Sustainability Through Diversification and Competitiveness: An Analysis of Global Maize Exports

Abstract

This study aimed to analyze the diversification and competitiveness of corn exports from the United States, Brazil, Argentina, and Ukraine during 2020–2024 through a quantitative, descriptive design using secondary data from Trade Map. Methodologically, it applied the Herfindahl–Hirschman Index (HHI) to measure destination-market concentration and the normalized revealed comparative advantage (NRCA) to assess export specialization and relative competitiveness. The results indicated heterogeneous patterns: the United States experienced rising concentration toward Mexico—heightening vulnerability despite persistent advantages in Japan and Colombia; Brazil maintained low concentration and robust advantages across the Middle East and Asia; Argentina combined favorable diversification with stable advantages in Asia, Africa, and South America, albeit with a mild uptick in concentration by 2024; and Ukraine showed moderate diversification but volatile competitiveness, with structural disadvantages in Türkiye exacerbated by wartime logistics. This study concluded that export sustainability depended jointly on diversification and competitive specialization, with Brazil and Argentina exhibiting the strongest balance.

1. Introduction

1.1. Global Relevance of Maize and Link to Food Security

Maize is a cornerstone of global food systems. It ranks among the world’s most important crops because of its high production volume, its direct role in human diets, and its wide use as an industrial input (e.g., ethanol production and compound feed) [1]. Together with wheat and rice, maize accounts for around 91% of global cereal output [1]. As a result, even small changes in maize supply can have broad effects on food availability and prices. In recent years, global cereal production has increased slightly, mainly due to higher maize harvests and yields, and maize consumption is projected to rise by up to 16% by 2027 [2]. At the same time, maize is a key income source for many exporting countries and an essential pillar of food security for importing nations [3]. In this context, analyzing the diversification and competitiveness of maize exports is not only about trade performance; it is also central to the resilience and sustainability of international agri-food systems.

1.2. Export-Market Concentration and Systemic Vulnerability

At the global level, the maize export market is highly concentrated. Before 2022, four countries (the United States, Brazil, Argentina, and Ukraine) accounted for nearly three quarters of world maize exports [4]. Such a narrow supplier base means that disruptions in production or logistics in any of these countries can quickly spread through international markets, with immediate effects on maize prices and availability [5]. The partial interruption of Ukraine’s exports after the outbreak of war is a recent example of this systemic fragility, raising widespread concern about global cereal supplies [6,7]. In parallel, adverse climatic events—such as droughts and floods in major producing regions—have repeatedly reshaped international maize trade flows [8]. Against this background, a systematic assessment of how diversified the export markets of these leading suppliers are, and how strong their revealed comparative advantage or international competitiveness is, becomes essential for identifying vulnerabilities and potential adjustment margins in the global maize market and, by extension, in the sustainability and resilience of global food systems.

1.3. Regional Demand-Side Context: Asia

Asia is the largest net maize-importing region at the continental level. Several countries face strong demand but insufficient domestic production. Japan, South Korea, and China lead Asia’s maize imports to meet livestock and industrial needs [9,10]. In recent years, China has become one of the world’s main maize importers, sharply increasing its external purchases after 2020 [11]. This rising demand has increased Asia’s reliance on a small group of suppliers: traditionally, the United States and Argentina were the main providers, while since 2021, Ukraine and Brazil have gained market share following sanitary and trade agreements [12]. This situation creates a food and input security challenge for Asia, because logistical disruptions or trade barriers could limit imported maize availability in high-consumption economies. For this reason, organizations such as FAO and ASEAN have emphasized the need to diversify import origins and build strategic reserves in response to volatility in international grain supply [13].

1.4. Regional Context: Europe

Europe shows a dual reality in the maize market. On one side, several European countries are major importers, especially European Union (EU) members that need maize for livestock production (Spain, the Netherlands, Italy, among others). On the other side, Eastern Europe has emerged as an exporting area, with Ukraine (until 2021 linked to the “granary of Europe” initiative) and, within the EU, countries such as Romania, France, and Bulgaria generating export surpluses in favorable seasons [14]. Europe’s dependence on maize imports became clear in 2019, when two-thirds of the maize imported by the Netherlands came from Ukraine [4]. This strong concentration by origin creates vulnerability. The war in Ukraine since 2022 disrupted regular shipments to the EU, pushing European importers to seek alternative supplies (Brazil, the United States, and others) and to rely on solidarity corridors for the remaining Ukrainian grain [15]. As a result, Europe faces the challenge of securing maize supplies by diversifying providers amid geopolitical tensions. In addition, the EU must balance internal dynamics: some members (e.g., France and Romania) increased exports, while deficit regions still require imports [16]. This context has renewed debates within the EU on agricultural policies that support fodder-crop production and on coordination with strategic partners to prevent disruptions in maize supply chains.

1.5. Regional Context: The Americas and Sustainability Tensions

The Americas (especially the Western Hemisphere) form the strongest export hub in global maize trade, although they are not free of risks. North and South America together account for nearly two-thirds of world maize exports, mainly due to the United States, Brazil, and Argentina [17]. This makes the region an essential supplier for importers across all continents. However, this strength also brings exposure: regional climatic shocks—such as droughts in the U.S. Plains or Argentina’s Pampas, or excessive rainfall in Brazil—can quickly reduce global maize supply and push international prices upward [18]. There is also intraregional competition. The United States long dominated the market, but Brazil and Argentina have significantly increased their export share over the last two decades [19], allowing them to compete more strongly in Asia and the Middle East. Another persistent issue is how to sustain maize export growth in a sustainable way. In Brazil and Argentina, agricultural expansion has involved land-use change and potential environmental impacts, while in the United States, the diversion of maize to ethanol can reduce exportable volumes in certain seasons [20]. Thus, the region must balance international competitiveness with sustainability and natural resource management while ensuring stable supply to trade partners.

1.6. Exporter Profiles and Challenges

In summary, Asia, as the largest importer, must manage its vulnerability to supply shocks; Europe combines importer and exporter roles but remains exposed because it relies on non-EU providers (e.g., Ukraine); and the Americas hold primary exporter status while facing climatic and sustainability risks. This situation supports the need for an in-depth analysis of the main exporting countries; to understand how market diversification and comparative advantage shape the resilience of global maize trade.

The following section examines the situation of the four largest maize-exporting countries, focusing on the problems and challenges they face in terms of market diversification and international competitiveness.

The United States has been the world’s leading maize exporter for decades, supported by high production levels (often about one-third of the global total) and efficient logistics infrastructure. It is also the largest maize exporter by export value worldwide [21], contributing approximately 30–40% of global export volumes in recent years [22]. This position creates challenges, including the need to diversify export destinations and strengthen product differentiation. Mexico, Japan, Colombia, South Korea, and China are among the main buyers of U.S. maize, which suggests relatively broad geographic diversification. However, several issues remain. In 2018–2019, trade disputes between the United States and China led to tariffs and other barriers that sharply reduced U.S. maize (and soybean) exports to China, revealing sensitivity to this emerging market [23]. In addition, the United States allocates a large share of its maize crop to domestic ethanol production (around 30–40%); so, changes in energy policy and oil prices can affect exportable supply [24]. A key challenge is to maintain cost-and-quality competitiveness against South American suppliers. In recent years, U.S. exporters have faced a strong dollar (which raises export prices) and, in some cases, lower logistics costs from Brazil to Asian markets through maritime transport routes [25].

