Biofuel Dynamics in Brazil: Ethanol–Gasoline Price Threshold Analysis for Consumer Preference

Abstract

The global transition towards environmentally friendly energy sources plays a major role in addressing both energy security and climate change. Brazil is at the forefront of this transition due to its rich natural resources and increasing investments in biofuels. Therefore, this investigation examines the consumption patterns and interactions between ethanol, primarily sourced from sugarcane, and gasoline within Brazil’s energy framework. Ethanol’s renewability, reduced environmental impact, and superior combustion characteristics position it as a feasible substitute for traditional fossil fuels. Nonetheless, obstacles like competition for land use and inadequate distribution infrastructure impede its widespread acceptance. This study explores the economic interaction between ethanol and gasoline, focusing on pricing dynamics and regional influences. Using consumer preferences and the accessibility of ethanol, this research identifies a range of price ratios within which consumer preferences shift from gasoline to ethanol in various Brazilian regions. The study also classifies Brazilian states into three distinct ranges based on the ethanol-to-gasoline price ratio in 2023 for a granular analysis of the economic dynamics influencing fuel choice. The research identifies states with competitive and dominant ethanol markets by examining the interplay between ethanol market share, fuel prices, and the adoption of flex-fuel vehicles (FFVs) in the country. Lastly, the findings support the importance of regional economic conditions and the influence of price ratios on consumer behavior, highlighting that ethanol’s market share does not always correlate with favorable pricing.

1. Introduction

Since concerns about environmental issues began to increase, especially in the last three decades of the twentieth century, the development and availability of renewable energy on a global scale have been a constant trend in international research. Aligned with these environmental issues, the growing instability of the international scenario since the end of the Cold War, represented by political and military events in the Middle East, Russia, Venezuela, and other conflict points, have increased global uncertainty regarding oil supply. In addition to being a security problem, these events have led to an economic issue, marked by the continuation of high fluctuation in oil prices and creating competition among countries to replace fossil fuels with more technologically efficient and self-sufficient sources. In this context, the development of biofuels has been catalyzed, standing out as a viable option to reduce the use of fossil fuels in the global and Brazilian energy matrix.

Pursuing green energy sources is becoming increasingly important as the global community addresses the interconnected issues of energy security and climate change [1]. The primary renewable energy sources are solar, wind, hydropower, and biofuels. The last one, in particular, is seen as the best alternative in the near future for reducing the impact of fossil fuels, as it can be easily implemented without more extensive changes in current combustion engines and can have a lower environmental impact due to fewer carbon emissions. According to the United Nations UN Convention on Climate Change (2023), global levels of the predominant greenhouse gas, CO₂, have exceeded those of the pre-industrial period by 50% in 2022. Therefore, several nations are about to face severe weather patterns, including extreme heat waves, glacial melt, and heat and ocean acidification [2,3].

The predominant advantage of biofuels is the use of sources that are not exhausted and can be quickly replenished or reused as by-products in other economic activities [4,5]. They also reduce the carbon footprint associated with burning petroleum derivatives, responsible for the intensification of the greenhouse effect. The most usual biofuel production routes are based on plant and animal biomass sources associated with methanol or ethanol. Using by-products can reduce production costs, even when compared to fossil fuels, when produced on a large scale, since the waste generated in production can be reused, making the entire production chain sustainable and economically viable. Another advantage is that their composition does not contain sulfur, which means that their combustion is free of SO₂ and SO₃, oxides that cause acid rain [3].

In this context, ethanol has gained significant attention as a potential alternative to fossil fuels due to its renewable nature and lower environmental impact and is currently considered one of the most viable biofuel options to reduce greenhouse gas emissions and dependence on non-renewable energy sources [6,7]. The physical and combustion properties of ethanol make it an attractive fuel for internal combustion engines. Ethanol has a higher octane rating than gasoline, allowing higher engine compression ratios and improving thermal efficiency and power. This property is particularly advantageous for modern engines designed to maximize performance and minimize emissions [8].

In addition to its favorable combustion characteristics [9], ethanol offers several other advantages over traditional gasoline. Ethanol is biodegradable and less toxic, which reduces the risk of environmental pollution in the case of spills [10]. It also produces lower particulate emissions, contributing to improved air quality. Furthermore, ethanol can be made from various biomass sources, ranging from those with established commercial viability, including corn and sugarcane, and others with prominent results for further production expansion, like cellulosic materials, making it a versatile and sustainable fuel option [11,12].

Despite these advantages, the global adoption of ethanol as a mainstream fuel faces several challenges. One of the main obstacles is the competition for land use between food production and biofuel crops. This issue raises concerns about food security and the potential negative impact on agricultural markets. Furthermore, the infrastructure for the distribution and refueling of ethanol is not as developed as that of gasoline, which poses logistical challenges for widespread adoption [13].

Brazil, a major global producer of sugarcane ethanol, has abundant natural resources and growing investments in biofuels and is on a growing path in the global movement towards renewable energy [14]. Vandenberghe et al. [15] indicates that ethanol and gasoline, a traditional fossil fuel, are critical elements of the Brazilian energy structure. A deep understanding of consumption patterns and the dynamics between these fuel types is fundamental to designing energy strategies that promote sustainability and economic development.

Today, Brazilian ethanol production is becoming a cornerstone of the nation’s renewable energy strategy. The sector has achieved a mature production technology capable of further growth, particularly if the oil price volatility continues [3,7]. Hoeckel and Alvim [13] present an interesting econometric analysis, demonstrating that the responsiveness of ethanol supply and demand to price changes suggests its great potential for expansion as a substitute for gasoline in the Brazilian scenario. As flexible fuel vehicles can run on any blend of ethanol and gasoline, the main determinant factor for consumer choice tends to be the price ratio between these fuels. Based on this assumption, the current research aims to answer the following question: what is the price ratio range between ethanol and gasoline in Brazil at which ethanol has emerged as a competitive fuel choice?

This issue is especially relevant given Brazil’s vast automobile market, which continues to grow despite economic fluctuations. For that reason, the importance of flex-fuel vehicles (FFVs) in Brazil’s ethanol landscape cannot be overstated. Government policies aimed for better price ratios between ethanol and gasoline, aligned with the expansion of FFVs in Brazil, could significantly impact the demand for ethanol, making it a more attractive option for consumers concerned about both cost and environmental impact [8,16].

This study uses a rigorous and reproducible methodology to systematically investigate the economic relationship between ethanol and gasoline, considering both price dynamics and regional factors. Through a multi-step process, leveraging data collection and processing, cross-price elasticity, regional ethanol availability, and inflection price, this paper aims to explore the price ratio between the two fuels at which consumer preference shifted from gasoline to ethanol in each group of states, based on their FFV fleet and historical consumption data.

Given that the technical performance differential between ethanol and gasoline is approximately 68.8% [8], FFV owners typically switch their fuel preferences only if the relative price is under this ratio. Based on that ratio, the Brazilian states were divided in this paper into three groups: the First Range encompasses the states where the ethanol-to-gasoline price ratio is below 0.688; therefore, ethanol is more economically advantageous, leading consumers to prefer it over gasoline. In the following range, the price ratio varies between 0.688 and 0.788, implying a competitive balance. Consumers may choose between ethanol and gasoline based on minor price fluctuations, vehicle performance, and fuel availability, reflecting a market equilibrium where both fuels are equally viable. Lastly, in the Third Range, where the price ratio exceeds 0.788, gasoline becomes more cost-effective, discouraging ethanol use and prompting consumers to predominantly choose gasoline.

