1. Introduction
International coffee trade, as part of the structural dynamics of South America’s agricultural economies, has historically been shaped by a high dependency on a limited number of importing markets. Statistics show that exports from this region accounted for an average of 28% of global coffee exports between 2020 and 2023, led by Brazil, Colombia, and Peru [
1]. Rather than fostering a resilient trade structure, this dependency has heightened the external vulnerability of exporting countries in the face of demand fluctuations, geopolitical instability, technical trade barriers, or abrupt changes in global consumer preferences—all while confronting the significant impacts of climate change on production [
2]. Recent studies have shown that climate change is significantly reducing the suitability of coffee-growing areas in South America, particularly for Arabica coffee, due to rising temperatures and altered precipitation patterns [
3,
4,
5]. This situation is causing declines in both yield and bean quality, while also increasing pressure from pests such as the coffee berry borer and diseases like coffee leaf rust [
6,
7]. Furthermore, suitable cultivation areas are projected to shift geographically to higher altitudes and latitudes, directly impacting traditional producers [
8]. These developments carry serious implications for small-scale farmers who rely on coffee as their main source of income, as they may face not only reduced production but also a loss in product quality, diminishing market value [
9,
10]. Additionally, the global market dynamic could be disrupted by these changes, leading to price volatility and supply chain disruptions [
11].
In this context, the degree of export market concentration, measured through the Herfindahl–Hirschman Index (HHI), becomes a key element in analyzing the international performance of the coffee sector. Similarly, external competitiveness, assessed using objective indicators such as the Revealed Comparative Advantage (RCA) Index, allows for an evaluation of each producing country’s relative position within the global trade system, considering both market share and export specialization. Based on these analytical tools, the present research aims to describe the level of market concentration and the degree of international competitiveness among the main South American coffee-producing countries, with the goal of providing quantitative evidence on the current conditions that shape their potential for sustainable trade diversification.
This study is important as it precisely establishes the structural conditions of coffee foreign trade in South American countries from a quantitative and objective perspective. Beyond offering a descriptive view, the indicators used (HHI and RCA) serve as essential tools for designing trade strategies that promote a more robust and balanced international integration. Understanding the degree of market concentration provides evidence of the need to diversify export destinations. At the same time, analyzing competitiveness helps to assess the extent to which countries are genuinely positioned as key players in the coffee market or if their participation is more circumstantial than structural.
1.1. Literature Review
Coffee export market diversification in South America faces multiple logistical, economic, and structural challenges. Logistically, countries such as Brazil—the region’s largest coffee producer—experience bottlenecks due to high port costs, container shortages, and limited shipping space, problems that worsened after the COVID-19 pandemic [
12]. Furthermore, the evolving regulations governing maritime and port transport add complexity and costs to the export process.
Economically, South American countries are at a disadvantage in a global market dominated by developed nations such as Switzerland, Germany, and Italy, which lead in the export of processed coffee, whereas South America primarily exports unprocessed coffee [
13]. Additionally, coffee price volatility, driven by market liberalization and increased financial investment in commodity exchanges, negatively affects producer stability [
14].
On the structural side, countries in the region must modernize their production systems through technological advances and changes in governance models, while also addressing global value distribution asymmetries and both tariff and non-tariff barriers. Small producers face financial constraints, limited access to information, and weak social networks, all of which hinder their full participation in specialty coffee markets [
15].
In response, proposed solutions include collaborative genetic improvement programs to develop more resilient varieties [
16] and a strategic focus on specialty coffee markets that offer better prices and sustainability [
17]. Furthermore, strengthening fair trade and certification schemes presents an opportunity to support small-scale producers, although meeting these complex requirements remains a challenge [
18,
19].
The profitability of the coffee industry is also critical to the well-being of many Latin American economies, as evidenced by Central America, where there is a growing need to reorient production toward quality and new markets, as seen in the case of Mexican coffee [
20]. Colombia, in turn, has been affected by falling international prices due to increased global supply and internal factors such as currency revaluation and a decline in available labor [
19].
Preferential trade agreements have proven decisive in improving export performance, as demonstrated in Eastern and Southern African countries [
21], highlighting the importance of regional integration in South America.
From an environmental standpoint, climate change, pests, and diseases pose growing threats to production sustainability, affecting productivity and the global competitiveness of exporting countries [
16]. The dependency model based on coffee exports in less-developed countries has also been linked to deforestation, raising concerns about environmental well-being [
22].
Socially, coffee has historically served as a driver of economic and social development, although the high dependence on agricultural exports has deeply shaped the internal structures of many countries [
23]. Initiatives such as fair trade are also seen as key strategies for improving the competitiveness of small producers, while factors such as geographic distance, pricing, and ease of doing business have been identified as determinants of the export supply from Brazil, Colombia, and Peru [
24].
Finally, technological barriers remain a challenge. In Brazil, the role of the institutional environment and the use of technologies such as waste-to-energy systems and business analysis tools in the coffee supply chain have been recognized [
25]. Meanwhile, for countries like Indonesia, despite having comparative advantages, a lack of competitiveness in markets such as the United States suggests the need to overcome existing technological barriers [
26].
While numerous studies have addressed the dynamics of coffee exports in South America, much of the existing literature tends to focus on descriptive statistics or isolated case studies of major producers such as Brazil, Colombia, and Peru. However, there is still limited debate regarding the structural vulnerability that results from market concentration and the implications of climate and geopolitical risks on long-term competitiveness. Some authors highlight the limitations of relying heavily on traditional export destinations, whereas others argue for the potential of emerging specialty markets and value-added products. Yet, there is a lack of consensus on the effectiveness of current diversification strategies and little comparative analysis between countries that have succeeded versus those that remain dependent on volatile commodity markets. Furthermore, although tools like the Herfindahl–Hirschman Index (HHI) and revealed comparative advantage (RCA) are commonly used, few studies have critically discussed their limitations or complemented them with broader multidimensional frameworks such as export gaps, price competitiveness, or value chain integration indicators. This study contributes to the debate by bridging these gaps, offering a cross-country comparison of South American exporters, and integrating structural, environmental, and institutional factors to reassess the region’s positioning in the global coffee market.
1.2. Theoretical Framework
The index has proven useful for revealing high concentration risks, as seen in the case of Chilean cherry exports, which are heavily reliant on the Chinese market [
27]. While the HHI provides a clear numerical value and is sensitive to changes in the largest market shares, its accuracy depends on the completeness of the available data. In contexts with partial information, estimates may be used, though this reduces the indicator’s precision [
28,
29]. Additionally, a study in Russia applied the HHI alongside other indicators such as the Lerner Index to assess the level of monopolization in various agricultural products [
30]. In China’s dairy industry, the HHI was employed to analyze market concentration in the downstream chain, revealing its impact on market efficiency and upstream agricultural production [
31]. In the case of horticultural products, research in Ukraine used the HHI to measure market competitiveness for fruits and berries, finding low concentration and high competition, which reflect a broad diversity of operators and limited dominance by individual actors [
32].