Brazil has shifted from being a marginal maize exporter to the world’s second-largest exporter in recent years. Driven by technological advances (such as safrinha production and no-till farming) and the expansion of its agricultural frontier, Brazil has multiplied export volumes over the last decade, reaching external sales of USD 12.150 billion in 2022 (43.4 million tons) [22]. Brazil has built strong competitiveness in maize, supported by relatively low production costs and an exchange rate that has often favored agricultural exports (a depreciated Brazilian real against the U.S. dollar) [26]. However, Brazil faces a challenging mix of logistics constraints and concentration in export markets. Much of its export maize is produced in the Center-West (Mato Grosso) and northern regions, far from ports, which increases inland freight costs. Traditional ports in the Southeast (Santos, Paranaguá) also compete for capacity with soybean exports, creating bottlenecks during peak periods [27]. Although public and private investments have expanded new routes (Northern Arc ports such as Itaqui and Barcarena, and Amazonian waterways) to diversify logistics corridors, this remains an ongoing challenge for sustaining competitiveness [28]. In terms of market diversification, Brazil exports mainly to Asia and the Middle East. Its largest buyers typically include Iran, Japan, Egypt, and Viet Nam [29], and more recently China, which authorized imports of Brazilian maize in 2022 and has become a key market [26]. This customer concentration may increase risk if any large buyer reduces demand due to domestic conditions or stronger competition from lower-priced suppliers. Another critical issue is production instability: despite Brazil’s strong potential, the safrinha crop is vulnerable to climate variability and the early onset of rains, which can increase volatility in export availability [30]. For example, drought in 2018 reduced production sharply and forced Brazil to import maize, while record harvests in 2019 and 2020 boosted exports [31]. This volatility complicates planning for international buyers.

Argentina has long been a major agricultural exporter and ranks third in global maize export volumes [17]. In 2022, it exported around USD 9.222 billion in maize (35.4 million tons), equivalent to roughly three out of every ten tons traded worldwide. Argentina holds a strong position in the maize export market, reflecting a high degree of specialization and competitiveness in this crop [32]. Argentine maize production has achieved rising yields and relatively low costs due to fertile land (the Pampas), technological adoption (genetically modified seeds, efficient machinery), and economies of scale in large farms [33]. However, Argentina faces challenges linked to macroeconomic conditions and domestic policies that can create uncertainty and concentration. First, Argentina applies export taxes (“retenciones”) on maize, often around 12–20% [34]. Combined with foreign exchange controls, these measures can reduce producer incentives and affect supply stability: even if production is efficient, policy uncertainty may weaken margins and make export volumes less predictable [35]. Another issue concerns timing and markets. Argentina ships much of its maize in the months after the main harvest (April–June), which can strain port capacity and market absorption during that period and then reduce availability later in the year [36]. In terms of destinations, Argentina exports to a broad set of countries (Viet Nam, Algeria, Egypt, Malaysia, Peru, among others), but it depends heavily on several North African and Southeast Asian buyers that purchase large volumes. Diversification has been moderate and has also been shaped by quality requirements (e.g., moisture levels and specific standards). Still, improvements in port logistics around Greater Rosario (the main export hub) and the development of non-genetically modified maize for niche markets have helped broaden export offerings [37]. A recent challenge was the severe 2022/23 drought, which reduced the maize harvest by nearly half, sharply lowering export volumes and weakening Argentina’s presence in global markets. This highlights climate vulnerability and the need for better risk management (for example, agricultural insurance remains underdeveloped) [38]. Finally, Argentina faces growing competition from Brazil within Mercosur, as Brazil contests traditional Argentine markets, especially in Southeast Asia. As Brazil expands output, Argentina must work to retain customers through quality and reliable deliveries [39].

Ukraine has consolidated its role as a major global maize exporter, representing around 13–16% of the world market. It has also managed to restore cereal export volumes to near pre-war levels, contributing to global food supply [40]. Fertile black soils and relatively low production costs have supported Ukraine’s strong position in cereals, including maize [32]. However, even before the war, Ukraine faced logistical constraints and regional instability. Black Sea ports (especially Odessa) were the main export channel, creating geopolitical exposure (tensions with Russia, potential naval blockades) and logistical limits (port capacity and reliance on safe-corridor arrangements) [41]. These risks became reality during the war: in 2022 and 2023, Ukraine’s maize exports fell sharply, as shipments were blocked or restricted until the Black Sea Grain Initiative was implemented under international mediation [42].

In addition to the disruption of maritime infrastructure and corridors, the conflict also constrained maize production and the formation of exportable surplus—through reduced access to land, damaged assets, labor displacement and input shortages—which reinforced the observed volatility in Ukraine’s destination profile and competitive position [6,7].

Many key importers (China, Spain, the Netherlands, Egypt) had to turn to alternative suppliers to cover the shortfall. Before the conflict, Ukraine had achieved notable market diversification. Beyond supplying the EU (mainly Spain and the Netherlands), it expanded strongly in China, which between 2019 and 2021 purchased about 30–40% of Ukraine’s maize exports. This concentration increased exposure to political decisions (e.g., China’s temporary purchase limitation in 2015) but also provided a relatively stable outlet while the trade relationship remained favorable [43]. Ukraine also exported to North Africa and the Middle East, adding geographic breadth to its portfolio [17]. Despite this, Ukraine’s central challenge today is how to sustain its export role during the war and in a post-conflict scenario. In the short term, it has relied more on land and river routes through the EU (solidarity corridors), which are costlier and less efficient than maritime shipping. This has raised Ukraine’s relative costs and weakened competitiveness compared with other suppliers [44].

1.7. Study Window (2020–2024) and Shock Selectivity Statement

Accordingly, this study aims to compare patterns of market diversification and international competitiveness in maize exports from the United States, Brazil, Argentina, and Ukraine. The period 2020–2024 was selected because it captures the most recent reconfiguration of maize trade flows under overlapping shocks—most notably the COVID-19 pandemic, extreme climatic events, and the onset of the war between Russia and Ukraine—while also providing a sufficiently long window to observe changes in both diversification and comparative advantage. Importantly, these shocks are not assumed to be uniform across the four exporters. While COVID-19 and extreme weather represent broad disturbances with heterogeneous national manifestations, the Russia–Ukraine war constitutes a highly selective supply-side shock for Ukraine, affecting both maize production capacity and the feasibility/cost of export corridors; for the other exporters, its main transmission channels are indirect, via price shifts, demand reallocation and rerouting dynamics in destination markets [6,7,8].

