RenovaBio and AFOLU emissions in the Center-South: quasi-experimental evaluation with Propensity Score Matching and Differences-in-Differences

doi:10.22167/2675-6528-202602643

Article

September 30, 2026

RenovaBio and AFOLU emissions in the Center-South: quasi-experimental evaluation with Propensity Score Matching and Differences-in-Differences

Renovabio and Emissions in the Center-South: A Quasi-experimental Evaluation with Propensity Score Matching and Differences-in-Differences

Alvaro Luz Alves Coutinho; Abdoulaye Aboubacari Mohamed

DOI: 10.22167/2675-6528-202602643

Article derived from a Course Conclusion Work (TCC), with content based on the student’s original work and adapted to the editorial format of the E&S Magazine with the support of the ResumeAI tool, an artificial intelligence solution developed by Instituto Pecege for textual synthesis and organization.

Summary

The study assessed the association between RenovaBio adherence and municipal greenhouse gas (GHG) emissions related to sugarcane in the Center-South region of Brazil. A quasi-experimental design was used, combining Propensity Score Matching (PSM) and Two-Way Fixed Effects (TWFE) differences-in-differences on a balanced panel of 1,511 municipalities and 19,643 observations between 2012 and 2024. In the aggregate specification in log(1+y), for which the joint test did not reject pre-trends at 5%, an increase of 26.0% in AFOLU emissions associated with sugarcane was estimated post-2019 in treated municipalities compared to controls. Estimates at the absolute level and by macro-channel showed pre-trends and were therefore interpreted as descriptive or suggestive evidence: a reduction of 36.1% in Land use change and 44.2% in Agricultural residue burning, an increase of 62.8% in Managed soils, and a difference of -12,157 tCO2eq at the level. Complementary analyses indicated a 13.0% increase in sugarcane area without statistical evidence of native vegetation reduction, as well as an insignificant variation of -0.5% in emission intensity per ton. Taken together, the results are compatible with an internal recomposition of emissions, but causal attribution is better supported only for the aggregate in logarithmic scale and remains conditional on the assumptions of the observational design. The findings contribute to the evaluation of decarbonization policies and suggest attention to managed soil emissions in the program’s evolution.

Keywords: Decarbonization; Differences-in-Differences; AFOLU Emissions; Propensity Score Matching; RenovaBio.

1. Introduction

Brazil has demonstrated a significant commitment to the global climate agenda, setting ambitious targets in the Paris Agreement for the reduction of its greenhouse gas emissions by 48% by 2025 and 53% by 2030 (MAGALHÃES; DOMINGUES, 2016). In this scenario, the National Biofuel Program, known as RenovaBio and established by Law No. 13.576/2017, has emerged as a fundamental pillar for the decarbonization of the transport sector in the country (BRASIL, 2017).

The RenovaBio structure is based on three interconnected elements: the establishment of mandatory targets for reducing carbon intensity, the commercialization of Decarbonization Credits (CBIOs), and the certification of efficient biofuel production through the Energy-Environmental Efficiency Note (NEEA) (BRASIL, 2017; LÁZARO et al., 2023). The economic magnitude of the program is notable, with individual targets totaling 41 million tCO2eq in 2023, representing an estimated financial volume of R$ 4.6 billion. The cumulative mandatory target for the period 2024 to 2033 reaches 570.76 million CBIOs (ANP, 2025).

Despite the relevance of RenovaBio in Brazilian climate policy, evidence on its environmental impacts and the mechanisms through which these effects manifest is still limited. This gap is crucial, as the program focuses on carbon intensity per unit produced, rather than absolute emission limits. Analytically, this can lead to heterogeneous responses among the various emitting sources, with the possibility of reducing extensive pressures and, simultaneously, intensifying production that entails greater input use (LÁZARO et al., 2023; OBSERVATÓRIO DO CLIMA, 2025).