In the international coffee market, the HHI indicated a low level of concentration in import and export structures, suggesting a dynamic and competitive environment [
33]. However, in Brazil’s domestic coffee market, the HHI revealed significant concentration, with limited variation among leading buyers and sellers, indicating a more rigid and stable structure [
34]. Similarly, an analysis of Colombian coffee exports to the European Union used the HHI to assess market share, trade value, and the competitive position of coffee compared to other agricultural exports such as bananas and palm oil [
35]. These studies highlight the usefulness of the HHI as a key tool for understanding market structure, identifying risks associated with trade dependency, and informing export diversification strategies in the agricultural sector.
On the other hand, the Revealed Comparative Advantage (RCA) Index is widely used in international trade analysis to assess a country’s relative advantage or disadvantage in exporting a particular good or service. This quantitative tool measures a country’s competitiveness in the global market by comparing the share of a specific product in a nation’s exports with the share of that same product in total global exports [
36].
Therefore, the RCA is a fundamental instrument for understanding export specialization and the economic performance of countries, enabling the precise identification of sectors in which a country has competitive strengths or weaknesses in international trade [
37,
38,
39]. Many countries have shown stable comparative advantages in certain agricultural products. For example, Russia has maintained competitiveness in exporting cereals such as wheat and barley, as well as oilseeds, vegetable oils, and chocolate [
40]. Likewise, in the La Libertad region of Peru, strong advantages have been identified in fruits like blueberries and avocados and vegetables such as asparagus and piquillo peppers [
41]. In India, the RCA has shown competitiveness in fish, fruits, vegetables, sugar, and various food products [
42].
However, coffee presents an opposing trend: India’s comparative advantage in coffee has significantly declined over time, reflecting a progressive loss of competitiveness [
43]. Other countries face similar challenges. In South Africa, while some products such as tobacco and raw hides show advantages, coffee, along with fruits and vegetables, reflects comparative disadvantages, posing serious challenges to sustaining its global market position [
44]. In contrast, Indonesia stands out as a positive case: the RCA for coffee indicates a clear advantage in East and West Asian markets [
45]. However, such success is neither universal nor guaranteed, as it depends on multiple strategic and structural factors. The factors influencing these disparities are diverse. Economic indicators such as GDP per capita and the existence of geographical indications have a positive impact on agricultural RCA [
39]. However, variables such as macroeconomic stability can have mixed effects, introducing uncertainty in the competitiveness of agri-food products. Likewise, domestic productivity growth and real exchange rate depreciation are key determinants of a country’s ability to compete in international markets [
46].
Continuous technological innovation is considered essential for maintaining and enhancing the competitiveness of agricultural exports. Strategic business management can also be a decisive factor in contexts where comparative advantages are fragile or declining [
41]. Finally, the design and implementation of trade-oriented public policies, including bilateral agreements, are fundamental to strengthening existing advantages and reversing those in decline [
45].
2. Methodology
This research was conducted with the purpose of analyzing the behavior of coffee exports in South America, focusing on the following countries: Brazil, Colombia, Peru, and Ecuador (excluding Bolivia, Uruguay, Venezuela, Chile, and Argentina). The selection of these countries is based on their significance within the regional South American context, due to their prominent role in coffee production and trade. To properly define the object of study, the analysis was centered on a specific item within the Harmonized Commodity Description and Coding System [
47], allowing for greater precision and comparability in reported trade flows across countries. The selected item was 090111, corresponding to non-roasted and non-decaffeinated coffee.
Statistical data were collected from the International Trade Center portal [
1], a reliable and internationally recognized source that provides detailed foreign trade data by tariff heading. A ten-year period was used as the reference for analysis. This time frame is supported by widely accepted methodological standards in international trade studies [
27,
48], as it enables the identification of structural trends, the evaluation of changes in international competitiveness, and the formulation of evidence-based strategies for sustainable economic development. Moreover, such a period is long enough to distinguish short-term fluctuations from long-term dynamics.
For analytical purposes, two key indicators were employed:
The Herfindahl–Hirschman Index (
HHI), a widely used tool for measuring market concentration, was applied to international trade to assess the concentration of a country’s exports to specific destinations. The
HHI is calculated by summing the squares of each destination’s market share. For example, if a country exports coffee with market shares of 30%, 30%, 20%, and 20% to four different markets, the
HHI would be 2600, indicating a moderately to highly concentrated market [
49]. Typically, an
HHI below 1500 indicates a competitive market, between 1500 and 2500 reflects moderate concentration, and above 2500 suggests high concentration [
50]. To analyze the diversification of export markets, the
HHI was used. This index, applied to analyze market, company, and commodity concentration, is calculated by summing the squares of each participant’s percentage share in relation to the total, with the equation
HHI =
, where “
s” represents the share or percentage of participation and “
N” is the total number of participants [
27].
The revealed comparative advantage (RCA) is calculated by dividing the share of a specific product in a country’s exports by the share of that product in global exports. An RCA value greater than 1 indicates a comparative advantage, while a value below 1 signals a comparative disadvantage [
51,
52]. The formula is
, where RCA(
Xij) represents the revealed comparative advantage of product
j in country
i. In this expression,
Xi denotes the total export value of country
i, while
Xij symbolizes the total export value of product
j from country
i.
Ww indicates the total value of worldwide exports, and
Wj reflects the total global export value of product
j [
27].
In addition to the traditional RCA, several methodological adaptations have been developed to address its limitations. Among the most notable are the normalized revealed comparative advantage (NRCA) and the additive RCA, which allow for more consistent interpretation and better comparability across different economic contexts [
53,
54].
Lastly, the methodology used follows a quantitative, descriptive, and comparative approach, enabling the identification of both common and distinct patterns among the countries analyzed. This provides a comprehensive view of the South American coffee export landscape over the past decade.
This research focuses on the application of the Herfindahl–Hirschman Index to measure the degree of concentration in export markets and the Revealed Comparative Advantage Index to assess trade specialization. However, it is important to note that these are not the only methodological approaches available for the analysis of international competitiveness. The specialized literature suggests alternative methods that allow for a more comprehensive evaluation of export performance, such as the export gap method or composite models, which integrate multiple structural and commercial dimensions. Nevertheless, this study opts for the use of the HHI and RCA due to their analytical clarity, comparative applicability, and data availability.
3. Results
3.1. Brazil
Over the 2015–2024 period, the global market for unroasted and non-decaffeinated coffee originating from Brazil exhibited an overall growth trend, increasing from USD 5.56 billion to USD 11.34 billion. This rise corresponds to a compound annual growth rate (CAGR) of 8.25%, driven in part by dynamic markets such as Belgium and the group of countries categorized as “others”, which recorded average annual growth rates of 11.51% and 11.20%, respectively. In 2024, Belgium stood out with the highest year-over-year increase of the entire period, doubling its imports with a 139.13% rise compared to the previous year. Conversely, Japan experienced the most moderate growth, with an average rate of 2.71%, although it maintained a stable trajectory with the least annual variation. However, this expansion was not linear. Significant declines were observed, particularly between 2015 and 2018, with reductions across nearly all major markets. The largest annual decrease during the period occurred in Germany in 2023, with a contraction of 36.31%. Despite these fluctuations, the overall market volatility was led by the global total, which exhibited a standard deviation of USD 2 billion, reflecting its sensitivity to changes in aggregate demand. In contrast, Japan displayed the lowest volatility, underscoring its more stable performance in response to market shifts. These findings highlight the concentration of growth in specific destinations and the importance of monitoring not only trade volumes but also the consistency of importer behavior (
Table 1).