1.8. Research Gap y Contribution

In a global market marked by strong interdependence and rising exposure to external shocks, assessing export performance only through volume or growth is no longer sufficient. What matters most is to understand, in an integrated way, how diversified export destinations are and how robust competitiveness is across those markets, because both dimensions relate directly to the sustainability and stability of international supply. However, existing empirical evidence often examines diversification and comparative advantage separately, without systematically linking them over a recent period affected by major shocks. To address this gap, the present study provides an updated comparative analysis of maize exports from the leading global suppliers, jointly assessing market concentration (HHI) and normalized revealed comparative advantage (NRCA) for the four main exporters. In doing so, it contributes to the literature on trade, food security, and sustainability by showing how different export structures may amplify or mitigate vulnerabilities in the global maize system.

To improve readability and avoid overlap across sections, the Introduction is organized into thematic sub-sections that (i) establish the context, exporters’ profiles and shock window, and (ii) motivate the analytical choice through a brief review of empirical antecedents and conceptual definitions. Importantly, the Introduction does not present computation procedures: all data, formulas, preprocessing steps, and index-construction decisions are reported exclusively in Section 2 (Methodology).

1.9. Literature Review

The literature contains numerous studies that have jointly applied the Herfindahl–Hirschman Index and revealed comparative advantage, or variants thereof, to analyze competitiveness and export diversification in agri-food products.

One study examined the competitiveness and diversification of global table grape exports using HHI and normalized RCA. It found significant differences across countries; for example, Peru and South Africa exhibited rapid export growth and high RCA in certain markets, but at the cost of a high concentration of destinations (elevated HHI) [45]. Similarly, another study analyzed four South American coffee exporters (Brazil, Colombia, Peru, and Ecuador), concluding that Brazil and Colombia combine moderate diversification with strong comparative advantage, whereas Peru and Ecuador depend on a small number of buyers (high HHI) and display more limited comparative advantages [46]. These studies show how leading Latin American economies in fruits and tropical commodities have implemented market diversification strategies to sustain their competitiveness.

In addition, another study assessed the sustainability of Peru’s blueberry exports using HHI and RCA, finding extraordinary growth in exported volume but a significant concentration in the United States market. Despite expansion into Europe and Asia, nearly half of Peru’s blueberry sales were destined for the United States, reflecting a high HHI and the need to continue diversifying destinations. Nonetheless, Peru’s RCA in blueberries turned out to be among the highest in the world, demonstrating its strong competitiveness in this niche. This duality—high RCA alongside persistently high HHI—is a pattern that can also be observed for some maize exporters, where a highly competitive country still faces the task of diversifying into a broader set of markets [47].

Another contribution analyzed the competitiveness of India’s sorghum exports, using Balassa’s RCA, Markov chain analysis, and HHI to measure market concentration. The findings indicated that India possesses comparative advantage in sorghum (RCA > 1 for most of the study period), but its exports were regionally concentrated, making them unstable. This study recommends diversifying buyers in order to fully capitalize on India’s competitiveness in this minor cereal [48]. In the same vein, Bashimov (2022) evaluated the comparative advantage of Kazakhstan’s cereals (wheat, barley, and maize) and found that Kazakhstan exhibits high RCA in wheat and barley, accompanied by robust competitiveness in those grains, although with a geographical concentration in neighboring markets (Central Asia and China) [49]. Although that study focused on RCA and the related symmetric revealed comparative advantage index, it establishes a precedent for the analysis of countries with strong cereal specialization that, as in the case of Ukrainian or Argentine maize, depend on a limited set of destinations and thus face the need to diversify.

Another cereal-focused investigation examined global competitiveness in wheat, maize, and rice over a 20-year period. Although its main emphasis was on Turkey, the results indicated that Argentina held the highest comparative advantage in maize worldwide, followed closely by Brazil and the United States, whereas Turkey lacked competitiveness in this product. This study combined RCA indices, net trade ratios, and trade balances, although it did not apply HHI directly. Nonetheless, it constitutes a useful antecedent by highlighting the prominent position of South American countries in maize and the importance of domestic conditions for leveraging that advantage (in Turkey’s case, it did not translate into exports due to domestic consumption and local policies) [32].

1.10. Theoretical Background/Conceptual Definitions

Trade resilience refers to an exporter’s capacity to absorb shocks and keep trade flows functioning with limited and temporary losses. In this logic, a higher HHI signals greater exposure because dependence on a few destinations reduces substitution options, while NRCA reflects the strength of revealed specialization that sustains market access. Thus, HHI and NRCA jointly describe how competitiveness and diversification shape resilience. From a sustainable food systems perspective, resilience matters because it supports the stability pillar of food security, alongside availability and access. When maize trade is concentrated, disruptions in a dominant route or buyer can translate into sharper volatility in volumes and prices, weakening stability in importing regions. Diversified, competitive networks improve the capacity to reroute supply and reduce systemic vulnerability.

The HHI–RCA pair has also been applied to processed products and specialized markets. One study analyzed the international market for sparkling wine from 2004 to 2018, calculating both the HHI of market structure and RCA for the main exporters (France, Italy, Spain, etc.). The authors found that France maintained a leading position, with a high market share and elevated RCA, while countries such as Italy and Spain improved their comparative advantage (increasing their revealed exports), but the market remained moderately concentrated among a small group of exporters (high HHI) [50]. Although this is a different sector, the parallels are clear: even in concentrated markets, new participants can improve their revealed competitiveness (as Italy did in sparkling wine, or Brazil in maize), yet the overall structure continues to show dependence on a few key players.

Another study evaluated the structure and competitiveness of the global wine market (generic wine), including an analysis of the duration of comparative advantage over time. It confirmed that the export market for wine exhibits moderate concentration (medium-level HHI) and that “New World” countries (Chile, Australia, etc.) achieved high RCA, although few of these advantages were sustained over long periods [51].

In summary, the existing evidence shows extensive use of concentration metrics (HHI) and revealed competitiveness indicators (RCA) in the analysis of agri-food exports. Researchers have investigated products as diverse as fruits (grapes, blueberries), beverages (wine), grains (wheat, sorghum), and spices (pepper), both in leading and emerging economies. Several common lessons emerge: typically, countries with high RCA tend to dominate markets but face the risk of elevated HHI (concentration), which they must manage; diversification is frequently recommended to strengthen export resilience without losing focus on the core area of competitive specialization.

These prior studies underscore the relevance of the present work, which applies similar tools to the case of maize in four exporting powers. By comparing its results with the existing literature, it becomes possible to determine whether maize follows patterns similar to other commodities or displays specific dynamics of its own. In any case, the accumulated evidence indicates that combining HHI and RCA analysis provides a more comprehensive understanding of a country’s position in the international market: not only whether it is competitive, but also how diversified—and therefore how robust—that competitiveness is in the face of external shocks.