Furthermore, cross-elasticity, an economic concept that measures the sensitivity of demand for one good as a response to changes in the price of another good, is applied for additional analysis. In the context of this study, the cross-elasticity between ethanol and gasoline indicates how a change in the price of one fuel influences the demand for the other. If the cross-elasticity is high and positive, then an increase in the price of gasoline leads to a significant increase in the demand for ethanol.

However, cross-elasticity is only measured in one direction in this study—gasoline prices affecting ethanol demand—and not vice versa. This is because, while ethanol can serve as both a complement (by raising the octane rating) or a substitute for gasoline depending on blending levels, in Brazil, ethanol has been blended with gasoline at increasing rates since 1976, making ethanol primarily act as a substitute for gasoline [17]. Additionally, gasoline prices play a dominant role in the fuel market because ethanol production is intertwined with sugar production, and sugar prices can influence ethanol supply. Therefore, gasoline prices have a more direct and consistent impact on ethanol demand, while the reverse relationship is less significant. Moreover, government mandates, such as Brazil’s ethanol blend mandate, further reinforce the unidirectional influence of gasoline prices on ethanol demand.

Lastly, this paper is structured as follows. Section 2 reviews the relevant literature on the regional dynamics of ethanol and public policies in Brazil and the elasticity of the cross-price in fuel consumption. Following this, Section 3 outlines the materials and methodology employed in this study. Section 4 analyzes ethanol dynamics with the aid of cross-elasticity and the price threshold, and, finally, Section 5 concludes the paper by summarizing essential key findings and discussing their implications for future research.

2. Literature Review

This section provides an overview of the Brazilian regional dynamics of ethanol, studies that provide a summary of cross-elasticities used for the consumption of different fuels, and research gaps in the literature based on this approach.

Another point explored in the Section 2, informed by the methodology used in Bispo et al. [18] to select pertinent bibliography, revealed gaps in existing research. As summarized in

Table 1. Comparison of the related literature.

Ref.	Year	Cross-Elasticity	Gasoline	Ethanol	Regional Analysis
[11]	2022	×	✓	✓	×
[17]	2022	✓	✓	✓	×
[6]	2022	×	✓	✓	×
[19]	2022	×	✓	✓	×
[20]	2020	✓	✓	✓	×
[21]	2022	✓	×	×	×
[22]	2019	✓	✓	✓	×
[23]	2019	✓	✓	✓	×
[24]	2020	✓	✓	✓	×
[25]	2019	×	✓	✓	✓
[26]	2021	✓	✓	✓	×
[10]	2020	×	✓	✓	×
[8]	2022	×	✓	✓	×
Current Paper	2024	✓	✓	✓	✓

, previous studies have mainly focused on the effects of gasoline and ethanol on various market dynamics, such as cross-elasticity and specific impacts on fuel consumption. However, these studies have largely ignored regional heterogeneity as a compeling factor.

2.1. Ethanol Development Trajectory in Brazil

The expansion of ethanol production in Brazil has significant socioeconomic and environmental implications. Although the industry has created more secure and qualified jobs in the agro-industry and contributed to rural development, particularly in sugarcane-growing regions, it has also raised concerns about land use, food security, and environmental sustainability [7,27]. Hence, it is essential to take a balanced approach to ethanol production, ensuring that it does not compete with food crops or lead to deforestation [16,28].

The production process of ethanol involves the fermentation of sugarcane juice and molasses, followed by distillation. Advances in agricultural practices, such as developing high-yield sugarcane varieties and efficient harvesting methods, have significantly increased ethanol yields over the years [11]. Ethanol production in Brazil operates in two cycles: the first focuses on producing anhydrous ethanol, which is mixed with gasoline, and the second focuses on producing hydrous ethanol, used as a standalone fuel in FFVs [8].

The price dynamics in the ethanol market are influenced by factors such as sugar prices, oil prices, and weather conditions that affect sugarcane harvests [10]. When sugar prices are high, producers may shift more of their output towards sugar production rather than ethanol, leading to fluctuations in ethanol supply. Conversely, low oil prices can reduce the competitiveness of ethanol compared to gasoline, impacting demand. This means that ethanol is more influenced by exogenous factors than it is capable of influencing other commodities [17].

Brazil’s ethanol production is primarily based on sugarcane, with very concentrated production in a few states. As seen in

Table 2. Top 5 Brazilian states in ethanol production.

State	Ethanol Production (MM/L)	Participation
São Paulo	12,111,495	35.43%
Mato Grosso	5,713,662	16.72%
Goiás	5,412,160	15.83%
Mato Grosso do Sul	4,392,310	12.85%
Minas Gerais	2,953,543	8.64%

Based on estimates of the Brazilian National Supply Company (CONAB) [29].

, almost 90% of the production takes place in five states, all located in the central-southern region of the country. São Paulo is especially important, accounting for 35.43% of the national production of ethanol in the estimate for the 2024/2025 harvest made by CONAB [3,27,29].

Government policies and mandates heavily influence the dynamic of the ethanol market within Brazil. These policies have included tax incentives, mandatory blending requirements, and support for research and development. These practices have been instrumental in maintaining the competitiveness of ethanol against fossil fuels and encouraging investment in the sector [6].

Although Brazilian ethanol production dates back to the beginning of the 20th century, when there was pressure to diversify the uses of sugar cane, an experience that led to the first tests of alcohol as a fuel in the 1920s [19], it was only in the 1970s that significant advances were made. With the worsening of the global oil crisis, Brazil sought alternatives to its dependence on imported fuels, creating in 1975 the National Alcohol Program, commonly known as Proálcool [8], the National Alcohol Program, which encouraged the production of alcohol from sugar cane as a biofuel.

Thus, it can be said that this initiative was a milestone for ethanol production, as it involved substantial government intervention, including subsidies, price controls, and mandates for mixing ethanol with gasoline. In 1990, a policy change caused a decline in ethanol production, leading to a decade of decreased importance of ethanol in urban transportation. However, technological advances in the automotive industry have breathed new life into the sector. In 2003, automakers introduced FFVs to the Brazilian market, capable of running on any mixture of ethanol and gasoline, giving consumers the flexibility to choose their fuel according to price and availability and stabilizing the ethanol market [8]. In 2005, the Brazilian state established the National Program for the Production and Use of Biofuels, PNPB, which determined the percentage of biofuels in the national territory. The main objectives of the PNPB were to implement a sustainable biofuel production program in the country, ensuring competitive prices and increasing biofuel production [19].

The current frontier in the ethanol industry is the development of second-generation (G2) ethanol, which represents a significant advancement in the biofuels sector, addressing some important challenges associated with first-generation (G1) biofuels. Unlike G1 ethanol, which is produced from food crops such as corn and sugar cane, G2 ethanol is derived from lignocellulosic biomass, including agricultural residues, forest residues, and dedicated energy crops. In the Brazilian scenario, G2 can be produced from the remaining sugarcane biomass, generally called sugarcane bagasse, although there is competition for its use as a combustion material for energy generation [11]. Therefore, one of the main advantages of G2 ethanol is its potential to provide substantial savings in greenhouse gases (GHGs) compared to G1 biofuels and fossil fuels. Using agricultural waste and non-food biomass, G2 ethanol reduces competition for arable land and mitigates concerns related to food security and change in land use. Karp et al. [7] emphasize that G2 ethanol can achieve up to 90% reduction in GHG emissions compared to gasoline, making it a highly sustainable alternative.