The issue is particularly relevant for first-generation sugarcane ethanol (E1GC). The agricultural phase of this technological route is responsible for 86.8% of the total carbon intensity, with emissions concentrated in nitrogen fertilizers, burning of agricultural waste, and fossil fuel consumption in mechanized operations (MATSUURA et al., 2018; LIU et al., 2023). Additionally, RenovaBio certification requires compliance with the Native Vegetation Protection Law, linking economic incentives to territorial management requirements (NOVAES et al., 2023). Given the concentration of national sugarcane production in the Center-South — with eight states accounting for 99.6% of production between 2019 and 2021, and São Paulo contributing 57% —, the analysis of this regional scope is fundamental to understanding the environmental effects of the program (RAMOS et al., 2024).

The identification of effects attributable to RenovaBio, however, presents challenges. Adherence to the program does not occur randomly, as municipalities with certified plants differ systematically from others in factors such as production scale, level of mechanization, access to credit, and land tenure structure. These differences prevent direct comparisons and require empirical strategies that minimize observable selection bias, although they do not eliminate the possibility of residual confounding (ROSENBAUM; RUBIN, 1983; CALIENDO; KOPEINIG, 2008). Furthermore, different emission channels may react in distinct ways to program incentives, making an analysis based solely on aggregate data insufficient (OBSERVATÓRIO DO CLIMA, 2025).

Given this context, this study contributes to the evaluation of decarbonization policies by examining changes in municipal AFOLU emissions associated with sugarcane after adherence to RenovaBio. Thus, the objective of this study is to evaluate the association between adherence to RenovaBio and changes in municipal AFOLU emissions associated with sugarcane in the Center-South region of Brazil, using a quasi-experimental design that combines Propensity Score Matching and Differences-in-Differences for the period from 2012 to 2024.

2. Material and Methods

This study adopted a quasi-experimental approach to assess the association between adherence to the National Biofuel Program (RenovaBio) and changes in municipal emissions from Agriculture, Forests, and Other Land Use (AFOLU) related to sugarcane. The research focused on the Center-South region of Brazil, covering the period from 2012 to 2024. The methodological design combined Propensity Score Matching (PSM) and Difference-in-Differences (DiD) techniques with two-way fixed effects (TWFE).

The unit of analysis consisted of municipalities, and the final analytical sample was composed of a balanced panel of 1,511 municipalities and 19,643 observations. The treatment group was defined as municipalities that had at least one certified first-generation sugarcane ethanol plant (E1GC) in RenovaBio in the year 2019, totaling 198 municipalities. The year 2019 was established as the beginning of the post-treatment period, in accordance with the program’s operationalization after ANP Resolution No. 758, of November 2018 (ANP, 2025).

The analytical base was built from the integration of eight distinct data sources. The 2017 Agricultural Census and the bases of the IBGE System of Automatic Recovery (SIDRA) provided the pre-treatment covariates. The National Agency of Petroleum, Natural Gas and Biofuels (ANP) and the System for Estimating Greenhouse Gas Emissions (SEEG v13.0) were used for treatment and emissions data, respectively. MapBiomas and the Systematic Survey of Agricultural Production (PAM/IBGE) contributed information on land cover and agricultural production, while the Institute of Applied Economic Research (IPEA/PNUD) and IBGE Centro-Sul complemented with socioeconomic data and municipal geometries.

The data collection and integration procedures involved harmonizing all sources by the seven-digit municipal code from IBGE. Records from certified plants were geocoded at the municipal level, and the annual databases were reorganized into a municipality-year format for the period from 2012 to 2024. The standardization of identifiers, handling of missing values, and organization of variable names were documented in a reproducible notebook, implemented in Python 3.12.

In the pre-processing covariate engineering step, variables were transformed to mitigate asymmetries and scale differences. Absolute variables, such as Gross Domestic Product (GDP), population, and agricultural areas, received logarithmic transformation (log(1+x)). Relative indicators were expressed as shares or densities. Missing values were imputed by the median of each covariate, and already normalized indices were kept in their original scale, resulting in 21 covariates for the final specification.

Before propensity score estimation, a quality and multicollinearity diagnosis was performed. Data types, the proportion of missing values, and the presence of multicollinearity were checked. Variables with more than 60% missingness or with a Variance Inflation Factor (VIF) greater than 10 were excluded, according to the guidelines of HAIR et al. (2009).