Between 2015 and 2024, Brazil’s diversification index remained at levels that, according to international standards, correspond to a competitive market, as the Herfindahl–Hirschman Index (HHI) did not exceed the 1500 threshold in any given year. Throughout this period, a general trend toward greater diversification was observed, albeit with significant fluctuations. The lowest value was recorded in 2023, at 709 points, indicating a peak in competition for that year, followed by a partial recovery in 2024, when the index rose to 796—marking the highest annual increase of the period at 12.28%. In contrast, the sharpest decline occurred between 2022 and 2023, with a decrease of 32.24%, reflecting an abrupt shift in market structure. Although the index increased in certain years, such as 2019 and 2022, the average annual rate reveals a reduction of 2.62%, confirming a general trend toward less concentrated markets. Nevertheless, the standard deviation of 13.68% indicates high variability, suggesting that changes in market composition were frequent and irregular (
Table 2).
In the case of the United States, all ten values over the period fall below −0.3, with seven of them below −0.6, indicating a strong competitive disadvantage 70% of the time and a moderate disadvantage for the remaining 30%. This consistency reinforces the notion of weak export specialization toward that market. Germany displays a more balanced distribution: in six of the ten years (60%), it falls between 0.3 and 0.6, representing an intermediate competitive advantage, while in the remaining four years (40%), it falls under the marginal advantage category. This reflects a relatively favorable and stable position, with moderate fluctuations. Belgium, by contrast, shifts across all categories, with three years showing a competitive disadvantage (one strong, two moderate), three with marginal advantage, and four with intermediate advantage. This suggests a volatile trajectory, though with signs of improvement. Italy remains in an intermediate zone, with five years in the marginal advantage category, three in intermediate advantage, and two in moderate disadvantage—indicating mild but unstable competitiveness. Japan, on the other hand, shows a clear disadvantage, with seven years scoring below −0.3, including four years of strong disadvantage, amounting to 40% of the time. This reinforces its status as one of the least export-specialized destinations for Brazil. From a statistical perspective based on the normalized revealed comparative advantage (NRCA) classification, Germany and, to a lesser extent, Belgium and Italy exhibit signs of competitive advantage, whereas the United States and Japan stand out as markets in which Brazil consistently maintains disadvantages (
Table 3).
3.2. Colombia
Between 2015 and 2024, the market for non-roasted and non-decaffeinated coffee in Colombia exhibited sustained growth, particularly toward destinations such as Panama and Chile. Panama recorded the highest cumulative increase, with growth exceeding 500%, as well as the highest average annual growth rate, surpassing 21%. However, it also experienced the sharpest decline in 2021, when its imports were halved. In contrast, the group classified as “Others” achieved the highest annual percentage growth in 2021, with an increase of over 100%. Overall, the United States remained the main purchaser, despite significant fluctuations, while the global market showed a positive trend, reflected in cumulative growth of nearly 150% and considerable variability in annual figures (
Table 4).
Between 2015 and 2024, the Herfindahl–Hirschman Index (HHI) applied to the market for unroasted and non-decaffeinated coffee in Colombia exhibited a downward trend, indicating a progressive diversification of export destinations. The initial value of 6,765 in 2015 reflected a high concentration among a few buyers, while the 2023 low of 4,700 marked the point of greatest market dispersion. The most pronounced decline occurred between 2017 and 2018, with a drop of 20%, suggesting a significant opening toward new trading partners. Overall, this evolution represents a cumulative 29% reduction in market concentration, consolidating a sustained diversification process over the past decade (
Table 5).
In the analysis of Colombia’s revealed comparative advantage between 2015 and 2024 with respect to its main export destinations, Chile and Ecuador exhibit the most dynamic trajectories. Chile achieves a robust advantage in 2024 with an index of 0.67, following sustained growth, particularly between 2018 and 2022. Ecuador, despite starting from an unfavorable position, shows the highest cumulative percentage increase—with a 1200% rise—transitioning from a marginal disadvantage to a marginal competitive advantage. Peru also improves its position, ending the period with a positive index, while the United States, despite maintaining an intermediate advantage, is the only country to show a net decline in competitiveness over the period. Panama, for its part, remains in negative territory, with a constant intermediate disadvantage and high volatility in its annual indicators. On the other hand, variability levels reveal significant differences in competitiveness stability. The United States shows the lowest standard deviation, indicating a more stable, though declining, performance, whereas Panama exhibits the highest, with sharp year-to-year fluctuations. In terms of year-on-year growth, Ecuador leads with an average annual rate of 18.56%, followed by Peru and Chile. Despite its fluctuations, Chile manages to consolidate its position as Colombia’s most competitive partner in 2024. This outlook suggests that while some destinations still present challenges, there is an improving trend in strategic markets, which could translate into opportunities if trade relations are strengthened and export sectors diversified (
Table 6).
3.3. Peru
Among the main destination markets for unroasted and non-decaffeinated coffee exported by Peru, Chile and the United States stand out. Chile has been the most consistent buyer and the one with the highest volumes, reaching its peak in 2022 with USD 1.55 million, although it experienced a slight decline to USD 1.053 million in 2024. The United States, meanwhile, showed an outstanding growth of 955% in 2019, rising from USD 57 thousand to USD 601 thousand. Despite a sharp drop in 2021, it managed to stabilize in the following years, reaching USD 121 thousand in 2024—representing a 128% increase compared to 2015. Globally, the total export value peaked in 2015 at USD 1.785 million and, after several declines and recoveries, closed at USD 1.245 million in 2024. Additionally, the entry of new markets such as Uruguay, China, and Ecuador is noteworthy. These countries had not recorded any purchases in 2015 but demonstrated significant transactions in recent years. Uruguay, for example, imported USD 28 thousand in 2022 and closed at USD 10 thousand in 2024, while Ecuador reached USD 20 thousand in the same year. However, the group categorized as “other” countries, which contributed USD 1.284 million in 2015, plummeted to just USD 31 thousand in 2024—representing the largest percentage decrease in the period (−97.6%). Overall, the average annual growth rate was negative for the global total and for the group of miscellaneous countries, although it was positive for Chile, the United States, and the new markets. This suggests a trend toward concentration in a few strategic buyers (
Table 7).
Between 2015 and 2024, the Herfindahl–Hirschman Index (HHI) showed considerable variability, with an average annual growth rate of 11.1% and a standard deviation of 42.94%, highlighting significant fluctuations in market concentration. The largest increase occurred in 2018, with a rise of 82.05%, while the most pronounced decline was recorded in 2019, with a decrease of 40.56%. In contrast, the least severe negative variation took place in 2017, with a drop of 12.61%. This behavior suggests alternating periods of increased and reduced diversification, reflecting potential changes in the competitive structure of the analyzed sector (
Table 8).