Economically, G2 ethanol can contribute to rural development by creating new markets for agricultural residues and promoting the cultivation of energy crops on marginal lands. This can provide additional income streams for farmers and stimulate economic activity in rural areas. Barbosa et al. [6] discuss the potential for G2 ethanol to enhance energy security and reduce dependence on imported fossil fuels, thereby contributing to national energy strategies. Despite its promising benefits, the commercialization of G2 ethanol faces several challenges. The high capital and operating costs associated with advanced biorefineries, coupled with the complexity of the conversion process of lignocellulosic biomass, pose significant barriers to large-scale production. The achievement of economic viability requires continuous technological improvements and economies of scale [19]. In addition, developing an integrated supply chain for biomass collection, transport, and processing is crucial to the success of G2 ethanol. This includes establishing efficient logistics systems and ensuring a consistent and sustainable feedstock supply. In the Brazilian ethanol market, only two enterprises have industrial plants producing G2 ethanol, GranBio and Raízen [19].

In related works, Campos and Viglio [19] provide a review of the drivers behind the development of ethanol fuel in Brazil from a sociotechnical perspective. The authors employ a multidisciplinary methodology that integrates historical analysis, policy review, and technological assessment to understand the interplay between the social, technical, and political factors that have shaped the ethanol industry. Further research is necessary to address emerging challenges, such as sustainability concerns, economic viability, and the integration of second-generation biofuels, with more in-depth studies on the long-term impacts of ethanol production on food security, land use, and environmental sustainability.

In addition, a deeper understanding of the reasons behind Brazil’s imports of corn-based ethanol from the United States is required, as discussed by Machado Neto [17]. Neto’s study employs Autoregressive Distributed Lag (ARDL) models to compare the effects of different American ethanol mandates on Brazil’s ethanol trade balance. The analysis reveals that the American mandate has a promising effect on the Brazilian ethanol trade balance, with the cellulosic mandate having a particularly strong impact. Conversely, the Brazilian blend mandate shows negative short- and long-term effects. Given the increasing international demand for cellulosic biofuels and the ambitious goals of the US government for this sector, more research is needed to explore how Brazil can better align its domestic policies to capitalize on this growing market without compromising its ability to meet both domestic and international demand for ethanol.

Furthermore, the study by Barbosa et al. [6] aims to evaluate the strategic choices and public policies of the Brazilian sugar energy sector in light of its growth challenges and opportunities. Utilizing a survey with 56 industry experts, the authors employ a SWOT analysis integrated with the Delphi and AHP methods to capture the sector’s status, strategies, and potential public policies in R&D and “product portfolio diversification” as the top strategic options, highlighting the necessity for R&D investment to address the sector’s weaknesses and capitalize on opportunities. The authors emphasize the need for future research that combines strategy and econometric analysis to further develop their findings.

Karp et al. [7] focused on the impacts of government policies, research, and technological advances to assess the current state and prospects of Brazil’s sugarcane ethanol industry. The research highlights the importance of sugarcane ethanol in Brazil’s energy matrix and explores the industry’s socioeconomic evolution since the Proálcool program’s inception. Methodologically, the study examines historical growth rates, market dynamics, and potential future scenarios through the lens of bioethanol production and demand. Despite steady growth in bioethanol production, the paper identifies several factors influencing future expansion, such as urban transportation investments, the rise of electric vehicles, and the potential of 2G ethanol from sugarcane bagasse. The necessity for further research is underscored, particularly in optimizing existing feedstocks, balancing the production of biofuels with food and other bioproducts, and evaluating the long-term sustainability and economic viability of the bioethanol sector in Brazil.

Also addressing the potential of 2G ethanol, Algayyim et al. [11] review the economic challenges associated with using sugarcane biomass as a source of biofuel for internal combustion engines, with a focus on ethanol and acetone–butanol–ethanol (ABE) production. The paper discusses the technological processes involved in the conversion of sugarcane biomass to biofuels and evaluates the economic viability of these processes. The authors highlight the potential benefits and barriers to the widespread adoption of sugarcane-based biofuels and emphasize the commercial significance of advancing treatment methods. More research is needed to improve the competitiveness and efficiency of biofuel production from sugarcane biomass.

In Brazil, ethanol–gasoline thresholds for FFVs and corresponding vehicle fuel economy ratios (VFER) for various models were analyzed in a study by Nascimento Filho et al. [8]. The study emphasized the potential consumer pitfalls in using a single fuel economy ratio for all FFVs and advocated for better consumer information, technological advancements in vehicle engines, and further research to bridge the FFV energy-efficiency gap. Therefore, the future of the Brazilian ethanol industry must navigate challenges such as market volatility, infrastructure limitations, and the need for continuous policy support. Developing a robust infrastructure for the distribution of ethanol and addressing logistical challenges are crucial to expanding the market. Similarly, maintaining favorable policies and incentives will be essential to sustain the industry’s growth and competitiveness in the global market [8].

2.2. Cross-Price Elasticity in Fuel Consumption

Positive cross-price elasticity indicates substitute goods, where an increase in the price of one good leads to an increase in the demand for another [21]. Negative cross-price elasticity indicates complementary goods, where an increase in the price of one good results in a decrease in the demand for another, and zero cross-price elasticity suggests that the goods are unrelated [21]. Therefore, cross-price elasticities are used in consumer behavior analysis to understand market dynamics and pricing strategies between different goods.

The cross-price elasticity of fuel consumption in Brazil is influenced by factors such as income levels, price differences, and the introduction of flexible-fuel technology. Studies show that cross-price elasticities become positive, significant, and increasing after the larger market penetration of FFVs, approximately three years after their introduction [8,20,21,22]. Regional income disparities and proximity to the 70% relative price mark between ethanol and gasoline also influence the elasticity of demand for ethanol [20]. Additionally, spatial panel data models emphasize the competition between gasoline and ethanol, highlighting the importance of spatial autocorrelation and flex-fuel technology in shaping regional fuel consumption patterns [22].

The widespread adoption of alternative energy sources, such as ethanol, is closely tied to the availability of alternative fuel vehicles like FFVs. Flex engines, which can run on both ethanol and gasoline, provide consumers with the flexibility to switch between fuels based on price advantages. This adaptability is crucial in the context of fluctuating fuel prices, as it allows vehicle owners to optimize their fuel expenses without compromising performance [25]. As more alternative fuel vehicles enter the market, the demand for alternative fuels, including ethanol, increases, further driving the adoption of these energy sources.

In addition, the cross-price elasticity of fuel consumption plays a key role in shaping the demand for various types of vehicles. The cross-price elasticities of petrol, diesel, electric battery, and plug-in hybrid vehicles significantly influence consumer decision-making [26]. Price elasticity levels vary between nations, with developing countries showing greater responsiveness to price changes. This suggests that fuel-related policies could strongly impact the adoption of alternative energy sources, shaping energy usage patterns and environmental outcomes.

Finally, in an analysis of supply and demand for hydrous ethanol in Brazil from January 2012 to December 2016, Hoeckel and Alvim [13] highlighted Brazil’s leadership in sugarcane ethanol production and its advanced production technology. The study provided insights into supply and demand elasticities across Brazilian regions, which can inform scenarios for expanding ethanol production as a gasoline substitute. Future research should compare Brazil’s ethanol market dynamics with other major ethanol-producing countries, such as the USA.