The propensity score was estimated using a regularized logistic regression logit model, after standardizing the covariates. The model’s discriminatory capacity was evaluated by the Area Under the Curve (AUC) and McFadden’s pseudo-R². The score logit was employed as a distance metric in the matching process, due to its more symmetric behavior in the tails of the distribution (ROSENBAUM; RUBIN, 1983).

The matching was performed using the nearest neighbor method, at a 1:1 ratio and without replacement, with a caliper of 0.2 standard deviation of the logit of the score. The matched subsample was used to diagnose the balancing of covariates. The balancing was assessed by the Standardized Mean Difference (SMD), adopting |SMD| < 0.1 as a reference (CALIENDO; KOPEINIG, 2008). Units outside the common support region were excluded.

The outcomes were organized into four balanced municipality-year panels (2012-2024). Panel A included total AFOLU-sugarcane emissions, harmonized from SEEG. Panel B disaggregated emissions into macro-channels: Land-use Change, Agricultural Residue Burning, Managed Soils, Soil Organic Carbon, and Forest Residues. Panel C addressed land cover, with MapBiomas data aggregated by class and municipality. Panel D integrated municipal sugarcane production from PAM/IBGE with SEEG emissions to calculate production and emission intensity.

The post-treatment differences were estimated by the TWFE model, formulated as `Yi = αi + λt + β (Treatedi × Postt) + εit`. In this equation, `αi` represents municipality fixed effects, `λt` year fixed effects, and `β` the average post-2019 difference between treated and control municipalities. The variable `Post` assumed a value of 1 for t ≥ 2019. Standard errors were clustered at the municipal level to accommodate intra-municipality serial correlation (BERTRAND et al., 2004). The analyses were performed on two scales: absolute level (tCO2eq) and logarithmic (log(1+y)), the latter being the main specification due to the greater stability of proportional trends (ROTH; SANT’ANNA, 2023).

The plausibility of parallel trends was assessed through an event study and joint Wald tests of the pre-treatment coefficients. The model included indicators of time relative to the treatment, omitting a reference period. Additionally, a sensitivity analysis to the reference period was performed, comparing the baselines k = -1 (2018) and k = -2 (2017) to verify the robustness of the results.

To triangulate the results on emissions, additional models were estimated for the sugarcane area, the participation of sugarcane in the municipal area, and the participation of native vegetation, using data from MapBiomas. With data from PAM/IBGE, the emissive intensity per ton and a specification of emissions with production control were calculated. These complementary analyses aimed to qualify the aggregated pattern and verify its compatibility with differences in productive scale or per-unit efficiency.

3. Results and Discussion

The research results reveal a complex panorama regarding the association between RenovaBio adherence and municipal sugarcane-related greenhouse gas (GHG) emissions in the Center-South region of Brazil. The quasi-experimental analysis, which combined Propensity Score Matching (PSM) and Differences-in-Differences (TWFE), indicated a post-2019 increase of 26.0% in sugarcane-related AFOLU emissions in treated municipalities compared to controls, when evaluated in the aggregated log-linear specification. This finding is the most robust in terms of causal attribution, as the joint test of pre-trends was not rejected at 5% (p = 0.098), although the causal interpretation remains conditioned on the assumptions of the observational design.

In contrast, the absolute-level estimates and those for the macro-emission channels showed significant pre-trends, qualifying them as descriptive or suggestive evidence, rather than identified causal effects. The absolute-level estimate indicated a difference of -12.157 tCO2eq, but the rejection of pre-trends prevents a direct causal interpretation. This distinction between the logarithmic and absolute scales reflects differences in the functional form and initial magnitude of emissions, with the logarithmic transformation being more suitable for comparing proportional variations between groups with distinct emission bases (ROTH; SANT’ANNA, 2023).

Quality of Matching and Balancing of Covariables

The propensity score matching step was fundamental to mitigate observable selection bias. The regularized logistic model demonstrated strong discriminatory capacity, with an Area Under the Curve (AUC) of 0.962 and a McFadden pseudo-R² of 0.550. This confirmed the existence of systematic differences between treated and control municipalities before the intervention, as expected for an observational study (CALIENDO; KOPEINIG, 2008). Before matching, the largest discrepancies between the groups were observed in variables of productive structure, such as sugarcane area (SMD = 2.22), the participation of sugarcane in the total agricultural area (SMD = 1.52), and sugarcane intensity in the landscape (SMD = 1.34).