Economic theory suggests that greater export diversification contributes to the stability and resilience of an economy by reducing dependence on a small set of products or markets [52,53]. Conceptually, diversification is linked to the idea of not “selling everything to a single actor or a single market,” thereby mitigating idiosyncratic risks (climate, conflict, regulatory changes) associated with specific destinations [54]. A widely used index for quantifying diversification—or, inversely, export concentration—is the Herfindahl–Hirschman Index (HHI). Originally formulated for measuring industrial concentration, this indicator is defined as the sum of the squared market shares of each element [55]. In the context of exports, the HHI can be calculated for a country’s exports by destination (measuring how concentrated they are in a few markets) [56,57,58].

Although HHI is computed from destination shares and is therefore scale-invariant mechanically, the absolute scale of exports can still affect diversification through the extensive margin. When export programs expand, exporters can amortize fixed market-entry and compliance costs and serve additional destinations, while contractions can force a retreat toward core outlets and raise concentration. Accordingly, HHI movements should be interpreted jointly with the evolution of total export values in each table (which may also reflect price-quantity interactions), rather than as a purely compositional phenomenon [52,53,54,55,56,57,58].

The concept of comparative advantage originates in classical theory (David Ricardo), which posits that each country tends to specialize in the goods it can produce relatively more efficiently [59,60]. However, the empirical measurement of this notion took shape with the revealed comparative advantage (RCA) index proposed by Béla Balassa [61]. Balassa’s formula is built on a simple idea: comparing the relative importance of a product in a country’s exports with the importance of that same product in world exports. First, the share of a specific product in a country’s total exports is calculated. Next, the same share is computed at the global level—that is, how much that product represents within total world exports. Finally, the national share is divided by the global share [62].

The resulting value reflects the export specialization of a country in that product. If the result is greater than one, the country is relatively more specialized in exporting that good than the world average, and this is interpreted as revealed comparative advantage. If the value is below one, the country does not exhibit comparative advantage in that good, since its relative importance is lower than in global trade.

There is also a normalized version of this index. Normalization aims to correct the fact that RCA values may range from zero to infinity, which complicates cross-country and cross-product comparisons [63]. For clarity and consistency, this manuscript uses RCA to denote Balassa’s original revealed comparative advantage index and NRCA to denote its normalized (symmetric) transformation bounded between −1 and +1 [64], computed from the Balassa index as in [63]; therefore, any alternative labels (e.g., IB/BI) are avoided and the empirical results consistently report NRCA values [57].

RCA summarizes multiple dimensions of competitiveness (relative costs, factor endowments, productivity, policies) into a single number based on effective trade outcomes (hence the term “revealed”, as it is derived from observed export/import patterns) [65]. Theoretically, RCA is an ex post measure that reflects competitive performance: a high value suggests that the country has captured a larger share of the world market for that good than would be expected based on its economic size [66,67]. Trade theory indicates that countries with high comparative advantage in a good tend to export it in large volumes and to obtain gains from trade in that sector, although transport costs, subsidies, and policy interventions may modify this simple prediction [68].

Finally, the integration of diversification and revealed competitiveness can be interpreted through trade resilience theory, understood as the capacity of trade systems to absorb shocks and sustain flows with limited losses. In this logic, a higher HHI indicates greater vulnerability due to dependence on a small number of destinations and reduced scope for substitution during disruptions, whereas a positive NRCA reflects a degree of specialization that helps maintain market access and regain participation in key outlets. From the perspective of sustainable food systems, such resilience is essential because it strengthens the stability dimension of food security: when maize trade becomes concentrated and is disrupted, volatility is more readily transmitted to prices and availability in importing regions, while more diversified and competitive networks help buffer these effects.

2. Methodology

The present study focuses on measuring the diversification and international competitiveness of maize exports from the United States, Brazil, Argentina, and Ukraine over the period 2020–2024. Secondary data were obtained from the Trade Map database, which reports export values in U.S. dollars under tariff subheading 100590 Maize (excluding seed for sowing).

Before computing the indices, a data preprocessing stage was applied. Records were standardized to a consistent exporter year structure. Missing values were then assessed: only explicitly reported zeros were treated as true zeros, whereas blank or suppressed entries due to reporting delays, confidentiality, or non-reporting were treated as missing. Data integrity for each exporter year observation was verified by comparing the total reported by Trade Map with the sum across destinations in the extracted dataset.

The procedure consisted, for each exporting country, in calculating a diversification index and a revealed comparative advantage index with respect to its main destination markets for maize exports. To measure diversification, the Herfindahl–Hirschman Index (HHI) was used. The equation is:

$${\sum }_{i=1}^N{Si}^2$$

where “s” represents the share or percentage participation of the analyzed country’s exports across all its destinations, and “N” is the total number of participants.

Theoretically, HHI ranges from 0 to 1 (or from 0 to 10,000 in alternative scaling). Values close to 0 indicate perfect diversification (many markets or products with small and similar shares), whereas values close to 1 (or 10,000) reflect extreme concentration (a single market or product dominates). In applied trade analysis, it is commonly considered that an HHI below 0.10 (or 1000 in the 10,000 scale) reflects a non-concentrated/diversified market, values between 0.10 and 0.18 (1000–1800) indicate moderate concentration, and values above 0.18 (>1800) point to high concentration [58]. These thresholds, adopted for example by the U.S. Department of Justice in competition analysis, are useful for assessing export diversification: a country with a high HHI for its maize export destinations would be dangerously concentrated

To assess export competitiveness, this study operationalizes revealed comparative advantage using the normalized revealed comparative advantage index (NRCA). First, Balassa’s revealed comparative advantage (RCA) is computed for each exporter–destination–year observation; then, RCA is transformed into a bounded, symmetric measure to improve cross-market comparability, yielding NRCA in the interval [−1, +1] [64]. Consistent with the normalization discussed in the specialization literature, NRCA is obtained from the Balassa index via the standard symmetric transformation reported in [63], and the manuscript reports this normalized measure (NRCA) consistently in the empirical section. The formula for RCA is as follows

$$RC{A}_{i,j,d}={\displaystyle \frac{\left(\frac{X_{i,j,d}}{X_{i,\cdot ,d}}\right)}{\left(\frac{X_{\cdot ,j,d}}{X_{\cdot ,\cdot ,d}}\right)}}$$

• i: exporting country under analysis;
• j: product;
• d: destination (import market);
• X_i,j,d: exports of country i of product j to destination d;
• $X_{i,\cdot ,d}$: total exports of country $i$ to destination $d$ (all products);
• $X_{\cdot ,j,d}$: world exports of product $j$ to destination $d$;
• $X_{\cdot ,\cdot ,d}$: total world exports to destination $d$ (all products).

