparative advantage in European countries with a particular focus on Western Balkan countries.

2. Theoretical Background

The global agri-food system is characterized by a complex network of trade flows, and current crises have emphasized the importance of countries’ food self-sufficiency and competitiveness.

Food self-sufficiency indicates the region’s degree of dependence on net imports. It is expressed as the relationship between domestic agricultural production and consumption. National food self-sufficiency is both a key indicator of food availability and a fundamental pillar of food security [27]. Although there are arguments by economists that a focus on self-sufficiency can threaten food security because it ignores the efficiency gains that arise from international trade, food self-sufficiency is the primary goal of agricultural and food policies [29]. As indicators of food self-sufficiency, self-sufficiency ratios (SSRs) are standard indicators in agricultural and economic statistics expressed in terms of energy, protein, and physical or monetary quantities [30,31].

Most of the research has analyzed food self-sufficiency by calculating self-sufficiency ratios for different product groups and regions. Sylla et al. applied the Metropolitan Foodshed and Self-Sufficiency Scenario (MFSS) model methodology to estimate the level of potential food self-sufficiency of functional urban areas (FUAs) [32]. Their approach was applied to nine city regions from different European countries: Wroclaw (PL), Ostend (BE), Berlin (DE), Avignon (FR), Copenhagen (DK), Bari (IT), Brasov (RO), Athens (EL), Barcelona (ES). Their results show that vegetarian and local food demand could be satisfied in the first five FUAs of these city regions.

Kaufmann et al. analyzed three EU SSR dimensions (livestock products, cropland products, and primary agricultural biomass) for 226 regions (NUTS2). Their results showed that 14% of EU regions were self-sufficient, and 26% were import-dependent in all three dimensions. The results showed that 54% of regions were self-sufficient in ruminant livestock products and 39% in monogastric livestock products. Also, 21% of the region depends on the import of crops and, simultaneously, is self-sufficient or a net exporter of livestock products [33]. Brankov et al. calculated the coefficient of food self-sufficiency for Southeast European countries. Their results showed that Southeast Europe has a high level of food self-sufficiency [18]. Đorđević et al. presented food production in Serbia, and the results showed that Serbia has been self-sufficient throughout its history. Also, the results showed that Serbia can improve its food self-sufficiency [34].

Bogdanov et al. analyzed the level of food self-sufficiency in the Western Balkans. The results showed that all Western Balkan countries are net importers of food, except Serbia [35]. Brankov & Matkovski calculated the coefficient of self-sufficiency for different food groups over 14 years [13]. Their results showed that in the pre-crisis period, the Western Balkans achieved satisfactory food self-sufficiency. In EU countries, there is significant diversity regarding cereal self-sufficiency. A similar situation exists in Western Balkan countries, where there is also a difference in the degree of self-sufficiency in cereals. Over the years, the highest degree of self-sufficiency has been recorded in Serbia [17].

If global cereal production is observed, China is self-sufficient in cereals, except for soybeans, whose self-sufficiency has declined significantly [36]. However, the biggest threat to self-sufficiency in China will be rapid industrialization and urbanization due to requirements for more cultivated land [37]. According to Kumar, cereals continue to be the most important food in India and are also the cheapest source of energy and protein. Cereal prices are important in providing food and nutritional security in India [38]. According to the latest World Bank report, the national cereal availability gap is anticipated to be more than 2 million tons in Africa. This is based on estimates of domestic production and anticipated formal wheat imports through Port Sudan [39].

Other authors have examined changes in competitiveness in international trade in global or regional markets, as it is a multidimensional concept that can be analyzed at different levels [40]. Competitiveness is a multidimensional concept that can be assessed for different time horizons and entity levels [41]. Most often, studies on the competitiveness of the agri-food sector use comparative advantage indicators.

The competitive position of the agri-food sector of the EU countries was estimated by Bojnec & Fertő, who analyzed the export competitiveness of agri-food products on international markets for 23 countries [42]. Their results showed that most of them have comparative advantages. Also, they analyzed drivers of the duration of comparative advantages of agri-food products in the EU, and the results showed that higher trade costs negatively affected the duration of comparative advantages [42]. On the other hand, the size of the country, level of economic development, diversification of exports, and being a new EU member state positively affected comparative advantages. The results for the Western Balkan countries showed that countries joining the EU as “new” member states had a positive impact on EU accession and trade intensification. In contrast, almost all countries had a decrease in the comparative advantages of agri-food products after accession [42].

Matkovski et al. analyzed agri-food competitiveness in Southeast Europe and its determinants. The results showed that Southeast European countries have comparative advantages in exporting these products to the global market (except Albania) [27]. The competitiveness of the EU food industry was explored by Wijnands et al., who measured the competitiveness of eight subsectors, and their results showed that the EU food industry’s competitiveness is weak [43]. Wijnands & Verhoog analyzed the competitiveness of the EU food industry, which was benchmarked against the USA, Australia, Brazil, and Canada. They used a set of economic and trade indicators, and the results showed that the overall competitiveness performance of the EU28 remained weak: the three economic indicators weakened, and the trade indicators improved in 2008–2012 compared to 2003–2007 [44].