2.3. Research Gaps

Despite the body of literature reviewed in Section 2, collected using the methodology used by Bispo et al. [18], the examination revealed gaps in the existing research. As summarized in Table 1, previous studies have mainly focused on the effects of gasoline and ethanol on various market dynamics, such as cross-elasticity and specific impacts on fuel consumption. However, these studies have largely overlooked a deeper understanding of regional analysis as a compeling factor.

In the study by Algayyim et al. [11], both gasoline and ethanol were analyzed, but cross-elasticity and regional analysis were not included. Similarly, Nascimento Filho et al. [8] and Barbosa et al. [6] focused on gasoline and ethanol without considering cross-elasticity or regional analysis. These studies mainly contributed to the explanation of fuel consumption patterns; however, they lacked conclusions into how changes in the price of one fuel affect the consumption of the other and how these patterns vary regionally.

The works by Machado Neto [17] and Uchoa et al. [20] included analyses of cross-elasticity, gasoline, and ethanol but did not address regional analysis. For example, these studies provided a deeper view of the relationship between ethanol and gasoline prices and consumption. However, they still missed the regional disparities that could impact Brazil’s understanding of fuel consumption behavior.

Moreover, some studies, such as those by Campos and Viglio [19] and Head and Mayer [21], did not include cross-elasticity or regional analysis. For example, Head and Mayer [21] focused on other factors, such as industry-level trade counterfactuals, particularly using constant elasticity of substitution (CES) models to address multi-product oligopolies and tariff pass-through elasticities. However, they did not examine the interplay between ethanol and gasoline markets or account for regional disparities, which are crucial in understanding fuel substitution dynamics in Brazil.

Interestingly, the study by Brito et al. [25] stands out as one of the few before the current paper to include regional analysis. However, it did not consider cross-elasticity. This study highlighted the importance of understanding regional variations in fuel consumption, which is crucial for formulating effective energy policies. Most studies do not analyze the ethanol market by region rather than by state. This study also aims to incorporate the distance from the producing area as a determinant factor of consumer preferences, since the government passes the logistics cost on to the customer.

In summary, the current paper heavily addresses all four critical components: cross-elasticity analysis, gasoline and ethanol analyses, and regional analysis. Additionally, this work shows a gap in the literature in this domain. This approach also allows for a supplementary understanding of how price changes in one fuel affect the consumption of the other. It also configures the overall consumption trends of both fuels and how these trends differ across various regions in Brazil. Therefore, incorporating regional analysis, the current work acknowledges the economic, social, and infrastructure factors that influence fuel consumption in different parts of the country, as well as analyzing all states of the country individually to provide policymakers with more ready-to-use information for decision-making.

3. Materials and Methods

The methodology described involves a thorough multi-step process that integrates diverse analytical methods, such as data collection, data processing, and the examination of cross-price elasticity. An important element of this methodology is evaluating the availability of ethanol on a regional scale and the determination of the price point at which consumers might transition between gasoline and ethanol.

The framework approach aims to analyze the economic relationship between ethanol and gasoline, shedding light on how price changes and regional availability impact consumer behavior and market dynamics. In this context, Figure 1 illustrates the methodological framework used.

Also, the framework is organized into five primary sections, Section 3.1, Section 3.2, Section 3.3, Section 3.4 and Section 3.5, each representing distinct stages within the research process, from data collection to economic analysis. Furthermore, this procedure not only explores the direct price elasticity between ethanol and gasoline but also takes into account broader regional variables that could influence the viability of ethanol as an alternative fuel.

Finally, the framework applied encompasses those aspects and allows for an overview of the interaction between these two energy sources in different geographical settings. Consequently, it provides conclusions for decision-makers and market stakeholders interested in potentially shaping the acceptance of ethanol as a sustainable fuel choice in a mosaic regional market.

3.1. Data Collection and Sources

Data were collected from the Brazilian National Agency for Petroleum, Natural Gas and Biofuels (ANP), and the National Traffic Secretariat (Senatran). Monthly data on ethanol and gasoline were collected from 2003 to 2023, but since the data for the FFV were only available between 2014 and 2024, that was the analyzed time span. The dataset encompassed production prices and consumption volumes for both ethanol and gasoline over the specified period.

Furthermore, post-collection, the dataset underwent processing to ensure its accuracy. Data processing procedures involved cleaning to identify and remove inconsistencies, such as erroneous entries, duplicates, and missing values. This step also included validating the data against known benchmarks and cross-references. Moreover, data normalization was carried out to standardize the format and enable integration across different variables and time periods.

Following initial cleaning and normalization, additional procedures were implemented to improve the reliability and usability of the data set. Outlier detection methods were applied to identify and address abnormal data points that could distort analysis results. These outliers were contextually examined to determine whether they represented genuine anomalies or critical data points requiring further investigation. After this, the data were segmented by region and fuel type to facilitate granular analysis.

Time series analysis techniques were employed to address any gaps or irregularities in the monthly data, particularly the missing consumption and price data for September 2020 and all months of 2021 for the state of Acre, to ensure temporal consistency. This included interpolation methods to estimate the missing values and smoothing techniques to minimize short-term fluctuations and highlight long-term trends. By filling these data gaps, the analysis maintained accuracy despite the incomplete dataset. The were data was then organized into a structured format, suitable for statistical analysis and modeling purposes.

3.2. Determination of National Vehicle Fleet

The size of the active vehicle fleet was determined by analyzing vehicle registration records in each Brazilian state by year of manufacture, obtained from the Brazilian National Traffic Secretariat (Senatran). These records provided an overview of the number of vehicles registered in different regions and the composition and distribution of the national fleet.

However, it is important to note that the official registration data may not fully capture the actual number of vehicles in active circulation. This discrepancy arises because of the bureaucratic complexity involved in the process of declaring a vehicle to be unfit for circulation. As a result, many vehicles that are no longer roadworthy remain listed in the registry and increase the apparent size of the active fleet. Therefore, the determination of vehicle scrappage, which would typically adjust for such inactive vehicles, was not assessed in this study due to discrepancies in the database.

The absence of data on scrapped vehicles leads to an overestimation of the number of gasoline-only cars. This occurs because, as time progresses, the percentage of new FFVs being produced is proportionally higher than that of gasoline-only models. Without accounting for the removal of older, gasoline-only vehicles from the fleet, the data gives a distorted view of the current market, inflating the number of gasoline-only cars still in circulation.

Moreover, with the collected data, an analysis of consumer preferences was conducted, focusing on the relationship between price ratios and fuel choice. The underlying assumption was that if more than half of the state’s vehicle fleet were powered by ethanol, the price ratio between ethanol and gasoline would have been more favorable, thereby influencing consumer behavior to shift away from gasoline consumption. This assumption rests on the premise that consumers are sensitive to fuel prices, and a lower ethanol-to-gasoline price ratio would incentivize a preference for ethanol, particularly in states where the fleet composition reflects a higher proportion of FFVs. Interestingly, this analysis provides a basis for understanding regional variations in fuel consumption patterns and highlights the economic factors that drive vehicle fleets.