Because competitiveness may vary across importing markets, this study applies a destination-specific (market-conditioned) version of Balassa’s revealed comparative advantage. For each exporter $i$, destination $d$, and year $t$, the index compares the share of maize in the exporter’s sales to that destination $\left(X_{i,p,d,t}/X_{i,\backslash *,d,t}\right)$ with the corresponding share of maize in total world exports to the same destination $\left(X_{w,p,d,t}/X_{w,\backslash *,d,t}\right)$ [61,62]. This conditioning on the importing market holds constant the destination’s demand structure and provides a direct benchmark of whether the exporter supplies maize to that specific market more intensively than the world average. Values greater than 1 indicate revealed comparative advantage in destination $d$, values below 1 indicate disadvantage, and the subsequent symmetric transformation yields NRCA bounded in $\left[-1,+1\right]$ to facilitate comparisons across destinations and time [63,64]. The formula for NRCA is as follows:

$$NRCA={\displaystyle \frac{{RCA}_k^i-1}{{RCA}_k^i+1}}$$

The methodological criterion adopted was one of descriptive objectivity, without inferring causal relationships; the results are presented by comparing the countries with one another and by examining temporal trends in diversification and competitiveness. Finally, all procedures and formulas employed are grounded in recent empirical literature that has applied the combined use of HHI and NRCA to agricultural products, which provides methodological robustness to this study. In this study, the Herfindahl–Hirschman Index was computed using the complete distribution of export destinations reported by Trade Map for each country and year, following the standard HHI formula based on the sum of squared market shares across all importing countries. Accordingly, the “Others” category was not treated as a single aggregated destination for the HHI calculation, which would artificially lower measured concentration. Instead, the index was estimated from the individual destination markets that constitute the full set of importers. However, for purposes of presentation and readability, the results tables explicitly report only the main destinations, while “Others” is shown solely as a descriptive grouping that aggregates the remaining smaller markets—i.e., destinations that are not among the most relevant buyers in each year. In this way, the HHI captures the true concentration/diversification structure, whereas the “Others” label serves an exclusively expository function by representing the set of secondary and emerging markets that complement the export portfolio.

3. Results

Throughout Section 3, NRCA values are interpreted as destination-specific competitiveness measures (market-conditioned revealed advantage), rather than as a single global index aggregated over all importers.

Because the empirical window comprises only five annual observations (2020–2024), the following results should be interpreted as short-horizon patterns that are especially sensitive to the overlapping shocks captured in this period, rather than as evidence of long-run structural change. Consequently, year-to-year movements in destination shares (HHI) and market-conditioned competitiveness (NRCA) may reflect temporary reallocation, price spikes, or disruption-driven rerouting, and should not be extrapolated beyond the observation window without additional years of data.

Because export diversification is often intertwined with export scale, changes in destination concentration should be interpreted jointly with the evolution of total exports reported in Tables. Mechanically, the Herfindahl–Hirschman Index is computed from destination shares and is therefore scale-invariant in its construction; however, expansions or contractions in export scale can affect the extensive margin (the number and stability of served destinations) and the ability to place volumes in smaller markets, which may indirectly reshape concentration dynamics in ways consistent with the diversification–resilience link emphasized in the literature. Accordingly, the descriptive patterns reported for 2020–2024 should be read as the joint outcome of scale-related adjustments and destination reallocation under overlapping shocks, and future work could disentangle price-driven changes in export values from quantity-driven changes to isolate the diversification component more precisely.

3.1. United States

In

Table 1. Destination of United States Corn Exports (in millions of USD).

Importers	2020	2021	2022	2023	2024
Mexico	2706	4732	4955	5433	5670
Japan	1851	3200	3006	2095	2789
Colombia	881	1092	983	1141	1565
Republic of Korea	552	864	515	285	699
Canada	272	663	1332	670	449
Others	3045	8199	7949	3676	2884
Total	9307	18,750	18,741	13,299	14,056

Note. Data taken from International Trade Center (2025) [17].

, the trajectory of destinations for United States corn exports reveals a configuration anchored in a small set of core markets, with Mexico emerging as an increasingly central buyer over the period. Its purchases expand steadily, contrasting with Japan’s more erratic path and confirming Mexico’s role as the structural “anchor” market for this product. Colombia consolidates as a dynamic secondary destination with a clear upward shift toward the end of the period, while the Republic of Korea and Canada show more fragile and discontinuous engagement, with episodes of contraction that interrupt any sustained upward trend. The “Others” category behaves in a distinctly volatile manner, surging to exceptionally high levels in the middle of the period and then shrinking sharply, which indicates that a large fraction of exports is periodically reallocated across a rotating set of smaller or more opportunistic markets rather than being locked into a stable, diversified base.

In Table 1, this configuration suggests an export portfolio that is only partially diversified in geographic terms and that remains heavily exposed to a few key partners. The growing weight of Mexico, together with the persistent relevance—but pronounced volatility—of the “Others” group, implies a dual structure: on one side, a very stable relational core, and on the other, a more tactical periphery that absorbs fluctuations in global demand and price conditions.

In

Table 2. Normalized Revealed Comparative Advantage of United States Corn Exports.

Importers	2020	2021	2022	2023	2024
Mexico	0.32	0.23	0.25	0.44	0.43
Japan	0.63	0.6	0.61	0.61	0.67
Colombia	0.84	0.72	0.68	0.82	0.85
Republic of Korea	0.25	0.1	−0.11	−0.2	0.22
Canada	−0.72	−0.66	−0.42	−0.55	−0.68

Note. Own elaboration.

, the pattern of normalized revealed comparative advantage for United States corn exports reveals a clear segmentation of markets into structurally “strong”, “contested”, and “unfavorable” destinations. Japan and Colombia consistently display values in the comparative advantage range across all years, with only mild fluctuations, indicating a persistent and relatively stable US competitive edge in these two markets. Mexico evolves from a borderline position close to the intra-product trade band at the beginning of the period toward a firmly positive advantage in the most recent years, suggesting an inflection from merely competing alongside other suppliers to a more clearly dominant stance. The Republic of Korea oscillates within the intra-product interval, including slightly negative results mid-period, which points to a market where the US position is neither structurally secured nor structurally excluded. Canada, by contrast, remains in the comparative disadvantage range throughout, with values consistently and markedly negative, indicating a persistent and deep-seated lack of competitive strength in that particular destination. These patterns imply a highly asymmetric geography of US corn competitiveness.

3.2. Brazil

In

Table 3. Destination of Brazil Corn Exports (in millions of USD).

Importers	2020	2021	2022	2023	2024
Egypt	552	667	1070	402	1103
Viet Nam	635	194	486	1134	948
Iran	745	702	2011	829	921
Republic of Korea	423	228	650	866	558
Japan	697	323	1355	1470	513
Others	2734	1983	6583	8764	4010
Total	5786	4098	12,155	13,465	8054

Note. Data taken from International Trade Center (2025) [17].