During the 2015–2024 period, Peru did not achieve revealed comparative advantages in its main export destinations: Chile, the United States, Ecuador, China, and Uruguay. In all cases, the competitiveness index (TC) remained at extremely low levels, with constant values of –1.00, reflecting a pronounced international disadvantage. The sole exception was Chile, where a slight improvement to –0.99 was recorded in 2018, a value that remained unchanged through 2024. While this minimal variation does not alter the disadvantage category, it does represent the only percentage growth in the period. In contrast, the other countries showed no variation in any year, indicating persistently low and stagnant competitiveness. Statistically, Chile was the only destination with a non-zero standard deviation, although marginal. The average annual growth across all trade partners was virtually zero, reinforcing the conclusion that Peru failed to strengthen its competitive position in these markets over time (
Table 9).
3.4. Ecuador
Between 2015 and 2024, the market for unroasted and non-decaffeinated coffee in Ecuador exhibited a trajectory characterized by significant fluctuations. Chile emerged as the primary export destination, with a cumulative growth of 65%, rising from USD 671,000 to USD 1,108,000, also reflecting one of the most stable annual growth rates, approximately 5%. In contrast, the group categorized as “Others” experienced the sharpest proportional decline, with an 84% decrease over the same period. This contrast highlights a concentration of trade among a few strategic partners, while other destinations lost relevance. Additionally, although France initially reported low values, it registered abrupt spikes, such as in 2021 when exports reached USD 173,000 after several years of null figures, indicating volatile behavior. On the other hand, in an analysis of temporal variability, the global market showed a standard deviation of approximately USD 365,000, reflecting high oscillations in export volumes. Chile, with a deviation of USD 238,000, also exhibited considerable variability, albeit within a context of sustained overall growth. Regarding year-on-year growth, notable extreme cases include the United States in 2016, with a 242% increase, and Hong Kong in 2023, when there was a rise from USD 1000 to USD 32,000, representing an extraordinary percentage leap. Taken together, these data reveal an unstable commercial dynamic, with expansion peaks in specific markets but lacking a sustained long-term trend beyond the Chilean market (
Table 10).
Between 2015 and 2024, the concentration index in Ecuador, measured through the Herfindahl–Hirschman Index (HHI), showed a cumulative increase of 123.71%, indicating a trend toward reduced productive diversification in the country. The highest annual increase was recorded in 2023, with a variation of 93.12%, whereas the sharpest decline occurred in 2022, with a decrease of 35.26% compared to the previous year. In contrast, the smallest reduction was observed in 2018, with a decline of 14.57%. On average, the index grew by 15.16% per year, albeit with high volatility, as reflected in a standard deviation of 35.97%, suggesting significant shifts in the national productive structure over the analyzed period (
Table 11).
During the 2015–2024 period, Ecuador’s revealed comparative advantage exhibited contrasting patterns depending on the destination country. Hong Kong recorded the highest cumulative growth, shifting from a negative value in 2015 (−1.00) to a positive one in 2024 (0.97), representing an increase of 197%. This significant change was also evident in the average annual variation, with Hong Kong leading at 21.78%, indicating a sustained improvement in the competitiveness of Ecuadorian exports to this market. In contrast, Chile displayed a stable and consistent performance, maintaining a positive comparative advantage throughout the period and showing low year-on-year variability (standard deviation of 0.038), suggesting a steady and predictable trade relationship. On the other hand, the United States showed an almost consistently negative trend, with values remaining unfavorable for most of the period and an average annual variation of −0.12%, pointing to structural weaknesses in Ecuador’s export position to this destination. Japan and France also demonstrated unstable behavior, with cumulative declines of 18.06% and 13.92%, respectively, along with high levels of year-on-year variability. In summary, while certain destinations such as Hong Kong offered growing opportunities for the consolidation of Ecuadorian exports, other markets reflected challenges that hindered the development of a sustainable comparative advantage (
Table 12).
Brazil shows the strongest overall export growth, nearly doubling its trade value with a compound annual growth rate of 8.25%, driven mainly by dynamic markets such as Belgium. The declining HHI indicates increasing diversification, and although the country enjoys a competitive advantage in Germany, it consistently struggles in the U.S. and Japan. Colombia also demonstrates robust growth (+147%), supported by strategic markets like Chile and Panama. Its HHI decreased significantly, signaling a solid diversification trend. Competitiveness improved notably in Chile and Ecuador, while remaining relatively stable in the U.S. Peru, in contrast, saw a 30% decline in exports and shows the most unstable diversification pattern. The HHI trend is erratic, peaking in 2022, and the country consistently shows revealed comparative disadvantages in all its major markets, with only minimal improvement in Chile. Ecuador experienced fluctuations in export performance, ending with a slightly lower value than in 2015. The HHI increased sharply, suggesting a re-concentration of exports. Nevertheless, it gained competitiveness in Chile and especially Hong Kong, though it faces ongoing disadvantages in traditional markets like the U.S., France, and Japan. In sum, Brazil and Colombia exhibit the most resilient export structures, while Peru and Ecuador remain vulnerable due to higher concentration and weaker international competitiveness. Colombia stands out for its balanced improvement in both diversification and competitive positioning (
Table 13).
4. Discussion
The comparative analysis reveals that the structure of South American coffee trade exhibits significant disparities in terms of market concentration and competitive performance. The values of the Herfindahl–Hirschman Index confirm that Brazil and Colombia have moved towards less concentrated markets, whereas Peru and Ecuador remain highly dependent on a limited number of buyers, reinforcing the hypothesis that export resilience relies on the geographical and functional diversification of the value chain [
33].
In Brazil, the rebound of the HHI recorded in 2024 indicates a partial reversal of the diversification progress achieved over the past decade. Ongoing logistical bottlenecks—high port fees, container shortages, and limited vessel space—continue to hinder the full integration of the Brazilian economy into international markets [
12]. The persistent competitive disadvantage vis-à-vis the United States and Japan, as reflected in the normalized revealed comparative advantage value, is largely explained by distance-related costs and institutional frictions highlighted by gravity trade models [
24].
The Colombian case illustrates the effectiveness of bilateral agreements as catalysts for diversification. The steady decline in concentration and the consolidation of a comparative advantage in Chile and Ecuador underscore the importance of regional integration [
21]. However, the high volatility of exports to Panama highlights that the opening of new markets does not guarantee stable benefits in the absence of robust governance and technological innovation that enables traceability and origin-based differentiation [
13,
14].
Peru’s situation emerges as the most critical. A persistently high HHI and a negative Revealed Comparative Advantage Index across all analyzed destinations indicate a vulnerable and technologically lagging export structure. Dependence on Chile and the United States exposes producers to price volatility, limiting their strategic flexibility, while the low adoption of fair trade certifications and other quality distinctions hampers the capture of price premiums [
18,
41].
Ecuador presents a dual trajectory. The cumulative increase in the HHI suggests a trend towards concentration, primarily driven by deepening sales to Chile. Nonetheless, the sharp rise in comparative advantage in Hong Kong reveals the presence of high-value Asian niches that could replicate Indonesia’s success through segmentation strategies, varietal innovation, and stringent environmental policies aimed at minimizing deforestation associated with monoculture [
22,
26].
