Between Sisyphus and the barrel of the Danaids

Column

Tax Law

September 09, 2026

Between Sisyphus and the barrel of the Danaids

The basic food basket, the minimum wage, and the true price of things

In Greek mythology, some punishments were not distinguished by the violence of a single suffering, but by the condemnation to repetition. Sisyphus had to roll an enormous stone to the top of a mountain and, when the effort seemed finally completed, the stone escaped and returned to the starting point, forcing him to start over.

For their part, the Danaids received a similar fate, as they were condemned to transport water to fill a container incapable of retaining it; they indefinitely repeated a task whose result was lost as it was performed.

There is something of these two mythological images that associates with the contemporary relationship between work, income, and cost of living. Every month, the worker converts part of their time into remuneration and, with it, needs to finance food, housing, transportation, health, and other daily needs. The following month, the cycle begins again.

For those who receive the minimum wage, the magnitude of this effort can be observed quite concretely when the price of things is no longer measured only in reais and starts to be converted into hours of work.

In 2026, the Brazilian minimum wage was set at R$ 1,621.00 per month, corresponding, according to decree no. 12,797/2025, to R$ 54.04 per day and R$ 7.37 per hour. From this value, the question ceases to be merely about the cost of the goods we consume and becomes: to what extent is the minimum wage capable of financing, in the different regions of the country, the set of needs that the Federal Constitution (CF) itself associates with a dignified existence?

One way to answer this question is to observe how much income and work time are allocated to food. According to the National Survey of the Basic Food Basket, from Conab and Dieese, in July 2026 a worker paid the minimum wage needed to work, on average, 100 hours and 24 minutes to acquire the basic food basket in the 27 capitals surveyed, which absorbed 49.34% of the net minimum wage.

The data also reveal important differences between the capitals. In July 2026, the five most expensive baskets were recorded in São Paulo, R$ 915.01, Cuiabá, R$ 881.27, Florianópolis, R$ 860.73, Rio de Janeiro, R$ 855.37, and Porto Alegre, R$ 841.94. The five least expensive were in Salvador, R$ 650.32, João Pessoa, R$ 644.04, Natal, R$ 631.51, Maceió, R$ 618.60, and Aracaju, R$ 594.07.

Between São Paulo and Aracaju, the difference was R$ 320.94 and, in work time, it corresponded to 124 hours and 11 minutes, versus 80 hours and 38 minutes, respectively. However, the comparison requires caution, as the research adopts different compositions for the baskets of the North and Northeast and the other regions. The values do not, therefore, constitute a general cost of living ranking, but reflect the set of foods defined by the methodology for each group of capitals.

Nevertheless, the contrast is relevant. The minimum wage is nationally unified, but its purchasing power is not. The same R$ 1,621.00 represents distinct efforts depending on where one lives, a difference that also appears in the evolution of prices.

Between June and July of 2026, the basket became cheaper in 26 out of 27 capitals, but, in relation to July of 2025, it had increased in 22 of them. In the accumulated total of the first seven months of 2026, there was an increase in all capitals surveyed.

This relationship between salary and purchasing power is not just economic. Article 7 of the Constitution establishes, in item IV, that the minimum wage must be capable of meeting the basic vital needs of the worker and their family, including housing, food, education, health, leisure, clothing, hygiene, transportation, and social security, with adjustments intended to preserve its purchasing power.

The enumeration shows that the constitutional parameter is not limited to subsistence and that food is only one of the needs to be financed. When almost half of the net income is consumed by the basic food basket, the data reveals something greater than the price of food itself.

This forecast is not isolated in the constitutional text. The dignity of the human person and the social values of labor are among the foundations of the Republic. In the same vein, Article 170 establishes that the economic order, based on the valorization of human labor, must ensure a dignified existence according to the dictates of social justice, while Article 193 defines the primacy of labor as the basis of the social order, aimed at social well-being and justice. The material capacity of wages therefore appears as part of a broader constitutional conception of labor, dignity, and well-being.

Minimum wage

One way to measure this parameter is the so-called minimum wage, calculated monthly by Dieese. In July 2026, for a family of four, the institute estimated the income needed to meet constitutionally foreseen expenses at R$ 7,687.01, a value equivalent to 4.74 times the official minimum wage of R$ 1,621.00.