, the evolution of Brazil’s corn exports by destination over 2020–2024 reveals a sharp expansion in overall export scale in the middle of the period, followed by a partial correction, rather than a linear growth path. The series for individual importers are clearly volatile, with pronounced surges and contractions across years, and no single named market consistently dominating the export portfolio. The most striking structural feature is the growing weight of the residual “Others” category during the export boom, which at its peak accounts for substantially more than half of total shipments before receding to a more balanced split with the top five named markets in the final year. This configuration suggests a destination structure that is not anchored by a small set of traditional buyers but instead is increasingly driven by a broad and fluid set of smaller or emerging markets.

This pattern carries important implications for Brazil’s export risk profile and strategic degrees of freedom in corn. The strong role of “Others” during the boom years is consistent with an ability to quickly reallocate volumes toward a wide range of destinations, which enhances short-term commercial agility and reduces dependency on any single buyer, but also exposes exporters to a more complex and heterogeneous set of regulatory, logistical, and demand conditions. The subsequent normalization in 2024, with total exports retreating from their peak yet remaining well above the earlier trough, points to a structural elevation in Brazil’s corn export base rather than a transient spike. Taken together, the evidence is consistent with a corn export sector that is simultaneously scaling up and diversifying geographically while managing a higher degree of demand volatility that requires sophisticated market intelligence and risk management capabilities.

In

Table 4. Normalized Revealed Comparative Advantage of Brazil’s Corn Exports.

Importers	2020	2021	2022	2023	2024
Egypt	0.84	0.92	0.82	0.63	0.84
Viet Nam	0.82	0.67	0.59	0.77	0.81
Iran	0.92	0.92	0.86	0.8	0.86
Republic of Korea	0.61	0.47	0.48	0.59	0.62
Japan	0.72	0.6	0.7	0.7	0.59

Note. Own elaboration.

, the normalized revealed comparative advantage indices for Brazil’s corn exports across the five main Asian and Middle Eastern markets remain firmly and persistently in the positive comparative-advantage range throughout 2020–2024. All values lie well above the +0.33 threshold, and in several cases approach the upper end of the scale, indicating that corn is systematically over-represented in Brazil’s export basket to these destinations compared with the world pattern. Differences across markets are relatively modest: Iran and Egypt exhibit the strongest and most stable indices, while Viet Nam, Japan, and the Republic of Korea show slightly more intra-period variation but without any year falling out of the advantage zone. Overall, the temporal profile is one of high and resilient structural competitiveness, with only minor fluctuations that suggest adjustments at the margin rather than any erosion of underlying advantage.

This configuration implies that Brazil’s corn exporters occupy a structurally privileged position in these demand centers, turning corn into a core pillar of the bilateral trade relationships rather than a peripheral or opportunistic flow. The combination of high levels and relative stability of the indices suggests that Brazil’s cost, quality, scale, and logistics attributes in corn are consistently valued in these markets, supporting long-term contracts and repeated transactions even through changing global conditions. At the same time, the cross-market differences hint at nuanced opportunities: markets where the index is both high and stable may sustain deeper integration and investment along the supply chain, while those with more variability may call for differentiated commercial strategies to consolidate the advantage. The evidence thus points to a pattern of specialization that strengthens Brazil’s export earnings but may also lock in a strong dependence on corn as a key export product to this group of economies.

3.3. Argentina

In

Table 5. Destination of Argentina Corn Exports (in millions of USD).

Importers	2020	2021	2022	2023	2024
Viet Nam	1231	1525	1361	826	1376
Peru	502	668	829	765	879
Malaysia	421	691	737	563	642
Algeria	520	575	644	602	583
Republic of Korea	431	1168	1273	511	575
Others	2890	4395	3728	2368	2455
Total	5996	9023	8572	5634	6509

Note. Data taken from International Trade Center (2025) [17].

, the trajectory of Argentina’s corn exports reveals a pronounced expansion at the beginning of the period, followed by a contraction and only a partial recovery by the end. The surge in the early years gives way to a marked decline around the mid-period, indicating that the export cycle is not purely trend-driven but sensitive to shocks, whether on the supply or demand side. At the market level, Viet Nam consistently emerges as the leading individual destination, but the prominence of the “Others” category shows that a large share of exports is distributed across a broader set of smaller buyers. The persistence of several recurrent medium-sized destinations—Peru, Malaysia, Algeria and the Republic of Korea—signals a stable core of demand around which more volatile peripheral markets fluctuate.

This configuration suggests a mix of structural opportunity and vulnerability for Argentina’s corn export profile. The presence of multiple relevant destinations, spanning Latin America, Asia and North Africa, is consistent with a reasonably diversified client base that can cushion idiosyncratic shocks in any single market. However, the sharp swings in total export values highlight that the country’s overall exposure remains high to global price and quantity adjustments, and that diversification across buyers has not fully insulated aggregate performance. The large and persistent weight of the “Others” group hints at untapped potential to upgrade some peripheral partners into more stable, strategic relationships, thereby reinforcing bargaining power and reducing dependence on a few major importers and on systemic conditions in world grain markets.

In

Table 6. Normalized Revealed Comparative Advantage of Argentina’s Corn Exports.

Importers	2020	2021	2022	2023	2024
Viet Nam	0.6	0.61	0.63	0.65	0.67
Peru	0.54	0.49	0.56	0.56	0.63
Malaysia	0.61	0.61	0.67	0.68	0.7
Algeria	0.63	0.54	0.61	0.78	0.75
Republic of Korea	0.7	0.71	0.73	0.67	0.70

Note. Own elaboration.

, the normalized revealed comparative advantage indices show a consistently strong and persistent comparative advantage for Argentina’s corn exports in all of the listed destinations. Throughout the period, the indicators for Viet Nam, Peru, Malaysia, Algeria and the Republic of Korea remain clearly within the positive advantage range (above +0.33), with several cases exhibiting a gradual upward drift rather than erosion. The pattern combines moderate short-term fluctuations with a clear long-term tendency towards consolidation of Argentina’s position as a net, structurally competitive supplier. Notably, some markets such as Viet Nam, Malaysia and the Republic of Korea display relatively smooth and high values, whereas Algeria exhibits somewhat more pronounced movements while still remaining firmly in the advantage zone. This configuration implies that Argentina’s competitiveness in corn is not merely episodic or price-driven, but has characteristics of a structural export strength in these specific destinations.

3.4. Ukraine

In

Table 7. Destination of Ukraine Corn Exports (in millions of USD).

Importers	2020	2021	2022	2023	2024
Spain	459	583	657	683	874
Turkey	245	255	296	74	604
China	1383	1873	1056	1081	553
Egypt	508	523	294	458	542
Netherlands	506	539	333	332	509
Others	1762	2103	3283	2222	1874
Total	4864	5875	5919	4850	4956

Note. Data taken from International Trade Center (2025) [17].