In summary, three cross-cutting factors shape regional performance: first, port and domestic transport logistics, impacted by historical underinvestment and heterogeneous regulatory frameworks; second, climate exposure, which reduces suitable areas for Arabica coffee and necessitates climate-smart agricultural practices [
2,
3]; third, the capacity to generate added value through genetic innovation, quality differentiation, and sustainability certification—essential tools for accessing premium segments and mitigating market risks.
5. Conclusions
The results obtained allow us to conclude that the concentration of target markets for South American coffee exhibits significant variability among the countries analyzed. Brazil and Colombia show a transition toward more competitive export structures, characterized by a greater diversification of destinations and relative stability in their comparative advantages. In contrast, Peru and Ecuador continue to rely on a limited number of strategic buyers, which exposes them to external risks such as price volatility, trade barriers, and shifts in global demand.
Furthermore, the increasing climatic variability projected for South America underscores the urgency of implementing adaptive production strategies. The progressive reduction in suitable areas for Arabica coffee cultivation—due to rising temperatures and altered precipitation patterns—necessitates sustained investment in genetic improvement programs, as well as the adoption of agricultural technologies that ensure resilience to extreme weather events.
Additionally, significant logistical and governance limitations have been identified along the value chains, particularly in countries such as Brazil and Peru. Persistent high port costs, delays in customs procedures, and the limited digitalization of foreign trade-related services undermine regional competitiveness and hinder access to demanding markets such as the United States and Japan. These structural deficiencies represent critical barriers that must be addressed as a priority.
Based on these findings, a comprehensive strategy is proposed, organized into three complementary pillars. In the commercial pillar, it is recommended to expand and deepen existing preferential agreements, strengthen national export promotion agencies, and develop trade intelligence systems focused on identifying emerging niches, with special emphasis on Asian markets. In the logistics pillar, it is essential to promote public–private investments aimed at modernizing ports, improving road infrastructure, and digitalizing customs procedures, thereby reducing operational times and costs. Finally, in the technological and environmental pillar, it is suggested to finance research programs focused on developing more resilient varieties, strengthen technical assistance for the implementation of agroecological practices, and incentivize sustainability certifications as mechanisms to access differentiated value chains and achieve better prices.
Ultimately, coherent coordination between trade, infrastructure, and science and technology policies constitutes a necessary condition for South American coffee-producing countries to enhance their comparative advantage in the international context. Moreover, this strategic integration will help ensure the economic, social, and environmental sustainability of an emblematic crop facing increasingly complex structural and situational challenges in today’s global economy.
Author Contributions
Conceptualization, J.C.M.N. and H.D.G.J.; Methodology, J.C.M.N., M.M.F.C., and H.Y.M.Y.; Software, J.C.M.N. and C.D.C.O.; Validation, J.C.M.N. and A.R.R.A.; Formal Analysis, H.D.G.J. and C.D.C.O.; Investigation, J.C.M.N., H.Y.M.Y., and S.J.A.M.; Data Curation, H.D.G.J. and S.L.L.L.; Writing—Review and Editing, A.R.R.A., S.J.A.M., E.J.S.C., and S.L.L.L.; Visualization, M.M.F.C. and E.J.S.C.; Project administration, J.C.M.N. and A.R.R.A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data are contained within the article.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- International Trade Center. Trade Map—Trade Statistics for International Business Development 2025. Available online: https://www.trademap.org/ (accessed on 1 February 2025).
- Girma, B. The Impact of Climate Change on Coffee Processing: A Review. Agric. For. Fish. 2023, 12, 120–129. [Google Scholar] [CrossRef]
- Bilen, C.; El Chami, D.; Mereu, V.; Trabucco, A.; Marras, S.; Spano, D. A Systematic Review on the Impacts of Climate Change on Coffee Agrosystems. Plants 2023, 12, 102. [Google Scholar] [CrossRef] [PubMed]
- Bracken, P.; Burgess, P.J.; Girkin, N.T. Opportunities for enhancing the climate resilience of coffee production through improved crop, soil and water management. Agroecol. Sustain. Food Syst. 2023, 47, 1125–1157. [Google Scholar] [CrossRef]
- Ovalle-Rivera, O.; Läderach, P.; Bunn, C.; Obersteiner, M.; Schroth, G. Projected shifts in Coffea arabica suitability among major global producing regions due to climate change. PLoS ONE 2015, 10, e0124155. [Google Scholar] [CrossRef]
- Jawo, T.O.; Kyereh, D.; Lojka, B. The impact of climate change on coffee production of small farmers and their adaptation strategies: A review. Clim. Dev. 2023, 15, 93–109. [Google Scholar] [CrossRef]
- Viguera, B.; Alpízar, F.; Harvey, C.A.; Ruth Martínez-Rodríguez, M.; Saborío-Rodríguez, M. Climate change perceptions and adaptive responses of small-scale coffee farmers in Costa Rica | Percepciones de cambio climático y respuestas adaptativas de caficultores costarricenses de pequeña escala. Agron. Mesoam. 2019, 30, 333–351. [Google Scholar] [CrossRef]
- Koutouleas, A.; Arias, M.; Barrera, J.F.; Zewdie, B.; Kagezi, G.; Ssekiwoko, F.; Avelino, J. Impacts of climate change on pests and diseases of coffee in East Africa and Mesoamerica. Adv. Bot. Res. 2025, 114, 163–206. [Google Scholar]
- Pham, Y.; Reardon-Smith, K.; Mushtaq, S.; Cockfield, G. The impact of climate change and variability on coffee production: A systematic review. Clim. Change 2019, 156, 609–630. [Google Scholar] [CrossRef]
- Abebe, G. Dealing with climate change and other stressors: Small-scale coffee farmers in the Fero-two Peasant Association in the Wensho district, southern Ethiopia. GeoJournal 2021, 86, 2539–2554. [Google Scholar] [CrossRef]
- Rivera, R.A.; Martin, G.M.; Simó, J.E.; Pentón, G.; García-Rubido, M.; Ramirez, J.F.; Gonzalez, P.J.; Joao, J.P.; Ojeda, L.; Tamayo, Y.; et al. Impact of climate change on coffee production|Impacto del cambio climático sobre la producción de café. Trop. Subtrop. Agroecosyst. 2020, 23, 1–18. [Google Scholar]
- Ferreira, R.S.; Alvarenga, R.P. Impacts of the Covid-19 pandemic on the logistics of exporting coffee in containers. Coffee Sci. 2023, 18, e182157. [Google Scholar] [CrossRef]
- Lima, U.M.; Lee, K. Governance and Asymmetry in Global Value Chains of the Coffee Industry: Possibility for Catch-Up by Emerging Economies. Seoul J. Econ. 2023, 36, 79–111. [Google Scholar]
- Newman, S.A. Financialization and changes in the social relations along commodity chains: The case of coffee. Rev. Radic. Political Econ. 2009, 41, 539–559. [Google Scholar] [CrossRef]