The indicator does not constitute a legally enforceable second floor, but it offers an economic reference for the distance between the current value and the estimated cost of the needs that the Constitution attributes to the minimum wage.

This distance depends not only on the income value, but also on the purchasing power it preserves when allocated to consumption. Complementary Law No. 214/2025, which regulated the IBS and CBS, incorporated this concern by reducing to zero the rates levied on products from the National Basic Food Basket and providing for the refund of these taxes to low-income families.

The cashback, regulated in articles 112 et seq., will be based on consumption from January 2027 for the CBS and from January 2029 for the IBS, as per article 123, while the zero rate for the basic food basket is provided for in article 125. Although the tax basket is not to be confused with the one researched by Dieese and it is not yet possible to anticipate the effect of these measures on prices, they show that the ability of wages to finance daily needs is also influenced by the taxation on consumption.

The numbers shift the discussion from the nominal value of wages to what they effectively allow to be financed, as income, prices, location, and taxation combine to determine how much of the work is converted into consumption and how much can remain after basic expenses.

It is in this sense that the images from the beginning regain their strength: Sisyphus represents the effort that needs to be renewed each month, while the barrel of the Danaids translates the difficulty of making income remain. For those who live on the minimum wage, the price of things ceases to be just that indicated in reais and also begins to reflect the work time necessary to acquire them and what remains after the most immediate needs are met.

This experience is not the same for all families, as other incomes, family composition, access to public services, and housing conditions alter the budget organization, and the basic food basket itself does not intend to measure all these dimensions. Nevertheless, the comparison is revealing: in July 2026, acquiring the researched foods required 80 hours and 38 minutes of work in Aracaju and 124 hours and 11 minutes in São Paulo, although the minimum wage was the same in both cities. Perhaps the true price of things lies precisely there, not only in the value indicated on the price tag, but in the time needed to pay for it and in the portion of income that ceases to be transformed into savings, assets, or freedom of choice.

Between Sisyphus and the Danaids’ barrel, the minimum wage thus reveals a tension that goes beyond its nominal value. On the one hand, there is a national floor constitutionally conceived to ensure a broad set of needs. On the other, there are prices that vary across the territory and an income that, to a large extent, is exhausted before reaching them. The true price of things may lie precisely in this distance.

To access the references of this text click here

Who wrote this column

Bruna Esteves

Advogada tributarista. Bacharela em Direito, mestra e doutoranda em Direito Econômico e Economia Política, todos na FD-USP. Possui MBA em Gestão Tributária, Investimentos e Banking e em Agronegócios pela USP/Esalq. Atua como professora de prática tributária do Curso de Especialização em Direito Tributário Brasileiro (IBDT) e como orientadora do MBA USP/Esalq.

You may also like

October 02, 2026

Determinants of supermarket location in São Paulo

A study investigated the determining factors for supermarket location in the state of São Paulo, with the objective of investigating the factors that explain the presence and expansion of these establishments, considering socioeconomic, demographic, and market dimensions. Data from the 2010 and 2022 Demographic Censuses of IBGE and information from the National Registry of Legal Entities of the Federal Revenue of Brazil were used to build a georeferenced database. A Random Forest classification model was applied, adjusted by grid search with cross-validation, prioritizing the recall-macro metric due to the imbalance of the dependent variable, which represented the presence or absence of supermarkets within a 50-meter buffer. The results indicated that supermarket location is strongly associated with demographic, income, and population characteristics in the surrounding area. The analysis of variable importance showed that sociodemographic factors, such as elderly literacy, household income, and the presence of other food establishments, exerted significant influence, especially in the immediate vicinity. The findings reinforced the hypothesis that the spatial distribution of supermarkets is not random, being conditioned by socioeconomic characteristics and the commercial structure of the territory, offering subsidies for business decisions and urban planning.

Keywords: Spatial Analysis; Machine learning; Expansion; Commercial location; Supermarkets.