After matching, there was a substantial improvement in the balancing of covariates. The proportion of variables with Standardized Mean Difference (SMD) below 0.1 increased from 4.8% to 66.7%, and thirteen of the twenty-one covariates showed a bias reduction greater than 80%. The final analytical sample for the TWFE models comprised 1,511 municipalities, with 188 treated and 1,323 controls, totaling 19,643 observations in the period from 2012 to 2024. However, seven covariates still remained with |SMD| above 0.1, indicating that matching reduced, but did not completely eliminate, the observable imbalance between the groups.

Evaluation of Pre-Trends and Identification Strength

The assessment of pre-trends is crucial for the validity of causal inference in Differences-in-Differences designs. For the aggregate specification in log(1+y), the joint Wald test of the pre-treatment coefficients did not reject the null hypothesis of parallel trends at a 5% significance level (W = 10.71; p = 0.098). This result offers relative support for the causal interpretation for this specification, although it is not definitive proof of the absence of pre-trends, which may have limited power (ROTH, 2024). In contrast, for absolute-level emissions, the hypothesis of parallel trends was rejected (W = 27.30; p < 0.001), which restricts the interpretation of this estimate to a merely descriptive character.

The sensitivity analysis to the reference period (baseline) revealed that, for the aggregate in log(1+y), the number of significant pre-treatment coefficients dropped from three to one when changing the baseline from k = -1 to k = -2. This suggests a possible anticipation of certification practices in 2018. For the macro-channels of Land use changes and Managed soils, the pre-treatment coefficients remained significant in both baselines, indicating divergences in emission trajectories prior to the program’s implementation. This pattern limits the causal interpretation for these channels, reinforcing the need to treat them as suggestive evidence.

Post-Treatment Estimates and Strength of Evidence

Post-treatment estimates from TWFE models revealed that, in the aggregate specification in log(1+y), the coefficient β was +0.231 (standard error = 0.046; p < 0.001). This value corresponds to a 26.0% increase in total AFOLU emissions associated with sugarcane in treated municipalities, compared to controls, in the post-2019 period. The 95% confidence interval for this effect ranged from +15.3% to +37.8%. This is the main finding of the study with the strongest support for a causal interpretation, given the non-rejection of pre-trends, but always considering the limitations inherent in the observational design.

At an absolute level, the estimate indicated a reduction of 12,157 tCO2eq (standard error = 2.659; p < 0.001) in total emissions. However, due to the rejection of pre-trends for this scale, this estimate should be interpreted only as a descriptive contrast. The level decomposition, although descriptive, suggests a reduction of 12,965 tCO2eq in Land-use change, an increase of 1,787 tCO2eq in Managed soils, and a reduction of 955 tCO2eq in Agricultural waste burning. These values help to understand the composition of emissions, but should not be causally attributed to RenovaBio.

Macro-Channel Decomposition

The macro-channel analysis revealed a heterogeneous pattern in post-2019 emissions in treated municipalities compared to controls. An estimated reduction of 36.1% in Land use change emissions and 44.2% in Agricultural waste burning emissions was observed, both on a logarithmic scale. These results are consistent with lower extensive pressure on land use and the substitution of manual burning harvesting for green mechanized harvesting. However, pre-trend tests for these channels were rejected, preventing exclusive causal attribution to RenovaBio, as pre-existing state legislation and sectoral transformations may have contributed to these patterns (CLIMATE OBSERVATORY, 2025).

In contrast, emissions from managed soils showed an estimated increase of 62.8% on a logarithmic scale. This pattern is consistent with the increased use of nitrogen fertilizers and organic residuals, indicating production intensification. However, the upward trend prior to 2019 for this channel suggests that a significant portion of this increase may be attributed to pre-existing sectoral processes, not exclusively to RenovaBio. Emissions from soil organic carbon and forest residuals also showed reductions of 17.4% and 18.7%, respectively, on a logarithmic scale, but the strength of identification for these channels is limited by pre-trends observed in event studies.