3.3. Determination of Consumption Ranges

Each Brazilian state is categorized according to consumption ranges as outlined by Nascimento Filho et al. [8]. The technical performance differential between ethanol and gasoline is approximately 68.8% [8], with slight variations depending on the vehicle model. Owners of FFVs tend to switch their fuel choice only if the relative price exceeds this threshold, defining when ethanol or gasoline becomes more advantageous. A 10% gap is used for defining these ranges to reflect the variability in the ethanol–gasoline price ratio across regions in Brazil, as noted in previous studies [30]. This range accommodates minor fluctuations and ensures that consumer responses to price changes are captured effectively. The study by Orellano et al. [30] highlights that regions where the price ratio nears this 70% threshold exhibit higher elasticity, making small price shifts critical to consumer choice. In contrast, regions with ratios outside this range show less sensitivity, underscoring the relevance of the chosen 10% gap.

Subsequently, three distinct consumption ranges were delineated, each reflecting a different range of price ratios between ethanol and gasoline. The First Range includes states where the price ratio of ethanol to gasoline is less than 0.688, indicating an economic incentive for consumers to prefer ethanol to gasoline. In these states, ethanol is the more cost-effective option, encouraging higher biofuel consumption rates.

The Second Range represents states where the price ratio ranges from 0.688 to 0.788 (10% range above the lower bound [8,30]), suggesting a competitive balance between the two fuels. In these regions, consumers may switch between ethanol and gasoline based on minor fluctuations in relative prices, vehicle performance considerations, and availability. This range reflects a market equilibrium where both fuels are equally viable options for consumers.

Lastly, the Third Range encompasses states where the price ratio exceeds 0.788, favoring gasoline consumption due to its relative cost advantage over ethanol. In these states, the higher relative price of ethanol discourages its use, leading consumers to choose gasoline predominantly. This range highlights the economic disincentives for ethanol use and underscores the importance of price competitiveness in fuel choice behavior.

3.4. Economic Analysis of Ethanol and Gasoline in Brazil

Lastly, an analysis of the dynamics of ethanol and gasoline was implemented in the country. This part involved a comparative assessment of ethanol and gasoline prices over time. The cross-elasticity aspects were also employed from a consumer perspective, considering the efficiency of ethanol versus gasoline.

Within this section, there is a further breakdown into three distinct but interconnected segments. The first segment is dedicated to examining the historical patterns of ethanol utilization compared to gasoline, offering a framework for the evolution of consumption trends in different time periods.

Subsequently, the second segment involves the thresholds of the ethanol/gasoline price ratio, identifying the pivotal price levels that play a role in shaping consumer preferences between the two types of fuel. Lastly, the third segment conducts an evaluation of the cross-price elasticity, a metric that evaluates the extent of responsiveness of ethanol demand to fluctuations in gasoline prices.

First, the historical percentage of ethanol consumption was examined to understand the trends relative to gasoline over the study period from 2003 to 2023. By tracking the proportion of ethanol consumed in relation to gasoline, the study identified patterns and shifts in consumer preferences.

Second, the analysis of ethanol/gasoline price ratio thresholds was important in determining the points at which consumers switch between ethanol and gasoline. Given the performance differential of 68.8% between the two fuels, the study investigated the specific price ratios that prompt consumers to favor one fuel over the other. This involved identifying the three distinct consumption ranges: states with a price ratio less than 0.688 favoring ethanol, states with a ratio between 0.688 and 0.788 indicating a competitive balance, and states with a ratio above 0.788 favoring gasoline.

Third, cross-price elasticity was assessed to measure the responsiveness of ethanol demand to changes in gasoline prices. Cross-elasticity of demand measures the responsiveness of the quantity demanded for one good when the price of another good changes. This concept primarily focuses on the relationships between different goods and identifies whether they are substitutes or complements.

Moreover, to analyze cross-elasticities, a diversity of aspects of economic theory must be considered. Primarily, demand theory is foundational and highlights the law of demand and the relationship between substitutes and complements. On the other hand, substitutes exhibit positive cross-elasticity, where an increase in the price of one good leads to an increase in the demand for another. Conversely, complements exhibit negative cross-elasticity, where an increase in the price of one good results in a decrease in the demand for another.

3.5. Logistics Modeling and Freight Cost

To address the matter of ethanol logistics, the city of Ribeirão Preto was set to generically be the origin of the loads, since it is the mid-point city from the five states presented in Table 2 that represent 90% of the national production. The Google Maps API was used to calculate the minimum road distance between Ribeirão Preto and each Brazilian state capital to estimate a freight cost based on [31]. The document provides a linear function to determine the average cost of the transportation in BRL per ton of liquid bulk, such as fuels, crude oil, and vegetable oils and is given by Formula (1):

$$Cost\left(BRL\right)/\mathrm{ton}=16.61+0.21\times distance \left(\mathrm{km}\right)$$

(1)

It is also important to note that the five leading states from Table 2 were excluded from this calculation, as they are not dependent on imports from other states for ethanol supply. Similarly, the logistics of gasoline distribution in Brazil were not computed, as gasoline production is decentralized and relatively well distributed across the country. This contrasts with ethanol, for which production is more centralized, making logistics a more critical factor in its pricing. Therefore, calculating logistics dynamics for gasoline was considered less relevant compared to calculating logistics dynamics for ethanol in the present study.

4. Analysis and Results

This section demonstrates the analysis and results of the implemented methodology. It also presents a breakdown of ethanol and gasoline consumption dynamics across Brazil.

4.1. Ethanol–Gasoline Market by Price Ratio Clusters

Each Brazilian state was classified according to a range corresponding to the average price ratio of fuels in 2023. The decision to use only 2023 for the calculation was made to ensure consistency in the analysis. By focusing on the most recent year, the data reflect current market conditions, capturing recent fluctuations in fuel prices, production, and distribution factors. This approach avoids potential distortions from historical price variations, especially those caused by the pandemic, which severely disrupted fuel markets through supply chain interruptions, reduced demand, and price volatility.

The First Range includes states where the price ratio is below 68.8%. The Second Range encompasses states with a price ratio between 68.8% and 78.8%. Finally, the Third Range comprises states where the price ratio exceeds 78.8%. The categorization of each state by its price ratio can be seen in

Table 3. States and price ratios in 2023.

State	Price Ratio (2023)	Range
Acre	0.740	Second Range
Alagoas	0.759	Second Range
Amapá	1.022	Third Range
Amazonas	0.721	Second Range
Bahia	0.756	Second Range
Ceará	0.794	Third Range
Distrito Federal	0.704	Second Range
Espírito Santo	0.773	Second Range
Goiás	0.684	First Range
Maranhão	0.839	Third Range
Mato Grosso	0.623	First Range
Mato Grosso do Sul	0.709	Second Range
Minas Gerais	0.692	Second Range
Pará	0.823	Third Range
Paraíba	0.750	Second Range
Paraná	0.711	Second Range
Pernambuco	0.767	Second Range
Piauí	0.782	Second Range
Rio de Janeiro	0.770	Second Range
Rio Grande do Norte	0.794	Third Range
Rio Grande do Sul	0.867	Third Range
Rondônia	0.804	Third Range
Roraima	0.843	Third Range
Santa Catarina	0.806	Third Range
São Paulo	0.676	First Range
Sergipe	0.788	Second Range
Tocantins	0.772	Second Range

.

This type of classification allows for a granular analysis of the regional variations in fuel pricing, facilitating targeted policy interventions and economic assessments. Therefore, this stratification is imperative to understanding the dynamics of fuel economics in different states, aiding in the formulation of strategies to address disparities and enhance the efficiency of the fuel market.