Neuroscience And Learning In Education

October 02, 2026

Anti-Racist Education: Inclusive Educational Practices and Social Development

Antiracist education, understood as a structuring axis of inclusive education and social development, was investigated in the Brazilian context. The study aimed to identify and analyze, based on legal documents and teachers’ perceptions, educational practices capable of promoting antiracism in school and society, and how the implementation of Laws nº 10.639/03 and nº 11.645/08 contributed to social justice. A qualitative and documentary approach was adopted, with analysis of educational legislation, curricular guidelines, institutional reports, and academic literature. Complementarily, a semi-structured questionnaire was applied to 295 Basic Education teachers. The data were evaluated quantitatively and qualitatively, through thematic content analysis, and validated with bibliographic studies. The results revealed a paradox: despite a robust legal framework, the implementation of antiracist policies proved fragile and sporadic, with a lack of teacher training, adequate teaching materials, and monitoring. Significant educational inequalities between white and black students were found to persist, and most teachers acknowledged the occurrence of racism in schools, but without clear institutional protocols. Neuroscientific analysis showed that racism negatively impacts students’ cognitive and emotional development. It was concluded that antiracist education is central to quality education, requiring political commitment, public investment, and intersectoral articulation. The integration of Neuroscience in teacher training and the production of qualified materials are crucial to strengthen the school’s role in building a more just and inclusive society.

Keywords: Social Development; Antiracist Education; Social Justice; Law 10.639/03; Inclusive Educational Practices.

Neuroscience And Learning In Education

October 02, 2026

Paths of Inclusion: Perceptions of Parents and Teachers on the Schooling of Students with Dual Exceptionality in the Brazilian Context

Dual Exceptionality, characterized by the coexistence of High Abilities/Giftedness and neurodevelopmental disorders, represents a complex phenomenon that challenges traditional identification and schooling models. The study aimed to understand the perceptions of parents or guardians, teachers, and other education professionals regarding the schooling of students with Dual Exceptionality in the Brazilian context, investigating challenges, pedagogical strategies, and possibilities for inclusion based on equity. The research adopted a qualitative, exploratory, and descriptive approach, and collected data through an online, voluntary, and anonymous questionnaire answered by 25 participants. Discursive data were analyzed using thematic content analysis. The results indicated that knowledge about the topic is often built from personal and professional experiences, revealing gaps in systematic training. Difficulties were identified in identifying these students, in teacher training, and in implementing individualized educational plans, pedagogical flexibility, and curriculum enrichment. Socio-emotional repercussions, such as frustration and low self-esteem, were reported. However, some schools demonstrated inclusive practices based on equity, articulating specific needs and potentialities. Although the results do not allow for generalizations, they highlighted the need to strengthen professional training and the articulation between school, family, and specialized services. It was concluded that the inclusion of students with Dual Exceptionality requires practices that simultaneously recognize their difficulties and potentialities, ensuring equitable conditions for participation, learning, and development.

Keywords: Human development; Teacher training; School inclusion; Neurodivergence; Pedagogical practices.

October 02, 2026

Data Transformation into Strategy: Applied Research for Ecotourism Operation Optimization

The growing demand in ecotourism in Minas Gerais has driven the search for business intelligence to transform customer data into strategic information. The study aimed to structure a data science pipeline to collect, segment, and classify the customer base of an ecotourism operation, in order to optimize marketing actions and anticipate market movements. An exploratory, quali-quantitative research was conducted through a case study. 2,777 transactional records from an ecotourism company, referring to January 2024 to December 2025, were used. The methodological process involved automated data collection (Google Sheets API), processing and enrichment (ETL), validation, and creation of RFM (Recency, Frequency, and Monetary Value) attributes. Dimensionality reduction via PCA and K-Means clustering was applied, with the number of clusters defined by the Elbow method and Silhouette Score. The results were validated with DBSCAN and K-Medoids. The results revealed the identification of three behavioral customer segments: “Loyal”, “Low Value”, and “Potential”. The “Loyal” segment represented the highest accumulated economic value, while the “Potential” segment stood out for its high average ticket and potential for conversion into recurrence. The integration of data analysis techniques proved to be a robust and replicable method for generating intelligence in ecotourism. It was concluded that the structured data science pipeline enabled the behavioral segmentation of the customer base, the statistical validation of the groups, and the creation of a predictive system for new buyers, providing subsidies for data-driven strategic decisions and future analyses.