- Aragón-Guzmán, S.E.; Regino-Maldonado, J.; Vásquez-López, A.; Toledo-López, A.; Nuria Jurado-Celis, S.; Granados-Echegoyen, C.A.; Landero-Valenzuela, N.; Arroyo-Balán, F.; Quiroz-González, B.; Peñaloza-Ramírez, J.M. A systematic literature review on environmental, agronomic, and socioeconomic factors for the integration of small-scale coffee producers into specialized markets in Oaxaca, Mexico. Front. Sustain. Food Syst. 2024, 8, 1386956. [Google Scholar] [CrossRef]
- Ngure, G.M.; Watanabe, K.N. Coffee sustainability: Leveraging collaborative breeding for variety improvement. Front. Sustain. Food Syst. 2024, 8, 1431849. [Google Scholar] [CrossRef]
- Jacobi, J.; Lara, D.; Opitz, S.; de Castelberg, S.; Urioste, S.; Irazoque, A.; Castro, D.; Wildisen, E.; Gutierrez, N.; Yeretzian, C. Making specialty coffee and coffee-cherry value chains work for family farmers’ livelihoods: A participatory action research approach. World Dev. Perspect. 2024, 33, 100551. [Google Scholar] [CrossRef]
- Renard, M.C.; Pérez-Grovas, V. Fair Trade Coffee in Mexico: At the Center of the Debates. In Fair Trade: The Challenges of Transforming Globalization; Routlege: Oxfordshire, UK, 2007; pp. 138–156. [Google Scholar]
- Ramos, M.M.; Chamorro, F.A.M.; Bejarano, L.R.; Calderón, K.A.A.; Gómez, L.A.G. Transformation of Colombian small coffee growers and new scenarios for their competitiveness. Int. J. Glob. Small Bus. 2017, 9, 120–143. [Google Scholar] [CrossRef]
- Xotlanihua-Flores, D.; Crespo-Stupková, L. Exports of Mexican Coffee to the United States and German markets | Exportações do café mexicano aos mercados estadounidense e alemão | Exportaciones del Café Mexicano a los Mercados Estadounidense Y Alemán. Rev. Iberoam. Vitic. Agroind. Rural. 2024, 11, 150–169. [Google Scholar]
- Nsabimana, A.; Tirkaso, W.T. Examining coffee export performance in Eastern and Southern African countries: Do bilateral trade relations matter? Agrekon 2020, 59, 46–64. [Google Scholar] [CrossRef]
- Austin, K. Coffee exports as ecological, social, and physical unequal exchange: A cross-national investigation of the java trade. Int. J. Comp. Sociol. 2012, 53, 155–180. [Google Scholar] [CrossRef]
- Nuhn, H. Globalization and Regionalization in Central America. In The Dialectics of Globalization; Routledge: Oxfordshire, UK, 2019; pp. 163–176. [Google Scholar]
- Arevalo, J.L.S.; De Andrade, Á.A.F.; E Silva, G.A.B. Uma nota sobre modelos gravitacionais aplicados à exportação de café de Brasil, Colômbia e Peru. Rev. Bras. De Econ. 2016, 70, 271–280. [Google Scholar] [CrossRef]
- Saraiva, C.E.D.A.B.; Fernandes, A.M.; Schultz, G.; Machado, J.A.D. Competitiveness in the coffee production chain: A systematic review of the literature. Custos E Agronegocio 2019, 15, 389–415. [Google Scholar]
- Innayatuhibbah, G.A.; Rahayu, E.S.; Ferichani, M. Export competitiveness of Indonesian coffee in the United States market. Sci. Horiz. 2024, 27, 125–135. [Google Scholar] [CrossRef]
- Ninaquispe, J.C.M.; Ballesteros, M.A.A.; Jugo, D.A.L.; Aldana, M.L.; Valle, M.; Salinas, L.E.C.; Chilicaus, G.C.F.; Juárez, H.D.G. Competition in the International Cherry Market: A Competitiveness Analysis of the Developing Country. Corp. Bus. Strategy Rev. 2024, 5, 27–35. [Google Scholar] [CrossRef]
- Naldi, M.; Flamini, M. Censoring and Distortion in the Hirschman–Herfindahl Index Computation. Econ. Pap. 2017, 36, 401–415. [Google Scholar] [CrossRef]
- Busu, M. A market concentration analysis of the biomass sector in Romania. Resources 2020, 9, 64. [Google Scholar] [CrossRef]
- Khasanova, S.F.; Fazullina, A.I. Assessing of the competitiveness level in the industry using the correlation analysis on the example of agriculture of the republic of Tatarstan, Russian federation. Am. J. Agric. Biol. Sci. 2015, 10, 12–17. [Google Scholar] [CrossRef]
- Yu, Z.; Feng, G.; Liu, H.; Peng, H.; Dong, X. Sustainable market? The impact of downstream market concentration on high-quality agricultural development: Evidence from China’s dairy industry. Front. Sustain. Food Syst. 2024, 8, 1453115. [Google Scholar] [CrossRef]
- Salo, I.A.; Cheremisina, S.G. Competitiveness in the Horticultural Market of Ukraine. Ekon. APK 2022, 29, 26–33. [Google Scholar] [CrossRef]
- Gois, T.C.; Thomé, K.M.; Balogh, J.M. Behind a cup of coffee: International market structure and competitiveness. Compet. Rev. 2023, 33, 993–1009. [Google Scholar] [CrossRef]
- Thomé, K.M.; Ferreira, L.S. Coffee international competitiveness and structure of market: Analysis from 2003 to 2012 | Competitividade e estrutura de mercado internacional de café: Análise de 2003 a 2012. Coffee Sci. 2015, 10, 184–194. [Google Scholar]
- Cubillos, J.P.T.; Soltész, B.; Vasa, L. Bananas, coffee and palm oil: The trade of agricultural commodities in the framework of the EU-Colombia free trade agreement. PLoS ONE 2021, 16, e0256242. [Google Scholar] [CrossRef]
- Liu, B.; Gao, J. Normality in the Distribution of Revealed Comparative Advantage Index for International Trade and Economic Complexity. Appl. Sci. 2022, 12, 1125. [Google Scholar] [CrossRef]
- Deb, K.; Sengupta, B. Value-Added Trade and Empirical Distributions of RCA Indices. J. Quant. Econ. 2018, 16, 235–264. [Google Scholar] [CrossRef]
- Bojnec, Š.; Fertő, I. Meat export competitiveness of European union countries on global markets. Agric. Food Sci. 2014, 23, 194–206. [Google Scholar] [CrossRef]
- Balogh, J.M.; Jámbor, A. Determinants of revealed comparative advantages: The case of cheese trade in the European Union. Acta Aliment. 2017, 46, 305–311. [Google Scholar] [CrossRef]
- Ishchukova, N.; Smutka, L. Revealed comparative advantage of Russian agricultural exports. Acta Univ. Agric. Silvic. Mendel. Brun. 2013, 61, 941–952. [Google Scholar] [CrossRef]
- Soriano-Colchado, A.M.; Diez-Matallana, R.A.; Gómez-Oscorima, R.M.; Jiménez-Díaz, L.A.; Vasquez-Quispe, C.Z. Competitiveness of the La Libertad region in agricultural exports, Peru, 2011–2023. Sci. Horiz. 2024, 27, 121–133. [Google Scholar] [CrossRef]
- Nabi, T.; Kaur, T.P. Export specialization of India with top five agricultural economies: An application of RCA and RSCA. Int. J. Innov. Technol. Explor. Eng. 2019, 8, 4705–4708. [Google Scholar] [CrossRef]
- Suresh, A.; Mathur, V.C. Export of agricultural commodities from India: Performance and prospects. Indian J. Agric. Sci. 2016, 86, 876–883. [Google Scholar] [CrossRef]
- Bahta, Y.T. Competitiveness of South Africa’s agri-food commodities. AIMS Agric. Food 2021, 6, 945–968. [Google Scholar] [CrossRef]
- Hermawan, D.; Pasaribu, Y.M.; Muda, I.; Abdunazarov, S.; Saksono, H.; Akhmadeev, R.; Al-Khafaji, F.A.H.; Alawadi, A.H. On the Priorities of Indonesia’s Agricultural Trade: Which Product-Market Combinations Are Economically the Best? Southeast Asian J. Econ. 2023, 11, 1–27. [Google Scholar]
- Abbas, S.; Waheed, A. Trade competitiveness of Pakistan: Evidence from the revealed comparative advantage approach. Compet. Rev. 2017, 27, 462–475. [Google Scholar] [CrossRef]
- World Customs Organization. HS Convention 2025. Available online: https://www.wcoomd.org/en/topics/nomenclature/instrument-and-tools/hs_convention.aspx (accessed on 29 March 2025).