, the distribution of Ukraine’s corn exports by destination shows a clear reconfiguration of market weights over the 2020–2024 period, with a shift away from an earlier dominance of China toward a more balanced set of buyers. The overall export trajectory climbs initially, then plateaus, before experiencing a downturn and only a partial recovery by the end of the period, indicating that total corn exports have not fully regained their previous peak. Within that aggregate, the most remarkable changes occur at the destination level: Spain consolidates and progressively enlarges its role, while China’s share declines sharply from an initial leadership position. Türkiye exhibits pronounced volatility, with a severe contraction mid-period followed by a strong rebound, whereas Egypt and the Netherlands move within a more moderate band, showing temporary weakening and subsequent recuperation. The sizeable and fluctuating “Others” category acts as an adjustment margin, absorbing part of the shocks and suggesting that a broad set of secondary markets has been instrumental in cushioning the system against abrupt shifts in major partners.

This evolving destination mix implies that Ukraine’s corn export profile has become less reliant on a single large buyer and more dependent on a combination of European Union markets and a diversified group of smaller partners, even though concentration risk has not disappeared. The reduction in China’s relative importance mitigates the vulnerability associated with overdependence on one extra-regional customer, but it also signals the loss of a formerly central market, which may weigh on long-term growth potential if not offset by deeper penetration elsewhere. The growing role of Spain and the recovery of Egypt and the Netherlands are consistent with an adaptive repositioning toward markets where Ukraine maintains logistical access and established relationships, while the turbulence observed in Türkiye highlights the sensitivity of trade flows to corridor-specific or regulatory disruptions. The behaviour of the “Others” group suggests latent resilience: Ukraine appears capable of redirecting volumes when major outlets falter, although this comes at the cost of greater uncertainty and possibly thinner margins in more competitive or less familiar destinations.

In

Table 8. Normalized Revealed Comparative Advantage of Ukraine’s Corn Exports.

Importers	2020	2021	2022	2023	2024
Spain	0.58	0.6	0.52	0.43	0.43
Türkiye	0.01	−0.17	−0.14	−0.62	0.38
China	0.33	0.46	0.52	0.54	0.31
Egypt	0.52	0.51	0.46	0.52	0.46
Netherlands	0.48	0.47	0.24	0.25	0.36

Note. Own elaboration.

, the normalized revealed comparative advantage indicates that Ukraine maintains a robust and persistent export advantage in corn vis-à-vis Spain and Egypt, while its competitive position in China and the Netherlands has weakened and become more nuanced over time. Spain’s and Egypt’s indices remain consistently in the comparative-advantage range, with only modest fluctuations, which signals a stable alignment between Ukraine’s export specialization and these markets’ demand structures. In contrast, China transitions from the threshold of advantage to values that drift back toward the intra-product trade band, suggesting that Ukraine’s privileged position there has eroded, even if it has not shifted into outright disadvantage. The Netherlands shows a similar softening of advantage, crossing into the intra-product interval for part of the period before a partial recovery that still leaves the index below its earlier highs. Türkiye displays the most volatile profile: it swings from near-neutral or mild disadvantage to a pronounced disadvantage and then abruptly to a renewed advantage, revealing a high sensitivity of that bilateral relationship to changing competitive conditions or to episodic shocks.

3.5. Comparative Analysis of the Indicators

In Figure 1, the four countries display markedly different diversification trajectories. The United States consistently operates in the zone of at least moderate concentration and shifts into clearly high concentration toward the end of the period, indicating a progressive narrowing of its export portfolio. Brazil, in contrast, remains firmly in the diversified range in almost all years, with only a brief move into moderate concentration before returning to an even more dispersed pattern, suggesting both stability and a recent deepening of diversification. Argentina also lies predominantly within the diversified band, with only a mild drift into moderate concentration in the last observation, pointing to a relatively stable but slightly tightening structure. Ukraine alternates between moderate and non-concentrated levels, with pronounced swings that reveal a more volatile pattern of market allocation and a less settled export geography than in the South American peers.

In Figure 2, the comparative heatmap reveals clear cross-country differences in destination-specific competitiveness. Brazil exhibits the strongest and most persistent NRCA levels, particularly in Iran and Egypt, and remains high in Viet Nam, indicating a robust revealed comparative advantage across multiple markets. Argentina maintains a solid but mid-range advantage, relatively stable over time, with stronger performance in the Republic of Korea and a noticeable peak in Algeria around 2023. Ukraine shows a moderate and more volatile pattern: NRCA stays positive in China, Egypt, and Spain, but deteriorates sharply in Türkiye, turning markedly negative in 2023. The United States displays the most uneven profile: it remains consistently strong in Colombia (and moderately positive in Japan, with partial recovery in Mexico after 2022) while showing a persistent disadvantage in Canada and temporary weakness in the Republic of Korea during 2022–2023.

4. Discussion

The findings reveal different patterns of competitiveness and concentration among the major maize exporters. The persistent increase in the Herfindahl–Hirschman Index for the United States points to growing concentration in the Mexican market, suggesting a structural vulnerability similar to that reported by Montes et al. [44] for Peruvian table grape exports, where strong competitiveness coexisted with high destination concentration. Consistent with the observations of Clapp [5] and Lubenets [53], reliance on a single buyer is often linked to lower trade resilience, even when comparative advantages are well established, as seen in Colombia and Japan. It is also important to stress that HHI and NRCA are descriptive metrics; therefore, the interpretations below are presented as associations that coincided with observed changes rather than as proven causal effects.

Brazil remains competitive in its key markets while keeping maize export concentration low. This pattern is consistent with the diversification strategy discussed by Al Roubaier et al. [52] and aligns with the revealed comparative advantage profile reported by Aktaş Çimen [32]. Brazil’s stronger presence in Asia—particularly its expansion toward China—coincided with institutional and policy developments, including the implementation of bilateral phytosanitary protocols and market-access arrangements signed in 2022, which enabled Brazilian maize shipments to China [26]. This context provides a plausible policy channel behind the observed reorientation of destinations.

Argentina displays an intermediate profile. Its normalized revealed comparative advantages consistently exceed 0.6 in major markets, while its HHI generally remains in the low-concentration range, with a mild upward movement in 2024. This pattern resembles the case of Colombian coffee, where strong competitiveness coexisted with moderate diversification [45]. Nevertheless, Argentina’s export performance may be influenced by domestic policy conditions—such as export duties and macroeconomic constraints—which may coincide with changes in the stability and composition of export flows, as discussed by González and Schmidt [34].

Despite some diversification, with an average HHI of 1101, Ukraine’s competitiveness appears less stable and more erratic, especially in Türkiye, where NRCA was negative for several years. This instability coincided with a period in which the literature highlights major logistical and geopolitical disruptions affecting Ukraine’s export capacity (including corridor restrictions and production-side constraints) [6,7,41]. Even under favorable agroecological conditions, exposure to external shocks may be associated with temporary weakening of revealed competitiveness, consistent with Ralte’s discussion of export volatility in cereals [47].

Overall, combining HHI and normalized revealed comparative advantage supports a more complete descriptive assessment of export sustainability. Competitiveness alone is not sufficient to reduce structural risks, and diversification remains critical, as Montes et al. [46] showed in the case of Peruvian blueberries. In this sense, Brazil and Argentina exhibit the most balanced profiles, whereas the United States and Ukraine show greater vulnerability associated with destination concentration and higher exposure to disruptive contexts.