Moreover, by categorizing states into these pricing ranges, the methodology provided an overview of the regional understanding of fuel and the economic factors influencing consumer behavior. This categorization is helpful for policymakers aiming to design targeted interventions that promote ethanol usage and reduce dependence on fossil fuels. In addition, understanding these consumption patterns also helps stakeholders in the energy sector forecast demand, plan supply logistics, and develop strategies to enhance the adoption of more sustainable fuel options.

To this extent, Figure 2 illustrates the distribution of three distinct ranges across the Brazilian territory. The ranges are categorized into First Range (green), Second Range (yellow), and Third Range (red).

The First Range is primarily focused on the central and southern regions, encompassing states like Goiás, Mato Grosso do Sul and São Paulo. The Second Range covers a wider area, including parts of the North, Northeast, and Southeast, such as Bahia, Tocantins, and Minas Gerais. The Third Range is mainly distributed across the northernmost and southernmost states, including Roraima, Acre, and Rio Grande do Sul.

This type of distribution is responsible for emphasizing the regional disparities and offers a geographical overview for further examination in this study. It is also possible to address the fact that the concentration of the First Range in the central and southern regions implies a level of uniformity in these areas, which could indicate shared economic, social, or environmental characteristics. Moreover, the coverage of the Second Range and the nature of the Third Range may signify varying levels of development and local circumstances.

Conversely, pertaining to the ethanol production in Brazil, Figure 3 shows the map distribution of it in the country. This map utilizes a gradient color scheme to represent varying ethanol production levels across different states. Darker shades indicate higher production volumes, while lighter shades signify lower ones.

Notably, the states of São Paulo, Goiás, and Mato Grosso exhibit the highest levels of ethanol production, as indicated by the darkest shades on the map. In contrast, states in the northern and southern regions, such as Roraima and Rio Grande do Sul, display lower production volumes, characterized by the lightest shades.

This distribution highlights the concentration of ethanol production in the central and southeastern regions of Brazil and suggests the presence of favorable conditions for ethanol production, such as climate, soil quality, and agricultural infrastructure. Also, these geographic disparities in ethanol production are critical to comprehend regional economic dynamics, the distribution of ranges in Brazil, and the formulation of policies aimed at optimizing ethanol output across the country, as the lack of proper supply structure inflates the price in certain locations further from production centers.

The analysese in Figure 2 and Figure 3 reveal a geographic correlation between the distribution of the ranges and ethanol production in Brazil, where the central and southeastern regions align with the highest ethanol production areas, particularly in states like São Paulo, Goiás, and Mato Grosso. This reinforces the major role played by the lack of proper distribution from production centers to distant states, despite other regional socioeconomic characteristics.

In addition, this overlap suggests that regions with higher development indicators, as implied by their classification in the First Range, are also leading in ethanol production. Conversely, states in the Third Range (red), which are spread across the northernmost and southernmost parts of Brazil, show lower ethanol production levels and thus need to have it transported from Ribeirão Preto’s distribution center, leading to a higher cost for the consumer since there is no governmental subsidy for its logistics. Figure 4 shows how expensive it is to transport liquid bulk to each Brazilian state, departing from São Paulo. The states that are shown in white belong to the list from Table 2 and are able to meet their demand internally. It is also possible to refer to Figure 4 to prioritize which states would need a higher subsidy for ethanol transportation to make the ethanol–gasoline price ratio reasonable.

4.2. Competitiveness of Ethanol in the Fuel Market

A further distinction was made to analyze the competitiveness of ethanol using the FFV fleet as the threshold trigger for classifying each Brazilian state in either a competitive or dominant ethanol market. For a state to be considered competitive, the ethanol market share should cross the line that denotes half of the FFV fleet in the state at least once. If the ethanol market share crosses the line that represents the whole FFV fleet, it is considered to have a dominant ethanol market. It is important to highlight that this threshold was chosen because the FFV fleet is calculated considering only the vehicles that have the possibility of chosing between these two fuels.

Therefore, Figure 5 demonstrates the representation of how variables have evolved over time and endorses the interplay between ethanol market share, fuel prices, and the adoption of FFVs in states where the price ratio of ethanol to gasoline is below 68.8%. The blue line represents ethanol’s market share, while the green line shows the price ratio between ethanol and gasoline. The red line indicates half of the participation of FFVs within Otto cycle vehicles, and the dashed green line denotes the price mean, which is 0.673.

In this context, the FFV fleet serves as a threshold for categorizing a state’s ethanol market as either competitive or dominant. For a state to be classified as having a competitive ethanol market, the ethanol market share must cross the line, indicating half of the FFV fleet at least once. If the ethanol market share exceeds the line representing the entire FFV fleet, the state is considered to have a dominant ethanol market. To this extent, the threshold discovery is an earnest analysis because the FFV fleet is calculated based on vehicles capable of utilizing both ethanol and gasoline.

Moreover, for Figure 6, the FFV fleet is a benchmark for categorizing the Second Range of aggregated states’ averages. In the Second Range, with a price ratio between 68.8% and 78.8%, the ethanol market share is slightly higher and more variable than in the Third Range.

The price ratio fluctuates around this range and reflects a balanced fuel price dynamic. As can be observed, the FFV participation continues to grow and suggests an increasing flexibility of fuel choice. In addition, this range indicates that the states exhibit a competitive ethanol market, where ethanol begins to gain a foothold.

For Figure 7, in cases where the price ratio is 78.8% or above, the market share of ethanol continues to exhibit low levels consistent with the elevated price ratio. The price ratio surpasses 78.8%, which indicates an increased cost of ethanol in comparison to gasoline. Despite the prevalence of FFV adoption, it does not result in a substantial surge in the market share of ethanol. This implies that even with the existence of FFVs, ethanol remains a minor player, possibly due to unfavorable pricing circumstances.

Therefore, the results derived from Figure 7 demonstrate that ethanol’s market share may not increase in accordance with the decay in the ethanol-to-gasoline price ratio. This underscores the notion that various other variables play a role in determining ethanol’s competitiveness and market dominance. The existence of FFVs hints at the potential for expansion in the ethanol market, especially in regions where the price ratio is more advantageous. Nevertheless, the dominance appears to hinge on factors beyond the presence of FFVs, as the chart indicates that for the analyzed range, the average price ratio is 86.2% and the area between the red and blue lines is greater than the one seen in Figure 6, which has an average price-ratio of 78.1%.

Consequently, the dominant Brazilian states for the ethanol market are Goiás, Mato Grosso, and São Paulo, which demonstrate the highest production levels and market influence. Admittedly, these states have favorable conditions, such as suitable climates, advanced agricultural infrastructure, and robust supply chains, which contribute to their dominance in the ethanol industry.

Conversely, competitive Brazilian states, including Mato Grosso do Sul, Minas Gerais, Paraíba, Paraná, and Rio de Janeiro, exhibit material but relatively lower production levels. In general, these states play a crucial role in the market and provide contributions while facing competition from the dominant states. This reiterates the interplay between the state production and its price for the final consumer.

4.2.1. States with Dominant Ethanol Markets

The states with dominant ethanol markets are the ones encompassed in the First Range, which are Goiás, Mato Grosso, and São Paulo. Therefore, the following figures were generated with the objective of understanding the behavior of the price ratio curve, which enables the delineation of an ideal scenario to assess the impact of the price ratio on market share behavior. In these states, ethanol presents a more attractive alternative to gasoline, even when efficiency differences between the two fuels are not factored in. Local production and distribution dynamics create an environment where FFV owners have the flexibility to choose between ethanol and gasoline, driven largely by personal preference rather than cost. This is due to a balanced price ratio and comparable fuel efficiency, making the two fuels nearly perfect substitutes. By analyzing these markets, we can better understand whether the limited adoption of ethanol as the dominant fuel is primarily a matter of consumer preference or if it stems from economic factors, such as pricing.