Simionescu et al. extended the Cobb–Douglas function by including other competitiveness factors in panel data for the EU28 countries during the period 2004–2018 [26]. Their results showed that human and physical capital, FDI, and R&D expenditure explain GDP per capita variation. Kittova et al. compared the readiness of particular Western Balkan countries for EU membership based on accession progress assessment and international economic position assessment. Their results showed that North Macedonia and Montenegro have the best international economic positions among the Western Balkan countries, while Serbia is among the worst rated [45]. There are differences between EU countries when it comes to revealed comparative advantages (RCAs) for cereals. Agri-food products with low added value, such as cereals, can significantly contribute to reducing the EU’s level of competitiveness. Also, there are differences between the countries of the Western Balkans when it comes to RCA for cereals. Serbia stands out as a country that has comparative advantages in cereals, especially in the markets of the other Western Balkan countries [46]. The remaining countries of the Western Balkans do not have comparative advantages in cereals [27].

When it comes to the combined analysis of competitiveness, where SSR and RCA are simultaneously analyzed using the example of a sector, the literature is scarce, but there are specific examples. For instance, Sarica analyzed the competitiveness and self-sufficiency of the broiler sector in Turkey and compared it with those of selected countries. These two methods allowed him to provide a clearer picture and recommendations for this sector. With this research related to the Western Balkans, the gap in the literature should be filled, and the competitiveness of cereals should be viewed from several angles.

Given the challenges associated with COVID-19 and the war between Russia and Ukraine, better agribusiness management must be incorporated. As stated by the Shovkun-Zablotska, crisis conditions require improvement in the structure of agricultural production with the participation of institutions and representatives of large, medium, and small businesses. During the implementation of these changes, the needs of food enterprises, export opportunities, and the self-sufficiency of the domestic market also need to be taken into account. In the event of war, when it is necessary to develop new structures of agricultural production, it is necessary to consider the distance of the region from the combat zone and military risks to the production of agricultural enterprises [47].

3. Materials and Methods

This research encompassed Western Balkan countries: Serbia, Bosnia and Herzegovina, Montenegro, Albania, and North Macedonia. To compare all European countries, estimations were conducted for 39 European countries (5 countries of the Western Balkans, 27 countries of the European Union, Belarus, Norway, the Republic of Moldova, the Russian Federation, Switzerland, Ukraine, and the United Kingdom). The data were taken from the FAOSTAT database [48] and the World Bank [49] for the period from 2010 to 2020. This research’s methodological framework examined cereal self-sufficiency and macro-level competitiveness in European countries, focusing on Western Balkan countries.

In the first part of the paper, the key indicator of the concept of food self-sufficiency, cereal self-sufficiency ratio (SSRcereals), was calculated, and in the second part, the revealed comparative advantage (RCA) was assessed.

The cereal self-sufficiency ratio (SSRcereals) in our paper was calculated by dividing the total domestic food output and the total supply in a particular country each year, using the following equitation:

SSRcereals = Pcereals/Dcereals × 100%

(1)

where SSRcereals is the rate of cereal self-sufficiency, Pcereals is the total domestic cereal output, and Dcereals is the total supply.

According to the FAO calculation method, the total supply represents [50]:

Dcereals = Pcereals − Ecereals + Zcereals + Icereals

(2)

where Ecereals is cereal exports, Zcereals is changes in stocks (decrease or increase), and Icereals are cereal imports.

The food self-sufficiency ratio shows if the country’s domestic food supply can satisfy domestic consumption. The countries with SSR < 100 produce less food than they consume, SSR = 100 means that the domestic food supply can satisfy domestic consumption, and the countries with SSR > 100 produce more food than they consume [13].

In the second part of the paper, we calculated the competitiveness of the European countries and the sample of only Western Balkan countries via the index of revealed comparative advantages. Competitiveness refers to the ability of a nation to produce and distribute goods in the international economy when competing with goods and services produced in other countries in a way that provides a rising standard of living [41]. In the literature, the traditional RCA index is used for the analysis of comparative advantages [38] at the macro level through tendencies in foreign trade flows.

The RCA index was first proposed by Balassa in 1965, and it is an important metric for quantifying the relative strength of a country in producing a product in relation to its trading partners. RCA is defined as [51] follows:

$${\mathrm{R}\mathrm{C}\mathrm{A}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{\frac{{\mathrm{X}}_{\mathrm{i}\mathrm{j}}}{{\mathrm{X}}_{\mathrm{i}\mathrm{t}}}}{\frac{{\mathrm{X}}_{\mathrm{n}\mathrm{j}}}{{\mathrm{X}}_{\mathrm{n}\mathrm{t}}}}}$$

(3)

where X—export; i—country; j—section or division (total cereals—according to FAOstat; t—total export (total merchandise trade according to FAOstat); n—group of exporting countries. If RCA > 1, then there are comparative advantages. Comparative advantages are strong when RCA > 3; RCA index values between 2 and 3 indicate significant comparative advantages, while RCA values of 1 and 2 indicate satisfactory comparative advantages [27].

It is necessary to point out that the RCA method is often criticized in the literature. As the main limiting factors in the literature, it is noted that this index summarizes comparative advantages in a certain country for a certain product in a certain period of time, and if this number obtained is higher (lower) than a certain neutral value, comparative advantages (disadvantage) exist. Because of this, it is necessary to keep in mind that the RCA is not symmetrical (problem of overestimation of the relative weight of sector), there are problems with small countries that often show significantly favorable values, and there is a problem of additivity (when summing up two or more regions). Various other specifications of this method have been derived (for example, relative import advantage, relative trade advantage and relative competitiveness, revealed symmetric comparative advantage, and normalized revealed comparative advantage) [25]. The literature suggests the use of different indices, but there is no single point of view that is the most favorable for the analysis, so Balassa’s measure remains a reference in the literature [52].