- Montes Ninaquispe, J.C.; Arbulú Ballesteros, M.A.; Cruz Salinas, L.E.; García Juárez, H.D.; Farfán Chilicaus, G.C.; Martel Acosta, R.; Guzmán Valle, M.D.L.Á.; Coronel Estela, C.V. A Strategy for the Sustainability of Peru’s Blueberry Exports: Diversification and Competitiveness. Sustainability 2024, 16, 6606. [Google Scholar] [CrossRef]
- Brezina, I.; Pekár, J. Sensitivity analysis of Herfindahl-Hirschman index on the Slovak banking sector | Analýza citlivosti hodnôt herfindahlovho-hirschmanovho indexu slovenského bankového sektora. Polit. Ekon. 2013, 61, 735–751. [Google Scholar] [CrossRef]
- Brezina, I.; Pekár, J.; Čičková, Z.; Reiff, M. Herfindahl–Hirschman index level of concentration values modification and analysis of their change. Cent. Eur. J. Oper. Res. 2016, 24, 49–72. [Google Scholar] [CrossRef]
- Wiryawan, D.; Rodliyah, N.; Wahyudi, H.; Leny, S.M. The Effect of Retail E-Commerce Sales and Domestic Direct Investment on the RCA Value of the Indonesian Medium High Technology Sector: RLS and FMOLS Approach. J. Ecohumanism 2024, 3, 5260–5272. [Google Scholar] [CrossRef]
- Kowalski, P.; Bottini, N. Comparative advantage and export specialisation mobility. In Globalisation, Comparative Advantage and the Changing Dynamics of Trade; OECD: Paris, France, 2011; Volume 9789264113, pp. 81–119. [Google Scholar]
- Hoen, A.R.; Oosterhaven, J. On the measurement of comparative advantage. Ann. Reg. Sci. 2006, 40, 677–691. [Google Scholar] [CrossRef]
- Yu, R.; Cai, J.; Leung, P.S. The normalized revealed comparative advantage index. Ann. Reg. Sci. 2009, 43, 267–282. [Google Scholar] [CrossRef]
Table 1.
Destination markets for unroasted and non-decaffeinated coffee from Brazil (USD billions).
Table 1.
Destination markets for unroasted and non-decaffeinated coffee from Brazil (USD billions).
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
World | 5.56 | 4.84 | 4.60 | 4.36 | 4.54 | 4.97 | 5.80 | 8.51 | 7.32 | 11.34 |
United States of America | 1.18 | 0.94 | 0.92 | 0.77 | 0.90 | 0.93 | 1.12 | 1.71 | 1.13 | 1.90 |
Germany | 1.06 | 0.95 | 0.88 | 0.75 | 0.79 | 0.97 | 1.06 | 1.68 | 1.07 | 1.81 |
Belgium | 0.41 | 0.34 | 0.30 | 0.30 | 0.30 | 0.47 | 0.49 | 0.74 | 0.46 | 1.10 |
Italy | 0.56 | 0.48 | 0.49 | 0.46 | 0.47 | 0.42 | 0.48 | 0.81 | 0.66 | 0.95 |
Japan | 0.44 | 0.41 | 0.32 | 0.32 | 0.34 | 0.29 | 0.40 | 0.38 | 0.44 | 0.56 |
Others | 1.91 | 1.71 | 1.69 | 1.75 | 1.74 | 1.90 | 2.25 | 3.19 | 3.55 | 5.02 |
Table 2.
Diversification index of Brazil’s exports.
Table 2.
Diversification index of Brazil’s exports.
Years | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
HHI Value | 1083 | 1039 | 1028 | 890 | 962 | 975 | 954 | 1046 | 709 | 796 |
Table 3.
Revealed comparative advantage of Brazil in its main export destinations.
Table 3.
Revealed comparative advantage of Brazil in its main export destinations.
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
United States of America | −0.46 | −0.51 | −0.60 | −0.64 | −0.54 | −0.41 | −0.55 | −0.64 | −0.60 | −0.58 |
Germany | 0.22 | 0.22 | 0.13 | 0.09 | 0.24 | 0.39 | 0.26 | 0.13 | 0.22 | 0.27 |
Belgium | 0.02 | −0.08 | −0.17 | −0.12 | −0.04 | 0.26 | 0.08 | −0.10 | 0.06 | 0.22 |
Italy | 0.14 | 0.08 | 0.00 | 0.04 | 0.19 | 0.14 | −0.01 | −0.10 | 0.15 | 0.09 |
Japan | −0.18 | −0.17 | −0.38 | −0.23 | −0.24 | −0.19 | −0.26 | −0.56 | −0.29 | −0.28 |
Table 4.
Markets for unroasted and non-decaffeinated coffee in Colombia, in millions of USD.
Table 4.
Markets for unroasted and non-decaffeinated coffee in Colombia, in millions of USD.
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
World | 42.41 | 38.86 | 60.28 | 60.36 | 79.60 | 67.19 | 81.37 | 110.07 | 90.39 | 104.74 |
United States of America | 34.80 | 31.64 | 50.13 | 44.95 | 59.75 | 50.25 | 56.75 | 81.14 | 61.09 | 71.66 |
Chile | 1.73 | 1.75 | 1.80 | 2.45 | 2.55 | 3.35 | 4.85 | 5.60 | 8.75 | 8.75 |
Ecuador | 1.40 | 0.92 | 1.45 | 1.51 | 2.10 | 1.78 | 2.26 | 2.71 | 3.20 | 3.98 |
Peru | 0.70 | 0.53 | 0.75 | 0.70 | 0.84 | 0.98 | 0.94 | 1.15 | 1.77 | 2.09 |
Panama | 0.34 | 0.61 | 0.99 | 1.53 | 2.45 | 3.64 | 1.81 | 1.89 | 2.00 | 2.06 |
Others | 3.45 | 3.42 | 5.17 | 9.23 | 11.92 | 7.20 | 14.77 | 17.59 | 13.58 | 16.20 |
Table 5.