These patterns have direct implications for the sustainability of global maize trade. Given the combined weight of the United States, Brazil, Argentina, and Ukraine, greater destination concentration and reliance on a limited set of buyers increase the system’s vulnerability to climatic, logistical, or geopolitical shocks, with consequences for availability and prices that may undermine food security in importing regions. In parallel, trade-route configuration and the need to reroute shipments in response to disruptions tend to increase transport distances and transit times, thereby raising the supply chain’s carbon footprint. Therefore, market diversification and logistical strengthening not only mitigate commercial risk but also support greater environmental sustainability.

5. Conclusions

This article shows that the sustainability of maize exports cannot be understood only in terms of volumes or isolated competitiveness indicators, but rather as the interaction between export specialization and the degree of market diversification. By jointly applying the Herfindahl–Hirschman Index to destination markets and the Normalized Revealed Comparative Advantage at the importer level for the four main global maize exporters (United States, Brazil, Argentina and Ukraine) over the shock-intensive period 2020–2024, this study provides an integrated, empirically grounded picture of how competitiveness and concentration combine to shape export resilience.

The first contribution of this paper is to document that high competitiveness, as reflected in persistently positive NRCA values, does not automatically translate into a low HHI or into resilient export structures. Brazil and Argentina approximate the “resilient specialization” pattern: they exhibit robust and stable NRCA in their main destinations while keeping their HHI mostly in the non-concentrated or only moderately concentrated range. This configuration shows that it is possible to maintain strong revealed advantages in core markets without incurring critical dependence on a small set of buyers. In contrast, the United States represents a “vulnerable specialization” profile, where high NRCA in key destinations coexists with a progressive and quantifiable increase in concentration towards Mexico, pushing the HHI into high-concentration territory in the final years. Ukraine illustrates a third, “shock-constrained” pattern: its HHI and NRCA move in a highly volatile way across destinations, as logistical and geopolitical disruptions alter both the distribution of markets and the intensity of its revealed advantages, especially in Türkiye and China.

A second contribution lies in showing how geopolitical, climatic and logistical shocks are transmitted into the HHI–NRCA space. The period of 2020–2024 includes overlapping disruptions (COVID-19, extreme weather episodes and the war in Ukraine) that did not affect all exporters symmetrically. The evidence reveals that for Brazil and Argentina, these shocks were largely absorbed through diversified portfolios and stable NRCA in Asia, the Middle East, Africa and Latin America, which limited the rise in their HHI even when export values fluctuated. For the United States, by contrast, the same context coincided with a further concentration of shipments toward Mexico, amplifying exposure to idiosyncratic risks despite maintaining advantages in Japan and Colombia. In Ukraine, the war generated a dual shock: a direct contraction in production and exportable surplus, together with severe corridor constraints (port blockades and rerouting through alternative corridors). This combination translated into abrupt swings in HHI and into temporary erosion or reversal of NRCA in strategic markets, underlining that conflict can reshape both diversification and competitiveness through simultaneous supply and logistics channels [6,7].

These differentiated patterns have direct policy implications for each exporter, derived from the empirical results. For the United States, the documented increase in HHI to high-concentration levels and the centrality of Mexico in the export basket suggest the need for an explicit de-risking strategy: strengthening and consolidating presence in emerging Asian and MENA markets where NRCA is positive or close to the advantage range, and designing trade and quality-differentiation instruments that reduce the relative weight of a single buyer. For Brazil, the combination of low or moderate HHI and systematically high NRCA in Middle Eastern and Asian destinations supports policies that deepen recent investments in logistics (particularly northern ports and multimodal corridors) to lock in its cost and scale advantage and prevent bottlenecks that could weaken its current diversified configuration. In Argentina, the coexistence of strong NRCA in Viet Nam, Peru, Malaysia, Algeria and the Republic of Korea with only mildly rising HHI underscores that the main risk does not stem from the structure of destinations but from macroeconomic and regulatory instability; stabilizing export taxes, foreign-exchange rules and port operations is essential to preserve the relatively balanced pattern revealed in the data. For Ukraine, the observed volatility of both HHI and NRCA across Mediterranean, European and Asian markets points to the priority of consolidating alternative land and river corridors, negotiating long-term agreements with European and MENA buyers, and incorporating contractual risk-management clauses that partially hedge against corridor-specific disruptions.

At the systemic level, the results highlight that global food security depends not only on the number of large maize exporters, but also on how diversified and competitive their market portfolios are. The finding that Brazil and Argentina can sustain high NRCA with relatively low HHI implies that the international system benefits when major suppliers combine specialization with broad client bases, as this facilitates the redirection of flows when one origin or route is affected. Conversely, the United States case shows that even a highly competitive exporter can become a source of systemic vulnerability if its shipments are heavily concentrated in a single partner, while Ukraine’s trajectory reveals how quickly geopolitical shocks can erode both diversification and competitiveness when there are no robust alternative corridors. These insights argue in favor of bi-regional cooperation instruments that explicitly monitor and address concentration risks in staple-grain trade.

Future research could extend this framework in several directions. First, by including additional exporters such as France, Romania or South Africa, it would be possible to analyse substitution dynamics and quantify how easily importers can reconfigure their supplier base when a given origin faces a shock. Second, linking changes in HHI and NRCA to exogenous variables (climate indicators, freight rates, exchange-rate movements and policy shifts) through econometric models would clarify the relative weight of each driver in shaping export sustainability. Third, integrating environmental metrics (e.g., carbon and water footprints, land-use change) into the HHI–NRCA space would allow for the identification of “green diversification” strategies, where resilience and environmental performance are jointly optimized.

This study is not without limitations. Its exclusive reliance on secondary trade data ensures comparability across countries and years, but it excludes qualitative information on private contracts, product differentiation, logistical bottlenecks at the micro level and informal risk-sharing arrangements between exporters and importers. As a result, some concentration or competitiveness risks may be under- or over-estimated, and the proposed typology should be interpreted as a structured approximation rather than as a definitive classification. Despite these constraints, the integrated use of HHI and NRCA over a period of exceptional turbulence provides a novel and empirically grounded lens to understand the sustainability of maize exports, and offers a transparent, replicable framework for policymakers and researchers interested in the intersection between trade concentration, competitiveness and global food security.

A further limitation is the short time horizon (2020–2024). While the period was intentionally chosen to capture an episode of exceptional turbulence, the five-year window restricts the ability to assess whether observed diversification–competitiveness configurations are persistent or merely shock-contingent. Extending the analysis to longer panels (e.g., 10–15 years) and separating pre-shock and shock/post-shock subperiods would improve inference on structural stability, reduce sensitivity to short-run price effects embedded in export values, and strengthen the external validity of the HHI–NRCA patterns reported here.