In the next step of the analysis, an attempt was made to find a connection between the RCA and the SSR, both in the countries of the Western Balkans and for all European countries, using a correlation matrix. Namely, when the levels of self-sufficiency in cereal production are examined alongside export potential on the world market, clearer conclusions can be drawn for the analyzed countries.

In the last step, an analysis of the impact of different factors on SSRcereals and RCAcereals, such as GDP per capita, area harvested under cereals, rural population, political stability, temperature change, and agriculture value added per worker, was conducted. Two forms of this model were estimated. In Model I, the dependent variable is SSR for cereals, while in Model II, the dependent variable is RCA for cereals. Both forms of the model were estimated for both analyzed groups of countries (Western Balkans and Europe). A description of the variables with expected relationships are shown in

Table 1. Description of the variables with the expected relationship.

Variable	Description	Source	Expected Relationship
GDP per capita (GDP)	GDP per capita (constant 2010 USD)	World Bank [49]	negative
Area harvested cereals (AHC)	Area harvested cereals (1000 tons)	FAOSTAT [48]	positive
Rural population (RP)	Rural population (1000 persons)	FAOSTAT [48]	negative
Political stability (PS)	Political stability and absence of violence/terrorism (index)	FAOSTAT [48]	positive
Temperature change (T)	Temperature change (Meteorological year °C)	FAOSTAT [48]	negative
Agriculture value added per worker (AVA)	Agriculture value added per worker (US $)	FAOSTAT [48]	positive

Source: Authors’ own research.

.

The basic form of the model is as follows:

Y_it = α + β₁lnGDP_it + β₂lnAHC_it + β₃lnRP_it + β₄lnPS_it + β₅lnT_it + β₆lnPS_it + μ_i + λ_t + u_it

(4)

where

Y_it—represents the SSRcereals (Model I) or RCAcereals (Model II) of the country i in the period t;

GDP_it—represents GDP per capita of the country i in the period t;

AHC_it—represents area harvested under cereals of the country i in the period t;

RP_it—represents rural population of the country i in the period t;

PS_it—represents political stability and absence of violence/terrorism of the country i in the period t;

T_it—represents temperature change of the country i in the period t;

AVA_it—represents agriculture value added per worker of the country i in the period t;

μ_i—represents individual effects in the panel model;

λ_t—represents temporal effects in the panel model that vary over time;

u_it—represents the stochastic variable of the model.

The selection of the optimal econometric model was performed using the standard procedure for panel data. The first step was the estimation of the model using the random effects (REs) model, and after examining the results of the Breusch–Pagan test (which shows whether the RE or the ordinary least squares (OLS) model is preferred), as well as the Hausman test (which selects between the RE and fixed effects (FE) models), model selection was performed. OLS ignores individual differences. In the RE model, the individual effects have a stochastic character, whereas in the FE model, effects are comprehended as fixed parameters. The models were also tested for heteroskedasticity, multicollinearity, and autocorrelation, and in case of inadequacy of the model, in some cases, the weighted least squares (WLS) assessment was used. In the WLS method, during the process of minimizing the sum of the square residuals, residuals with higher absolute values receive less weight and vice versa. The econometric modeling procedure was carried out using Gretl software (Gretl version 1.9.4).

4. Results and Discussion

4.1. Cereal Performances

Figure 1 shows the share of cereal production in the total world production in the period from 2010 to 2021. The highest production of cereals was recorded in China (20.71%). After China, the highest cereal production was recorded in the United States of America (15.20%), while India is in third place (10.87%) in terms of cereal production. The European Union (27) is fourth when it comes to cereal production with 10.11%, while the Western Balkans has a share of 0.43% in in total world cereal production.

Figure 2 shows the average production of cereals in European and Western Balkan countries. In the countries of the Western Balkans, corn is produced the most, with an average production of 1,584,903 t, followed by wheat, with an average production of 662,861 t. In second place is barley, with an average production of 114,610 t. Oats (27,181 t), rice (11,972 t), rye (7175 t), and sorghum (2677 t) are produced significantly less. When it comes to cereal production in Europe, the situation is somewhat different compared to a sample of only Western Balkan countries. In Europe, wheat is produced the most at 131,803,198 t, corn production is in second place at 66,765,772 t, and barley production is in third place at 51,872,564 t. Rye (8,001,231 t), oats (7,342,932 t), rice (2,954,228 t), and sorghum (782,916 t) are produced less in Europe.

Table 2. Cereal trade in tons.