Diversification index of Colombia’s exports.
Table 5.
Diversification index of Colombia’s exports.
Years | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
HHI Value | 6765 | 6664 | 6940 | 5588 | 5676 | 5667 | 4974 | 5507 | 4700 | 4789 |
Table 6.
Revealed comparative advantage of Colombia in its main export destinations.
Table 6.
Revealed comparative advantage of Colombia in its main export destinations.
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
United States of America | 0.55 | 0.51 | 0.44 | 0.42 | 0.46 | 0.58 | 0.47 | 0.33 | 0.49 | 0.49 |
Chile | 0.40 | 0.44 | −0.02 | 0.11 | 0.19 | 0.51 | 0.44 | 0.15 | 0.70 | 0.67 |
Ecuador | −0.01 | −0.13 | −0.29 | −0.34 | −0.25 | −0.07 | −0.15 | −0.29 | 0.03 | 0.11 |
Peru | −0.24 | −0.34 | −0.46 | −0.47 | −0.42 | −0.10 | −0.34 | −0.43 | 0.02 | 0.04 |
Panama | −0.75 | −0.52 | −0.66 | −0.59 | −0.27 | 0.26 | −0.41 | −0.78 | −0.55 | −0.55 |
Table 7.
Markets for unroasted and non-decaffeinated coffee in Peru (in thousands of USD).
Table 7.
Markets for unroasted and non-decaffeinated coffee in Peru (in thousands of USD).
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
World | 1785 | 702 | 697 | 476 | 1583 | 744 | 1716 | 1743 | 1524 | 1245 |
Chile | 448 | 231 | 345 | 374 | 754 | 533 | 1035 | 1550 | 1212 | 1053 |
United States of America | 53 | 55 | 136 | 57 | 601 | 68 | 14 | 79 | 125 | 121 |
Ecuador | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 5 | 20 |
China | 0 | 0 | 16 | 0 | 0 | 0 | 0 | 17 | 0 | 10 |
Uruguay | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 28 | 16 | 10 |
Others | 1284 | 416 | 198 | 45 | 228 | 143 | 667 | 69 | 166 | 31 |
Table 8.
Diversification index of Peru’s exports.
Table 8.
Diversification index of Peru’s exports.
Years | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
HHI Value | 5181 | 3980 | 3478 | 6333 | 3764 | 5327 | 4404 | 7937 | 6444 | 7253 |
Table 9.
Revealed comparative advantage of Peru in its main export destinations.
Table 9.
Revealed comparative advantage of Peru in its main export destinations.
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
Chile | 0.55 | 0.51 | 0.44 | 0.42 | 0.46 | 0.58 | 0.47 | 0.33 | 0.49 | 0.49 |
United States of America | 0.40 | 0.44 | −0.02 | 0.11 | 0.19 | 0.51 | 0.44 | 0.15 | 0.70 | 0.67 |
Ecuador | −0.01 | −0.13 | −0.29 | −0.34 | −0.25 | −0.07 | −0.15 | −0.29 | 0.03 | 0.11 |
China | −0.24 | −0.34 | −0.46 | −0.47 | −0.42 | −0.10 | −0.34 | −0.43 | 0.02 | 0.04 |
Uruguay | −0.75 | −0.52 | −0.66 | −0.59 | −0.27 | 0.26 | −0.41 | −0.78 | −0.55 | −0.55 |
Table 10.
Markets for unroasted and non-decaffeinated coffee in Ecuador (in thousands of USD).
Table 10.
Markets for unroasted and non-decaffeinated coffee in Ecuador (in thousands of USD).
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
World | 1652 | 1046 | 530 | 990 | 1234 | 1124 | 1347 | 1237 | 1095 | 1430 |
Chile | 671 | 331 | 352 | 598 | 844 | 922 | 991 | 713 | 922 | 1108 |
United States of America | 154 | 527 | 92 | 122 | 121 | 68 | 107 | 110 | 86 | 92 |
France | 92 | 40 | 0 | 1 | 28 | 1 | 0 | 173 | | 50 |
Hong Kong, China | 0 | 3 | 0 | 0 | 0 | 0 | 0 | 1 | 32 | 39 |
Japan | 78 | 72 | 0 | 144 | 0 | 0 | 0 | 0 | 28 | 36 |
Others | 657 | 73 | 86 | 125 | 241 | 133 | 249 | 240 | 27 | 105 |
Table 11.
Diversification index of Ecuador’s exports.
Table 11.
Diversification index of Ecuador’s exports.
Years | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
HHI Value | 2718 | 3619 | 4801 | 4103 | 4901 | 6809 | 5736 | 3713 | 7168 | 6081 |
Table 12.
Revealed comparative advantage of Ecuador in its main export destinations.
Table 12.
Revealed comparative advantage of Ecuador in its main export destinations.
Importers | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
---|
Chile | 0.88 | 0.83 | 0.90 | 0.88 | 0.91 | 0.96 | 0.94 | 0.89 | 0.96 | 0.96 |
United States of America | −0.29 | 0.56 | −0.01 | −0.19 | −0.21 | −0.24 | −0.27 | −0.45 | −0.21 | −0.26 |
France | 0.79 | 0.68 | −1.00 | −0.76 | 0.56 | −0.73 | −1.00 | 0.88 | −1.00 | 0.68 |
Hong Kong, China | −1.00 | 0.67 | −1.00 | −1.00 | −1.00 | −1.00 | −1.00 | −0.05 | 0.95 | 0.97 |
Japan | 0.72 | 0.79 | −1.00 | 0.89 | −1.00 | −1.00 | −1.00 | −1.00 | 0.75 | 0.59 |
Table 13.
Comparison table.
Table 13.
Comparison table.
Country | Export Trend (2015–2024) | Key Growth Markets | HHI Trend | Competitiveness |
---|
Brazil | Growth from USD 5.56B to USD 11.34B (CAGR 8.25%) | Belgium (+139%), Others | Declining (1083 to 709); avg ↓2.62% | Advantage: Germany; Disadvantage: USA, Japan |
Colombia | Growth from USD 42.41M to USD 104.74M (+147%) | Chile, Panama, Others | Declining (6765 to 4700); ↓29% | Improving: Chile, Ecuador; Stable: USA; Low: Panama |
Peru | Decline from USD 1.79M to USD 1.25M (−30%) | USA, Chile, China, Ecuador | Volatile; avg ↑11.1%; peak 7937 (2022) | Consistent disadvantage in all markets; only Chile improved slightly |
Ecuador | Fluctuating trend: USD 1.65M to USD 1.43M | Chile, Hong Kong | Increasing (2718 to 6081); ↑123.7% | Advantage: Chile, Hong Kong; Disadvantage: USA, France, Japan |
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