To this extent, Figure 8 illustrates the temporal evolution of fuel dynamics in the state of Goiás from 2014 to 2024. The green line represents the price ratio of ethanol to gasoline (Eth./Gas.), with the dashed horizontal line indicating the average price threshold at 0.660, considering only the values where the blue line is above the red line. The dashed lined was included as a reference point to provide a clearer understanding of the magnitude of changes in the price ratio. Additionally, the red line signifies the involvement of FFVs within the Otto cycle vehicle fleet, displaying a consistent upward trajectory.

Distinctly, the market share of ethanol encounters notable variability, characterized by peaks and troughs that point to responsiveness to diverse factors like price changes, policy adjustments, and consumer inclinations. The ethanol-to-gasoline price ratio remains in proximity to the average threshold, influencing ethanol’s competitiveness in the marketplace. The increasing pattern in FFV participation implies a rising acceptance of vehicles capable of utilizing ethanol, potentially steered by technological progressions and regulatory encouragements for alternative fuels.

To this extent, it is possible to address in Figure 9 the temporal evolution of fuel dynamics in the state of Mato Grosso from 2014 to 2024. The dashed green line marks the price threshold mean at 0.620.

The graph reveals that the ethanol market share fluctuates over the period, with peaks around 2019 and subsequent decreases thereafter. On the other hand, the price ratio exhibits substantial volatility, generally staying above the price threshold mean of 0.620, particularly in periods around 2015 and 2023. The participation of FFVs shows a steady upward trend, which indicates a prevalence of these vehicles in Mato Grosso’s vehicle fleet over the years since the ethanol market share is 56.4% of the time above the FFV line.

Moreover, Figure 10 represents the state of São Paulo. The depiction also showcases the development of the market dynamics of ethanol in the region of São Paulo from 2014 to 2024.

The blue line denotes the ethanol market share, which illustrates major fluctuations throughout the timeframe. However, despite the instability, there is an evident downward trajectory until the middle of 2022, followed by a modest rise towards 2024. The red line, which represents the FFVs’ participation among Otto cycle vehicles, displays a consistent upward pattern, indicating a gradual escalation in interest in these types of vehicles.

The green line corresponds to the price ratio between ethanol and gasoline, while the green dashed line corresponds to the mean value of the months at which the market share surpasses the whole FFVs’ participation among Otto cycle vehicles. The involvement rate seems to exhibit an inverse correlation with the ethanol market share, as higher market shares align with periods of reduced price ratio.

To this extent,

Table 4. Percentage of time the ethanol market share surpassed the state’s FFV.

State	Percentage of Months
Mato Grosso	56.91%
São Paulo	45.53%
Goiás	32.52%

shows the percentage of time each dominant state had its ethanol market share above the entire FFV along the analyzed years.

Mato Grosso led, with ethanol surpassing the FFV threshold 56.91% of the time, which indicates a strong market presence. São Paulo followed with 45.53%, showing significant but slightly lower ethanol dominance. On the other hand, Goiás had the lowest percentage at 32.52% and reflects more frequent fluctuations below the FFV threshold and suggests a less consistent ethanol market share compared to the other states.

Therefore, Figure 11 presents the comparison between ethanol markets and price ratio in the dominant states. These states are Goiás, Mato Grosso, and São Paulo, representatives of the southwest and midwest of Brazil. Each data point represents a unique observation within these states.

The ethanol market share is plotted on the y-axis, while the price ratio of ethanol to gasoline is plotted on the x-axis. The scatter plot shows a negative correlation between the ethanol market share and the price ratio across all three states, indicating that as the price ratio of ethanol to gasoline increases, ethanol’s market share tends to decrease. The data points for Goiás are marked in blue, for Mato Grosso in green, and for São Paulo in teal.

Subsequently, Figure 11 underscores the variability in the dominant market and reflects the economic and consumer dynamics in these three states: the number of data points above the green line and to the left of the red line is significantly higher than the ones on the right of the red line, indicating that ethanol market is stronger when the price ratio is lower than the average in these states. To this extent, it is possible to note that the average value for the price ratio in these three states was 67.3%, which suggests that this could be a lower bound for the price ratio between these fuels in order to make ethanol dominant in a state.

4.2.2. Competitive Market States

Regarding the competitive states, an analysis was conducted wherein these states were meticulously scrutinized and ultimately selected based on the intersection point between the red and blue lines, as depicted in the visual representations provided below. In the context of this particular category, the benchmark utilized for this evaluation was determined to be equivalent to fifty percent of the total number of vehicles within the FFV fleet.

Figure 12 shows that the ethanol market share (blue line) remains relatively low throughout the period, with minor fluctuations and no significant upward trend. The price ratio (green line) remains consistently above the threshold mean of 0.693, indicating a relatively high cost of ethanol compared to gasoline over most of the period. The participation of FFVs (red line) shows a gradual but steady increase, suggesting a slow adoption rate of these vehicles in Paraíba.

Also, Figure 12 shows the persistent challenges in increasing ethanol market share in Paraíba, despite the rise in FFV adoption, mainly due to the unfavorable price ratio of ethanol to gasoline. Similarly, the ethanol market share is above the FFV line 2.4% of the time. Therefore, the average value for the ethanol–gasoline price ratio in the state, in which the ethanol market share is above half of the FFV, was 69.3%.

For the eight competitive states (Goiás, Mato Grosso, Mato Grosso do Sul, Minas Gerais, Paraíba, Paraná, Rio de Janeiro, and São Paulo), the average ethanol–gasoline price ratio was 67.8%, which suggests that this could be an upper bound for the price ratio between these fuels in order to make the market competitive.

4.2.3. Dominant Gasoline Market States

The dominant gasoline states were filtered based on the intersection between the red and blue lines in the figures below. For this class, the threshold considered was also half of the FFV fleet.

Figure 13 illustrates that the ethanol market share (blue line) remains extremely low throughout the period, exhibiting almost no fluctuations and no significant upward trend. This suggests a persistent lack of consumer preference for ethanol in Amapá. The price ratio (green line) consistently stays above the threshold mean of 0.788, indicating that ethanol is more expensive than gasoline for the entire period. Therefore, the high relative cost is a likely deterrent to ethanol adoption among consumers.

Meanwhile, FFV participation shows a slow increase. This suggests that while the fleet of vehicles capable of using ethanol is growing, albeit slowly, it is not translating into increased ethanol usage, likely due to the unfavorable price dynamics.

The consistent gap between the price ratio and the threshold mean shows the economic barrier that prevents a shift towards ethanol in the region. Additionally, the low volatility in ethanol market share further underscores the strong influence of price on fuel choice and emphasizes the need for price incentives or policy interventions to enhance ethanol’s competitiveness in Amapá and other states that pertain to the last range.

Table 5. Percentage of time the ethanol market share surpassed half of the state’s FFV.

State	Percentage of Months
Goiás	100.00%
Mato Grosso	100.00%
São Paulo	100.00%
Paraná	66.67%
Minas Gerais	60.98%
Mato Grosso do Sul	10.57%
Rio de Janeiro	4.07%
Paraíba	2.44%

shows the percentage of time each competitive state had its ethanol market share above half of the FFV during the analyzed years.