Western Balkans
Imports
	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Albania	363,622.15	376,540.65	343,262.70	342,837.30	338,419.85	320,397.81	308,242.99	254,129.78	306,612.80	247,369.30	343,876.07	315,698.30
Bosnia and Herzegovina	579,379.60	529,334.60	501,144.20	530,869.75	671,869.68	673,104.96	752,012.71	706,496.15	599,951.35	547,599.68	541,446.76	442,485.80
Montenegro	29,698.20	43,451.85	48,131.25	44,913.50	56,844.00	60,490.41	54,358.54	43,779.47	49,094.26	44,817.61	44,988.75	35,538.84
North Macedonia	104,044.00	141,698.20	186,378.65	116,198.75	137,047.54	163,123.72	131,143.13	163,840.46	139,932.86	154,271.69	159,832.31	137,654.78
Serbia	17,260.10	52,369.90	42,165.90	46,428.20	26,850.89	22,761.52	16,861.79	15,590.43	22,294.35	25,087.87	32,348.67	25,897.31
Europe
Imports
	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Total Europe	62,608,418.05	63,506,435.1	63,990,232.35	62,487,146.1	72,362,542.87	73,635,589.18	77,997,729.86	83,606,392.64	86,818,091.84	87,752,061.13	85,065,292.64	82,439,293.79
Western Balkans
Exports
	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Albania	36.70	145.50	42.00	162.10		48.47	778.70					46.28
Bosnia and Herzegovina	67,835.00	4965.00	5215.00	45,838.00	84,385.04	77,904.59	129,019.52	59,585.73	69,283.13	24,482.06	43,545.67	48,794.59
Montenegro	100.00	103.00	2.55	46.60	18.25	60.12	5.14	0.42	7.32	0.39	399.51	139.53
North Macedonia	6668.40	11,557.75	10,512.95	11,567.15	9596.04	13,558.76	15,430.33	26,557.36	44,932.82	36,814.75	29,419.70	48,763.20
Serbia	2,110,619.85	1,965,313.45	2,488,277.65	1,950,498.25	2,811,318.92	2,622,692.93	2,937,925.08	2,050,975.26	2,497,247.95	3,508,298.27	4,219,106.44	3,501,485.88
Europe
Exports
	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Total Europe	80,378,597.55	72,740,546.05	74,613,668.70	87,754,096.80	93,190,105.79	102,860,696.84	99,539,285.78	91,164,000.53	86,080,524.05	95,098,716.90	107,841,998.62	102,942,129.26

Source: authors’ own research based on FAOSTAT [48].

shows the foreign trade exchange of cereals in the period from 2010 to 2021. The countries of the Western Balkans show significant variations when it comes to imports of cereals. The largest imports were recorded in Bosnia and Herzegovina, while the smallest imports of cereals were recorded in Serbia. Larger imports were also recorded in Albania, which is in second place in terms of cereal imports. Montenegro has import values similar to Serbia, while North Macedonia has slightly higher imports than Montenegro. Across all European countries in the observed period from 2010, imports grew until 2019, after which a slight decline was noted, which is largely a consequence of the crisis.

Regarding cereal exports, Serbia emerged as a country that, in the observed period, recorded significantly higher volumes of exports compared to other countries of the Western Balkans. The remaining countries of the Western Balkans (Albania, Bosnia and Herzegovina, Montenegro, and North Macedonia) performed similarly in the observed period, with minimum quantities of cereal imports. Larger amounts of exports were recorded in European countries in relation to imports, and over the years, especially since 2015, there has been an increase in the export of cereals, with smaller fluctuations over the observed years.

When it comes to the self-sufficiency ratio and revealed comparative advantage, there are significant differences between European countries compared to a sample of only Western Balkan countries (Figure 3). In the analyzed period, European countries had a higher average self-sufficiency ratio, which was 109.12%. The obtained results indicate self-sufficiency in European countries when it comes to cereals (SSR > 100). On the other hand, the countries of the Western Balkans have an average self-sufficiency ratio of 71.89% (SSR < 100), which means that they do not have food self-sufficiency in cereals. The situation is similar when it comes to the index of revealed comparative advantage (RCA), which is higher in European countries and amounts to 2.21, while in the countries of the Western Balkans, that value is 1.53.

In

Table 3. SSR in the Western Balkans.

	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Albania	60.03	60.90	62.23	62.99	62.22	61.56	62.54	63.24	61.69	59.36	63.69
Bosnia and Herzegovina	60.75	64.25	57.41	68.69	60.50	62.34	77.26	58.73	77.89	72.69	78.77
Montenegro	12.40	12.03	12.23	14.71	5.52	4.86	4.96	4.93	4.86	4.93	4.86
North Macedonia	75.80	74.60	64.79	76.78	82.44	64.97	78.75	64.09	78.48	75.07	78.14
Serbia	125.15	131.77	186.31	129.10	166.58	129.65	168.22	140.46	136.56	160.48	159.89

Source: authors’ own research based on FAOSTAT [48].

, the differences in SSR in the countries of the Western Balkans are shown. The results show that the highest SSR in cereals was recorded in Serbia. The values in all years are greater than 100%, which indicates self-sufficiency in cereals. The remaining countries of the Western Balkans (Albania, Bosnia and Herzegovina, Montenegro, and North Macedonia) have significantly lower recorded SSR values since the values are lower than 100%. Albania, Bosnia and Herzegovina, and North Macedonia have approximately similar values when it comes to the SSR of cereals, with SSR values in the observed years ranging from 50–80%. Of all the countries of the Western Balkans, Montenegro has the lowest SSR, which in the observed period has values of less than 20%.

Table 4. RCA in the Western Balkans.