Triangulation: Land Cover and Emissive Intensity

Complementary analyses on land cover and emissive intensity help qualify the aggregated results. An estimated increase of 13.0% in the sugarcane cultivated area was observed on a logarithmic scale in the treated municipalities. However, no statistically significant variation was detected in the participation of native vegetation in the municipal area (β = +0.0002; p = 0.390), nor in the participation of sugarcane in the municipal area (β = +0.0004; p = 0.496). This data from MapBiomas is compatible with the expansion of sugarcane over pastures or other crops, but the absence of statistical significance for native vegetation does not allow us to infer that the program has causally caused deforestation containment.

Regarding production and emissive intensity, sugarcane production was 97.9% higher post-2019 in the treated municipalities, but this result is descriptive due to the strong previous productive imbalance. Emissive intensity per ton of sugarcane showed a non-significant variation of -0.5% (p = 0.082). When including production as a control in the analysis of total emissions, the difference dropped to +2.1% (p = 0.531), also without statistical significance. Together, these results are compatible with a scale mechanism, where increased production may influence emissions, but they do not causally confirm this mechanism, as production may be a result of the program itself.

Discussion: Mechanisms and Policy Implications

Together, the estimates suggest a pattern of internal recomposition of emissions, diverging from an expectation of uniform reduction. Negative contrasts in extensive sources, such as Land-use change and Agricultural waste burning, coexist with positive contrasts in sources associated with intensive input management, such as Managed soils (LÁZARO et al., 2023). This recomposition should be interpreted as a joint reading of the results, rather than a fully demonstrated causal mechanism, given the variation in the strength of identification between outcomes.

RenovaBio, by operating as a carbon intensity-based pricing instrument, remunerates the reduction in intensity per unit produced, without imposing a direct limit on the total volume of emissions (BRASIL, 2017). This design encourages practices that decrease the carbon intensity of the technological route, but allows for production expansion, which can increase CBIO revenue and, consequently, absolute emissions. The reduction in the burning of agricultural residuals is consistent with the progressive elimination of manual harvesting, penalized by RenovaCalc, but also driven by state legislation and previous sectoral trends, which makes it difficult to attribute causality exclusively to the program.

The increase in emissions from managed soils can be the complementary face of productive intensification, reflecting the greater use of nitrogen fertilizers, vinasse, and other residues. This dynamic is an intrinsic property of intensity-based instruments, as documented in the literature on carbon policies (FISCHER; NEWELL, 2008). The distinction between intensity standards and absolute caps is crucial for evaluating climate policies, as only the latter guarantee the reduction of aggregate emissions when production expands. The results are consistent with the international literature that points to heterogeneous responses to carbon instruments, conditioned by pre-existing institutional and technological capacities (HUANG; CHEN, 2022; FAN; ZHANG, 2021).

As a policy implication, the findings suggest that the evolution of RenovaBio should pay special attention to emissions from managed soils. Options such as progressive nitrogen use efficiency targets, incentives for controlled-release fertilizers, nitrification inhibitors, and conservationist management practices should be evaluated. The implementation of these measures, preferably with field data and designs that allow for the estimation of their specific effects, can be crucial to enhance the program’s environmental impact.

Limitations

The main limitation of this study lies in the observational nature of the quasi-experimental design. Although Propensity Score Matching reduced differences in observable characteristics, seven covariates remained above the balancing threshold, and unobserved factors may have simultaneously influenced program adherence and emissions. Thus, the aggregate estimate in log(1+y) has the strongest support for causal interpretation, while the estimates at the individual and macro-channel levels, which showed pre-trends, should be treated as descriptive or suggestive.

Additionally, the binary definition of the treatment, based on the presence of at least one certified plant in 2019, does not capture the intensity of participation in RenovaBio, the volume of CBIOs traded, the Energy-Environmental Efficiency Score (NEEA), or changes in certification over time. The use of the broader sample in the common support for TWFE, while preserving information, maintains residual heterogeneity between groups. There is also the possibility of spatial interference, where plants buy sugarcane in areas that exceed municipal boundaries, and economic, technological, or environmental effects can reach neighboring municipalities, which would violate the SUTVA (Stable Unit Treatment Value Assumption) assumption and could contaminate the control group.