4.3. States’ Price Threshold for Consumer Preference

For the states where any number of crossings occurred between the ethanol market share and half the FFV fleet, the threshold condition was used. In these cases, the price ratios were collected to estimate an ideal average price ratio between ethanol and gasoline in each of these states, as shown in

Table 6. Ethanol–gasoline price ratio threshold for each Brazilian competitive state.

State	Price Ratio Threshold
Goiás	68.78%
Mato Grosso	64.64%
Mato Grosso do Sul	67.21%
Minas Gerais	67.24%
Paraíba	69.28%
Paraná	70.67%
Rio de Janeiro	68.65%
São Paulo	68.48%

. In this scenario, this number shows the inflection point at which consumers began choosing ethanol over gasoline, indicating the average price ratio at which ethanol becomes the preferred fuel option for a significant portion of the state market.

Mato Grosso exhibits the lowest threshold at 0.646, which indicates that ethanol needs to be necessarily cheaper than gasoline to gain market share in this state. In contrast, Paraná has the highest threshold at 0.707, which suggests a higher tolerance for ethanol prices compared to gasoline.

Other states, such as Goiás and Rio de Janeiro, have thresholds close to 0.688 and 0.686, respectively, and indicate a moderate competitiveness of ethanol. Sao Paulo, one of the largest and economically significant states, has a threshold of 0.685, reflecting its balanced fuel market dynamics.

Moreover, the cross-elasticities are presented in

Table 7. Cross-price elasticity in Second Range states.

State	Average Cross-Price Elasticity
Distrito Federal	13.23
Espírito Santo	6.99
Piauí	3.08
Bahia	2.60
Mato Grosso do Sul	2.53
Acre	2.47
Paraná	2.20
Minas Gerais	2.04
Alagoas	1.45
Pernambuco	1.35
Paraíba	1.28
Amazonas	1.18
Rio de Janeiro	0.19
Sergipe	−1.88
Tocantins	−3.93

. To address the issue of some states having an infinite average cross-price elasticity, the calculation method was adjusted. For instance, when the variation in the average price was less than BRL 0.01, the cross-price elasticity was set to zero. This decision was taken to avoid distortions in the data caused by minimal price fluctuations that do not meaningfully reflect consumer behavior. Furthermore, states where the average cross-price elasticity remained infinite after this adjustment were excluded from the analysis, ensuring that the final dataset only included values that are interpretable for the study.

The Distrito Federal exhibits the highest average cross-price elasticity at 13.23, which indicates a strong substitutability between the two goods. Espírito Santo follows with a value of 6.99, and Piauí registers an average of 3.08. Other states, such as Bahia (2.60), Mato Grosso do Sul (2.53), and Acre (2.47), also show positive but moderate substitutability. Paraná, Minas Gerais, Alagoas, Pernambuco, Paraíba, and Amazonas display lower positive elasticities, ranging from 2.20 to 1.18, suggesting weaker substitution effects. Rio de Janeiro, with an average cross-price elasticity of 0.19, shows minimal substitutability, perhaps because this state has a significant supply of natural gas for vehicles, which might inhibit ethanol’s substitutability potential.

On the other hand, Sergipe and Tocantins exhibit negative average cross-price elasticities, with values of −1.88 and −3.93, respectively. These negative values typically suggest complementarity, where an increase in the price of one good would lead to a rise in the demand for another. However, in these states, the expected complementarity is not observed. Rather, the effects of crop seasonality are strongly observed, as the price ratio rises between January and April and decays right after the harvest. For these states, it was observed that the price ratio increases a little while the demand has a negative variation. This leads to a highly negative cross-elasticity for these months, shifting the annual time series down. If these months are excluded from the calculation, the cross-elasticity for these states is positive, indicating a substitutability relationship between these goods. This discrepancy suggests that other factors may influence consumer behavior in these regions, preventing the typical complementary relationship from being verified.

4.4. Main Research Results

• Price Elasticity and Regional Influences: It was observed that the price elasticity between ethanol and gasoline varies significantly between regions, being influenced by distance from production centers, relative fuel prices, and the penetration of flex-fuel vehicles. Positive cross-price elasticities in demand were found in states where the price ratio made ethanol and gasoline an equally viable option for consumers, which is consistent with economic theory. This result suggests that the relationship between the two goods exhibits substitutability that would result in a positive cross-price elasticity.
• Impact of Flex-Fuel Vehicles: The introduction and adoption of flex-fuel vehicles play a significant role in consumer preferences, shifting the demand between ethanol and gasoline. Approximately three years after their introduction, the preference for ethanol increases as the market adapts to the new technology. A third topic noted that region-specific economic conditions play a key role in determining ethanol demand. The analysis found that states with a higher proportion of flex-fuel vehicles tend to exhibit greater elasticity in demand for ethanol.
• Optimal Price Relationships and Policy Recommendations: This study also established optimal price relationships between ethanol and gasoline that encourage ethanol preference. These relationships are influenced by regional factors and should be considered when formulating fuel pricing policies. It is suggested that differentiated policies should be implemented to encourage ethanol use in regions with higher price sensitivity. In addition, investments in ethanol distribution infrastructure can help overcome logistical barriers and improve fuel accessibility.

5. Conclusions

The study presents an evaluation of the dynamics governing ethanol and gasoline consumption across all Brazilian states. By categorizing the states into three distinct price ratio ranges—below 68.8%, between 68.8% and 78.8%, and above 78.8%—it identified regional disparities in fuel pricing and consumer preferences.

The findings also underscore the importance of flexible-fuel vehicles (FFVs) as a key factor in determining the competitiveness and dominance of ethanol in regional markets. States with a high diffusion of FFVs, such as Goiás, Mato Grosso, and São Paulo, exhibit a more stalwart ethanol market, particularly when the ethanol-to-gasoline price ratio is favorable. In these states, ethanol emerges as a dominant fuel option, supported by both economic incentives and consumer acceptance.

Conversely, in regions where the price ratio exceeds 78.8%, ethanol struggles to maintain a significant market share, even in the presence of a substantial FFV fleet. In these regions, higher transportation costs and the lack of government subsidies for ethanol distribution exacerbate the price disadvantage. Another problem is the absence of a national policy for ethanol incentives through reduced tax rates, as these rates greatly vary from state to state.

Moreover, the investigation into market share competitiveness across different states reveals that even in regions with a growing FFV fleet, ethanol’s market penetration is not guaranteed. This highlights the complexity of market dynamics, where pricing, consumer preferences, and economic conditions collectively influence fuel choice.

The results indicate that while ethanol has the potential to dominate in certain regions, particularly where it is produced at scale and priced competitively, achieving widespread adoption will require a multifaceted approach. This approach must consider not only price incentives but also investments in infrastructure, policy support, and public awareness campaigns to encourage a shift towards environmental stewardship. As Brazil continues to navigate its energy transition, this study can inform the development of targeted strategies that leverage regional strengths, ultimately contributing to a balanced and resilient energy market.

Therefore, future research should examine the regional environmental and economic impacts, compare Brazil’s ethanol market with international counterparts, and assess the role of emerging technologies and future trends, as well as considering the vehicle’s scrapping rate. Economic modeling and forecasting analysis could help predict market outcomes, while the impact of climate change on ethanol production should also be investigated.