	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Albania	0.01	0.01	0.01	0.01	0.00	0.02	0.01	0.01	0.01	0.01	0.01
Bosnia and Herzegovina	0.73	0.12	0.11	0.44	0.77	0.70	1.01	0.41	0.36	0.17	0.31
Montenegro	0.01	0.01	0.00	0.01	0.00	0.01	0.00	0.00	0.00	0.00	0.06
North Macedonia	0.22	0.36	0.35	0.27	0.14	0.18	0.20	0.21	0.27	0.22	0.22
Serbia	8.04	8.68	10.86	6.12	7.48	6.68	6.32	4.16	4.71	5.88	7.44

Source: authors’ own research based on FAOSTAT [48].

shows the movement of RCA in the period from 2010 to 2020 in the countries of the Western Balkans. The highest RCA was recorded in Serbia, which has RCA values greater than 4. The higher RCA in Serbia can be attributed to the greater available agricultural resources, used agricultural areas, and arable land per capita, which creates the largest export surpluses [50]. The remaining countries of the Western Balkans have significantly lower RCA values. The RCA values in Bosnia and Herzegovina, Montenegro, North Macedonia, and Albania are lower than 1. One of the reasons for lower RCA values in these countries can be found in poor export performance per hectare and employment in agriculture, as well as inadequate responses to improving competitiveness [27].

Correlation analysis (

Table 5. Correlation analysis of SSR and RCA.

Western Balkans
SSR	RCA
1.0000	0.8352	SSR
	1.0000	RCA
Europe
SSR	RCA
1.0000	0.6305	SSR
	1.0000	RCA

Source: authors’ own research based on FAOSTAT [48].

) indicates a strong correlation between these two indicators. The connection between these indices in the countries of the Western Balkans is 0.8352 and is stronger than when all European countries are analyzed (connection 0.6305). As previously mentioned, it is clear that Serbia stands out from all the countries of the Western Balkans, as it is the only one with a favorable SSR for cereals and the only one that achieves comparative advantages in exporting to the international market. In terms of self-sufficiency, Serbia ranks 11th in Europe, while in terms of comparative advantages, it is in 4th place. When looking at the connection between RCA and SSR, it can be concluded that all analyzed countries that have comparative advantages in the export of grain are also self-sufficient, with the exception of Greece, which achieves slight comparative advantages but is not self-sufficient. On the other hand, a high SSR does not necessarily mean comparative advantages in the export of cereals, which can be seen in the example of several European countries. For example, Slovakia and the Czech Republic have a self-sufficiency index of over 150% for cereals, but they do not achieve comparative advantages. Additionally, countries with a favorable index of self-sufficiency but no comparative advantages are Poland, Denmark, Germany, and Finland. The reason for such tendencies in the mentioned EU countries is that these countries use a large part of the produced cereals for livestock production, which is at a high level in these countries; cereals are not seen as having export potential, so they do not achieve comparative advantages.

4.2. Estimation of Model of SSR

Within Model I, we first observed the influence of selected independent variables on SSR in European countries, and then we observed the influence of independent variables on SSR in the sample of only Western Balkan countries. The same was done for Model II, where we first observed the influence of selected independent variables on RCA in European countries, and then we observed the influence of independent variables on RCA in the sample of only Western Balkans countries.

In this paper, the selection of the appropriate panel model among the RE, FE, and OLS was based on the following tests: Breusch–Pagan and the Hausman test statistic (Appendix A).

Table 6. Estimation of Model I.

Model I (Dependent Variable—SSR)
Europe (WLS)	Coefficient	Std. Error	t-Statistic	p-Value
Constant	3.11105	0.245144	12.69	<0.0001
GDP	−0.0122801	0.0342338	−0.3587	0.7201
AHC	0.539054	0.0165142	32.64	<0.0001
RP	−0.382931	0.0186592	−20.52	<0.0001
PS	0.163526	0.0246396	6.637	<0.0001
T	0.0550525	0.0286829	1.919	0.0559
AVA	−0.274813	0.0319558	−8.600	<0.0001
Sum squared resid	272.8472	S.E. of regression	0.952087
R-squared	0.812044	Adjusted R-squared	0.808297
F(6, 301)	216.7396	p-value(F)	4.3 × 10−106
Log-likelihood	−418.3701	Akaike criterion	850.7403
Schwarz criterion	876.8510	Hannan–Quinn	861.1805
Sum squared resid	272.8472	S.E. of regression	0.952087
Mean dependent var	4.377944	S.D. dependent var	0.925921
Sum squared resid	78.31678	S.E. of regression	0.510087
Western Balkans (OLS)	Coefficient	Std. Error	t-Statistic	p-Value
Constant	2.01069	3.19781	0.6288	0.5390
GDP	−1.84106	0.577031	−3.191	0.0061
AHC	0.386412	0.217088	1.780	0.0953
RP	0.633644	0.480758	1.318	0.2073
PS	0.0544208	0.0859474	0.6332	0.5361
T	−0.0480473	0.348696	−0.1378	0.8922
AVA	0.989907	0.336127	2.945	0.0100
Mean dependent var	3.478504	S.D. dependent var	1.313333
Sum squared resid	0.964988	S.E. of regression	0.253639
R-squared	0.973359	Adjusted R-squared	0.962702
F(6, 15)	91.33980	p-value(F)	5.99 × 10−11
Log-likelihood	3.176855	Akaike criterion	7.646290
Schwarz criterion	15.28359	Hannan–Quinn	9.445407
rho	0.342223	Durbin–Watson	0.976615

Source: the authors’ calculations.

shows the model estimation results for the SSR of cereals in Europe and the sample of only Western Balkan countries. When choosing a model for Europe, the RE model was performed first, in which the Breusch–Pagan test showed that the use of the RE model was preferred, while the Hausman test showed that the FE was preferred. In the FE model, an autocorrelation of the first order was recorded (Durbin–Watson (DW) =1.104438, which is less than dL = 1.692). Therefore, the use of the WLS model is suggested.