The outcomes analyzed derive from an inventory based on emission factors and municipal allocation proxies, meaning that local variations in soil, climate, and management may not be fully captured. The results, therefore, refer to officially estimated emissions and not to direct field measurements. The sensitivity of the baseline choice to the aggregate diagnosis, and the temporal horizon of 2012–2024, which may be insufficient to capture long-term structural effects, are other limitations. These considerations prevent an interpretation of absolute causality and justify the explicit gradation of the strength of evidence adopted in this work.

In summary, this study demonstrated that adherence to RenovaBio is associated with a 26.0% increase in aggregate sugarcane AFOLU emissions in treated municipalities, relative to controls, on a logarithmic scale. Although results at the absolute and macro-channel level suggest an internal recomposition of emissions, with reductions in Land-use change and Burning of agricultural waste and increases in Managed soils, the presence of pre-trends limits the causal interpretation of these findings. The research found no statistical evidence of native vegetation reduction or worsening of emission intensity per ton, indicating that the program may be encouraging productive intensification without, however, guaranteeing an absolute reduction in emissions or preventing increases in specific channels, such as managed soils, which points to the need for continuous attention to these aspects in the evolution of the decarbonization policy.

4. Conclusion

This study evaluated the association between RenovaBio adherence and changes in municipal AFOLU emissions related to sugarcane in the South-Central region of Brazil, using a quasi-experimental design. An increase of 26.0% in aggregate sugarcane AFOLU emissions was observed post-2019 in treated municipalities compared to controls, in the log-scale specification. This finding, for which the joint test of pre-trends was not rejected, has the most robust support for a causal interpretation, although conditioned on the assumptions of the observational design. At the absolute level and for the macro-channels, the estimates showed pre-trends, being interpreted as descriptive or suggestive evidence of an internal recomposition of emissions. A reduction was observed in Land use change and Agricultural waste burning, while emissions from Managed soils showed an increase. Complementary analyses indicated an increase in cultivated sugarcane area, with no statistical evidence of native vegetation reduction, and a non-significant variation in emission intensity per ton. The main contribution of this work lies in the evaluation of decarbonization policies, by evidencing that RenovaBio, as an intensity-based pricing instrument, can lead to an internal recomposition of emissions, suggesting the need for special attention to managed soils emissions in the program’s evolution.

Despite the results, the study has limitations inherent to its observational design, such as the persistence of imbalances in seven covariates after matching and the inability to control for unobserved factors that may influence adherence and emissions. The binary definition of treatment did not capture the intensity of program participation, and the outcomes derive from an inventory based on emission factors and proxies, not direct field measurements, which may not capture local variations in soil, climate, and management. The time horizon from 2012 to 2024 may be insufficient to capture long-term structural effects. For future studies, it is suggested to explore participation in RenovaBio using continuous intensity measures, analyze certification cohorts, and adopt estimators robust to temporal heterogeneity. Incorporating effective supply areas of the plants and spatial spillover models may also enhance the understanding of the program’s effects, testing land-use shifts and reducing reliance on the municipality as an isolated unit. In summary, the findings indicate that the decarbonization policy must consider the complex dynamics of emissions, especially in managed soils, to ensure the program’s effectiveness.

Bibliographic References

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Keywords: E-commerce; Consumer behavior; Consumer experience; Loyalty; Virtual business.

October 22, 2026

Psychosocial Risks and Mental Health at Work in a Banking Institution

Mental health in the workplace is a topic of growing relevance, impacting professional development and employee well-being. A study was conducted to identify aspects and situations that can influence absenteeism levels in a banking institution. The research involved 108 participants and used a structured questionnaire, based on the short version of COPSOQ II by Gonçalves (2021), which contained 45 closed Likert scale questions and two open-ended questions. Data were collected via an online platform and analyzed with a descriptive and quantitative approach. The results revealed a scenario that indicated the need for adjustments in the distribution of activities and in managers’ perception of behaviors and signs of disorders. Important evidence was identified in the participants’ open-ended responses. It was concluded that the study contributed to promoting the perception of a safe environment for mental health in the organization.

Keywords: Absences due to disorders; Professional development; Operational leadership; Medical leave; Mental health.