Keywords: Clustering; Business intelligence; Machine Learning; Customer segmentation; Decision making.

October 02, 2026

Classification of defaulting customers using supervised machine learning techniques

The risk of default in credit operations demanded analytical approaches to anticipate losses. This study comparatively evaluated the performance of supervised machine learning models in classifying defaulting customers in credit card operations. The public dataset “Default of Credit Card Clients” from the University of California Irvine was used, with 30,000 observations and class imbalance. The algorithms Logistic Regression, Random Forest, and Extreme Gradient Boosting were employed. The imbalance was addressed by assigning weights to the classes, and model optimization occurred with the RandomizedSearchCV method, prioritizing sensitivity. Cross-validation results indicated that the Extreme Gradient Boosting model showed a higher capacity for identifying the defaulting class and better discriminatory performance, followed by Random Forest and Logistic Regression, with a sensitivity of 0.8250 and an AUC-ROC of 0.7844 for XGBoost. Interpretability analysis, conducted by the Shapley Additive Explanations (SHAP) technique, highlighted the predominance of variables associated with payment behavior, especially the history of delays. It was concluded that tree-based models, particularly boosting techniques, proved to be more suitable for capturing complex patterns in the data, configuring themselves as consistent alternatives for credit risk management.

Keywords: Machine Learning; Credit Card; Classification; Extreme Gradient Boosting; Credit Risk.

October 02, 2026

Sentiment Analysis on Brazilian Banks on Twitter/X: Comparison between Traditional and Digital Institutions

A study analyzed public perception of Brazilian financial institutions on the Twitter/X platform, highlighting the importance of sentiment monitoring on social networks for understanding reputation and customer experience in the banking sector. The objective was to compare user perception of the image and reputation of traditional and digital banks, based on the sentiment patterns identified in the analyzed manifestations, seeking to identify structural differences between these groups. The methodology was based on the analysis of 1,096 tweets collected between November 2022 and June 2023. Two complementary sentiment analysis approaches were used, the sum and the average of labels, to capture the majority sentiment and nuances of perception. Additionally, the Market Profile Model, with indicators of emotional reputation, reputational risk, neutrality, and polarization, and the Banking Clustering Model, which allowed grouping institutions according to perception patterns, were developed. The results indicated a predominance of neutral and negative sentiments, a higher volume of interactions in digital banks, and structural differences in the emotional intensity of perceptions, with greater stability in digital banks and greater polarization in traditional ones. It was concluded that the combination of analytical and statistical techniques contributed to an in-depth understanding of institutional image in the digital environment, demonstrating the importance of data-driven reputation management strategies.

Keywords: Digital banks; Traditional banks; Data modeling; Opinion mining; Social Networks.

October 02, 2026

Optimization of annual budget planning through project management methodologies

The Annual Budget Planning (POA) is a crucial process for translating organizational strategy into operational and financial goals, but it frequently faces deadline pressures, interdepartmental dependencies, and the repetition of habitual expenses. The study aimed to analyze how the combined application of project management practices and Zero-Based Budgeting (OBZ) can optimize the POA. To this end, a case study was developed in the Brazilian operation of a publicly traded company in the beverage sector, using documentary research of its 2023 results report and an anonymous questionnaire applied to 47 respondents. Documentary analysis indicated growth in net revenue, expansion of gross profit and adjusted EBITDA, and contained advancement of selling, general, and administrative expenses, suggesting cost discipline and operational leverage. The complementary survey revealed a high perception of cascading effect on the schedule, strong support for defining cost package owners, and a preference for technical justification of expenses, in addition to demand for controlled flexibility after the baseline definition. It was concluded that structuring the POA as a project, associated with the rigor of OBZ, increased the process predictability, reinforced accountability for expenses, and broadened the coherence between budgetary execution and economic-financial performance.

Keywords: Cost Control; Operational Efficiency; Zero-Based Budgeting; PMBOK; Beverage Sector.