For the selection of models for the Western Balkans, the same steps were applied. First, the RE model was performed, and the Breusch–Pagan test showed that the OLS model is preferred. The estimation of the OLS model showed that there is no autocorrelation according to the Durbin–Watson test. So, the OLS model was performed for the Western Balkans.

Model I included the following variables as a set of independent variables: GDP per capita, area harvested under cereals, rural population, political stability, temperature change, and agriculture value added per worker.

The model estimation for Europe showed that the adjusted R-squared value of 0.808297 indicates that the independent variables explain approximately 80.83% of the total variation of the dependent variable, which indicates a high explanatory power of the SSR of cereals. The results of the research showed that the area harvested under cereals, rural population, political stability, and agriculture value added per worker have significant contributions to the explanation of the SSR of cereals. Area harvested under cereals and political stability have a positive and significant influence on the SSR of cereals in European countries. On the other hand, rural population and agriculture value added per worker have a negative and significant influence on the SSR of cereals in European countries. A smaller percentage of the explanation of the SSR of cereals was provided by temperature changes, while GDP per capita has no significant impact on the SSR of cereals in European countries.

For the Western Balkans, the model estimation showed that the independent variables have a high explanation of 96.27% (adjusted R-square of 0.962702) of the total variation of the SSR of cereals. According to estimated results, GDP per capita has a negative and significant influence on the SSR of cereals in the Western Balkans. On the other hand, agriculture value added per worker has a significant and positive influence on the SSR of cereals. Area harvested under cereals has a smaller and positive influence on an explanation of the SSR of cereals. Rural population, political stability, and temperature change have shown that they have no influence on the explanation of the SSR of cereals in the countries of the Western Balkans.

4.3. Estimation of Model of RCA

Table 7. Estimation of Model II.

Model II (Dependent Variable—RCA)
Europe (WLS)	Coefficient	Std. Error	t-Statistic	p-Value
Constant	1.13481	0.551467	2.058	0.0405
GDP	−0.657222	0.0793026	−8.288	<0.0001
AHC	1.14989	0.0445620	25.80	<0.0001
RP	−0.770508	0.0394248	−19.54	<0.0001
PS	0.371447	0.0437512	8.490	<0.0001
AVA	−0.498387	0.0815821	−6.109	<0.0001
Sum squared resid	299.0182	S.E. of regression	0.986915
R-squared	0.898338	Adjusted R-squared	0.896682
F(5. 307)	542.5618	p-value(F)	4.9 × 10−150
Log-likelihood	−436.9759	Akaike criterion	885.9518
Schwarz criterion	908.4291	Hannan–Quinn	894.9343
Mean dependent var	−1.233499	S.D. dependent var	2.427709
Sum squared resid	812.2563	S.E. of regression	1.626587
Western Balkans (WLS)	Coefficient	Std. Error	t-Statistic	p-Value
Constant	−107.802	9.12280	−11.82	<0.0001
GDP	4.50075	1.85936	2.421	0.0278
AHC	0.359689	1.19118	0.3020	0.7666
RP	4.21141	2.53877	1.659	0.1166
PS	0.406763	0.151545	2.684	0.0163
AVA	3.75229	1.36329	2.752	0.0142
Sum squared resid	19.84189	S.E. of regression	1.113606
R-squared	0.969385	Adjusted R-squared	0.959818
F(5. 16)	101.3238	p-value(F)	1.57 × 10−11
Log-likelihood	−30.08093	Akaike criterion	72.16185
Schwarz criterion	78.70811	Hannan–Quinn	73.70396
Mean dependent var	−3.592668	S.D. dependent var	3.192690
Sum squared resid	20.20789	S.E. of regression	1.123830

Source: the authors’ calculations.

shows the model estimation results for RCA in European countries and the sample of only Western Balkan countries. When choosing a model for Europe, the RE model was first performed, in which the Breusch–Pagan test showed that the use of the RE model was preferred, while the Hausman test showed that the FE was preferred. In the FE model, an autocorrelation of the first order was recorded (Durbin–Watson (DW = 1.774953, which is greater than dU = 1.760) (Appendix A). Therefore, the use of the WLS model is suggested.

For the analyses of RCA in the Western Balkans, we performed the RE model and the Breusch–Pagan test showed that the OLS model is preferred. The estimation of the OLS model showed the presence of autocorrelation (DW = 1.701745, which is greater than dU = 1.691) (Appendix A). Therefore, for the model estimation we used WLS.

In Model II, we excluded the influence of temperature change and included the following independent variables: GDP per capita, area harvested under cereals, rural population, political stability, and agriculture value added per worker.

The research results showed that the model estimation for Europe has the adjusted R-squared value of 0.896682, which indicates that the independent variables explain approximately 89.66% of the total variation in the RCA, which indicates a high explanatory power. The results of the research showed that GDP per capita, area harvested under cereals, rural population, political stability, and agriculture value added per worker significantly contribute to the explanation of RCA. Area harvested under cereals and political stability have positive and significant contributions to RCA in European countries. On the other hand, GDP per capita, rural population, and agriculture value added per worker have a negative and significant influence on RCA in European countries.

The model estimation for the Western Balkans showed an adjusted R-square of 0.962702, which has a high explanatory power because it explains 96.27% of the total variation in the RCA. The results of the research showed that GDP per capita, political stability, and agriculture value added per worker significantly and positively contributed to the explanation of the RCA variable. Area harvested under cereals and rural population were shown to have no influence on the explanation of RCA in the countries of the Western Balkans.

5. Discussion

The results of food self-sufficiency levels and revealed comparative advantages analysis showed that there are significant differences between European countries and the sample of only countries of the Western Balkans. Also, there are significant differences regarding the influence of independent variables on the SSR of cereals.

The results of the research showed that GDP per capita has a significant and negative influence on the SSR of cereals in the Western Balkan countries, while GDP per capita has no significant impact on the SSR of cereals in European countries. The negative impact can be explained by the fact that in lower-income countries, most of their earnings go to the consumption of basic foodstuffs such as cereals. Thus, as income rises in lower-income countries, their food expenditure rises, and consumption patterns appear to be trying to catch up to the composition of higher-income countries [16,53].

The area harvested under cereals has a positive and significant influence on the SSR of cereals in European countries, while its influence is positive but less significant on the SSR of cereals in countries of the Western Balkans. A positive effect is expected because, with an increase in the area under cereals, it is possible to increase production and ensure food self-sufficiency levels for cereals. The importance of agricultural land was also confirmed in the papers by Sylla et al. [32] and Brankov & Matkovski [13]. In Europe in 2022/23, cereal production is projected at 265.6 million t, which represents a 6.9% decrease compared to the 5-year average, mostly due to drought conditions. According to the European Commission [21], poor harvest combined with high cereal prices and an expected decrease in meat production is expected to reduce the use of cereals for feed by 2.9% year-on-year. On the other hand, food use is expected to increase slightly by +0.8% year-on-year. Europe’s imports of cereals could increase by 44% compared to a 5-year average to 35 million t due to an increase in imports from Ukraine, while cereal exports are expected to remain high (+4.7% above the 5-year average) [21].

The results showed that the rural population has a negative and significant influence on the SSR of cereals in European countries, but the influence of the rural population is positive and not significant in Western Balkan countries. The positive influence of the rural population in Western Balkan countries has been confirmed in Brankov & Matkovski’s research [13]. It is characteristic of less developed countries, such as the countries of the Western Balkans, that they rely more on rural populations in agriculture because they have outdated machinery with traditional production technology. Political stability has a positive and significant influence on the SSR of cereals in European countries, while political stability has shown that it has no influence on the explanation of the SSR of cereals in the countries of the Western Balkans. A positive effect is also expected since greater political stability guarantees greater stability in global patterns of trade, production, and consumption. The positive effect of political stability was confirmed in the paper by Brankov et al. [18].

Temperature changes have shown that they explain the SSR of cereals in a smaller percentage in European countries, while they have no influence on the explanation of the SSR of cereals in the countries of the Western Balkans. The effect of temperature change on SSR was also confirmed in the paper by Brankov & Matkovski [13]. Additionally, global climate change is a critical factor that influences cereal production. Variability in the climate has severe implications for agriculture regarding its influence on cereal yields directly by heat and water stresses, crop damage, low productivity, and high production costs. In many countries, there is a lack of concern for climate change, which is often justified by the uncertainties of projections. So, it is important to raise awareness of the future risks and benefits that can be derived from developing national strategies for adaptation and mitigation of climate change. Some possible technical solutions are changing the planting calendar, irrigation, and nutrient management, improving crop varieties, and expanding the agricultural areas [54].

Agriculture value added per worker has a negative and significant influence on the SSR of cereals in European countries, while in the sample of only countries of the Western Balkans, agriculture value added per worker has a significant and positive influence on the SSR of cereals. The opposite effect of agriculture value added per worker is also expected since, in European countries, agriculture relies more on new technologies and less on the workforce. This is not the case when it comes to the countries of the Western Balkans, which rely more on the workforce in agriculture.

The results indicate that European countries have self-sufficiency in cereals (SSR > 100), while the average self-sufficiency ratio of 71.89% (SSR < 100) in Western Balkan countries indicates that Western Balkan countries do not have food self-sufficiency in cereals. However, between European countries, there are significant differences in the SSR for cereals. The highest SSR for cereals (SSR > 140) in the period from 2010 to 2020 was recorded in Bulgaria, Latvia, Lithuania, and Ukraine. Also, between the countries of the Western Balkans, there are significant differences when it comes to the SSR for cereals. The results showed that Serbia stands out when it comes to self-sufficiency in cereals because the values in all years are greater than 100%, which indicates self-sufficiency in cereals. The remaining countries of the Western Balkans have significantly lower recorded SSR values. The self-sufficiency in cereals in European countries was confirmed in the paper by Kaufmann et al. [33], while self-sufficiency in cereals in Western Balkan countries was confirmed in the papers by Brankov et al., Brankov & Matkovski, Đorđević et al., and Bogdanov et al. [13,18,34].

Similar to the SSR model, the assessment of the model for RCA for the countries of Europe and the sample of Western Balkan countries showed that there are significant differences regarding the influence of independent variables on RCA. The results of the research showed that GDP per capita has a significant impact on RCA; however, a positive effect of GDP per capita was recorded in the model for the countries of Europe, while a negative effect was recorded in the models for the countries of the Western Balkans. The opposite sign for GDP in European countries and Western Balkan countries is also expected because usually, with economic growth, a country can increase the purchase of food from abroad.

Area harvested under cereals has a positive and significant contribution to RCA in European countries; however, area harvested under cereals has a positive but not significant influence on RCA in the Western Balkans. Similar to SSR, the rural population has a negative and significant influence on the SSR of cereals in European countries, but the influence of the rural population is positive and not significant in Western Balkan countries. Political stability has a positive and significant contribution to RCA in European countries; however, political stability does not have a significant influence on RCA in Western Balkan countries. Agriculture value added per worker has a negative and significant influence on RCA in European countries and no influence on RCA in Western Balkan countries. The negative influence of agricultural value added per worker is expected because developed countries use new technologies, less labor force, and knowledge in economic activities that generate higher value-added goods, thus increasing the chances of success in this competitive world economy [55].

The results of the research showed that Europe has a higher index of revealed comparative advantage (RCA), 2.21, while in the countries of the Western Balkans, that value is 1.53. As stated by Matkovski et al., the Western Balkans have relatively poor export performance per hectare [27]. The higher index of revealed comparative advantage in European countries is in line with previous research by Matkovski et al. and Bojnec & Fertő [27,42]. It is also important to emphasize that there are significant differences between the countries of Europe in terms of RCA. The highest RCA for cereals in the period from 2010 to 2020 was recorded in Ukraine, while the lowest RCA was recorded in Albania, Iceland, and Montenegro. Also, there are significant differences between the Western Balkan countries in RCA. The highest RCA was recorded in Serbia, which has RCA values greater than 4, while the remaining countries of the Western Balkans (Bosnia and Herzegovina, Montenegro, North Macedonia, and Albania) have significantly lower RCA values (lower than 1). RCA values in Bosnia and Herzegovina, Montenegro, North Macedonia, and Albania are lower than 1.

Bilateral and multilateral agreements significantly influence the dynamics of trade in agricultural products. The agricultural sector, compared to other sectors, is more complicated because it is linked not only to economic growth but also to food security, especially in the least developed countries [55]. Today, at the global level, there are challenges to transforming agri-food systems to ensure affordable and healthy food [56]. The EU has numerous preferential trade agreements with other regional groupings around the world, which greatly facilitates trade. Thus, regional food systems are associated with a number of positive aspects, such as close relationships between consumers and producers, healthy diets due to the availability of fresh and nutritious food, and a small carbon footprint caused by short transport distances [33]. However, as stated by Kinnunen et al. [57], only one-third of the global population can supply locally. This indicates that food self-sufficiency can only be achieved through trade with other regions, countries, and continents, which is of key importance for global food security [33]. The importance of short food supply chains as a vision of a sustainable agri-food system was particularly pointed out by the current crisis and market risks (local or regional food systems) [58].

Regional cooperation needs to be strengthened to allow for the seamless flow of agri-food products between countries. Also, the emphasis must be on strengthening the food supply by ensuring that producers are supported and can adapt to a changing climate through the implementation of sustainable practices. These sustainable practices include improving land management, improving energy use, and reducing pollution, food waste, and post-harvest losses [59].

6. Conclusions

The results of the research showed the following:

• European countries have higher self-sufficiency in cereals and a higher index of revealed comparative advantage compared to the sample of Western Balkan countries, which have lower values for the mentioned indicators.
• The Western Balkan region, as well as Europe, is composed of very different countries, from exporters to importers, and they differ from each other in terms of self-sufficiency in cereals and the index of revealed comparative advantage. The results showed that Serbia stands out when it comes to self-sufficiency in cereals, and the index of revealed comparative advantage in comparison to other Western Balkan countries.
• The results of the correlation analysis between SSR and RCA for cereals show a stronger positive relationship in the sample of Western Balkan countries than is the case for all analyzed European countries. The reason for the somewhat weaker correlation when analyzing all European countries is that in some more developed countries of the European Union, cereals are not an important export product because they are used as an input in livestock production that is developed in those countries.
• The results of econometric modeling for the countries of the Western Balkans showed that GDP per capita has a negative influence on the SSR of cereals, and agriculture value added per worker and area harvested under cereals have a positive influence on the SSR of cereals. When it comes to the influence of cereals on the RCA in the Western Balkan region, the key influences are GDP per capita, political stability, and agriculture value added per worker, all of which have a positive influence on RCA.

The research results indicate levels of self-sufficiency and revealed comparative advantage for cereals in European countries and the sample of Western Balkan countries, which is significant from macroeconomic as well as microeconomic perspectives. The results of this research have certain policy implications. Analysis of self-sufficiency and revealed comparative advantage for cereals could be useful for agricultural policymakers in creating policies that would adopt more effective support for the agricultural and food sector, which would contribute to favoring domestic producers and increasing competitiveness on the international market. In order to maintain a satisfactory level of food security, it is crucial to create appropriate food policies, strategies, and programs that include a set of principles that affect food production, food consumption and nutrition, use of resources in the agricultural sector, domestic and international food markets, food security, and conditions in by which people live in rural areas. Since food security is significantly influenced by the created food policies, when creating them, it is necessary to consider the impact of numerous microeconomic and macroeconomic factors that affect the level of food security. Research of this type is of great importance for agri-food producers since the production and trade of cereals in the world is growing significantly, especially because cereals provide more than half of the total daily energy value of meals in the world.

The conducted research has limitations because some factors, such as food prices, investments, trade policies, and resource utilization, that can affect cereal self-sufficiency and revealed comparative advantage have not been included in the statistical analysis. Further research papers will need to improve the coverage and quality of the data and analysis. Therefore, future studies will be directed toward a more detailed analysis of factors influencing cereal self-sufficiency and competitiveness in European countries.