October 22, 2026

Digital Observatory of the Amazon: Data Science Applied to the Analysis of Social, Economic, Environmental, and Health Indicators

The state of Amazonas faced historical challenges in consolidating the Unified Health System (SUS), stemming from geographical barriers, socioeconomic inequalities, and structural limitations. This study described the development and implementation of a health information geoportal, designed to support monitoring, evaluation, and planning in the Amazonian context. A descriptive case study approach was adopted, based on documentary analysis and secondary data, covering the mapping of functionalities, technical infrastructure, and validation steps of the tool. The Portal was developed with open technologies and integrated multiple national databases, offering interactive dashboards, thematic maps, and a digital document repository. Among the results, highlighted were the georeferenced visualization of key indicators, the possibility of temporal comparative analyses, and the use of the platform in reviewing health plans and redirecting strategic actions. The portal can represent an advance in digital governance and evidence-based management, with potential for replication in other highly complex territories, provided it is accompanied by investments in technological infrastructure, professional training, and inter-institutional coordination.

Keywords: Amazon; Health Evaluation; Digital Health; Health Information Systems.

October 22, 2026

Continuous Learning as a Factor of Organizational Growth in the Perception of Collaborators

The impact of continuous learning and knowledge management on organizational growth was studied in a context of globalization and constant changes. The study’s objective was to analyze employees’ perception of learning culture and its importance for personal and professional development. Data were obtained through an anonymous survey, with a quantitative approach, using a form with “survey” type questions applied to 87 professionals from the technology, health, education, commerce, and services sectors. The results indicated that employees had a positive perception of the contribution of continuous learning to personal and organizational growth, recognizing its benefits for the development of new skills, innovation, and competitiveness. However, it was observed that the incentive for internal knowledge exchange and the offering of practical training still presented moderate levels of agreement. It was concluded that continuous learning significantly contributes to individual and organizational development, suggesting that companies should develop strategic policies for learning focused on new skills, aiming for greater competitive advantage and innovation.

Keywords: Continuous learning; Self-development; Organizational growth; Knowledge Management; Innovation.

October 22, 2026

Statistical Regression in Microgrids for Operational Performance Estimation: Campusgrid Case

A multiple statistical regression model was proposed to estimate the operational performance of UNICAMP’s CampusGrid microgrid, based on internal electrical quantities. The microgrid integrates photovoltaic generation, batteries, and a gas generator. Energy management system data were collected at five-minute intervals over one month. The Operational Reliability Index, defined as the ratio between supplied and demanded energy, was established as the dependent variable. The model was adjusted for the islanded operation mode, evaluating the impact of demand, state of charge, solar generation, and supplied energy. The results revealed high explanatory power, indicating that operational reliability depends on the interaction between supply and demand. It was observed that the nighttime period concentrated the highest rate of partial supply, attributed to the reduction in solar generation. It was concluded that multiple regression offers an interpretable and useful framework for microgrid monitoring and control strategy support.

Keywords: Battery storage; Photovoltaic generation; Reliability Index; Islanded operation; Energy Management System.

October 22, 2026

Forecast of Aggregate Default in the Brazilian Financial System by Sarimax Model with Macroeconomic Variables

Aggregate non-payment in the Brazilian financial system is a crucial indicator of credit risk, the prediction of which is regulated by CMN Resolutions n.° 4.557/2017 and 4.966/2021 for the prospective measurement of expected losses. Aggregate non-payment was modeled and predicted using the SARIMAX model, projecting its trajectory until December 2026 under optimistic, base, and pessimistic scenarios. 164 monthly observations (July/2012 to February/2026) and macroeconomic variables such as unemployment, Selic, IPCA, IBC-Br, and household debt were used. The specification with contemporaneous variables was selected based on information criteria and coefficient stability, and residual diagnostics confirmed statistical adequacy, with a MAPE of 3.12%. Historical non-payment ranged between 4.33% and 7.64%. The estimation identified unemployment (β = 0.2534; p < 0.001) and Selic (β = 0.2128; p < 0.001) as the main positive determinants, with strong temporal persistence (AR(1) = 0.8965). Selic showed increasing correlation with non-payment (r = 0.62 at lag 12), while unemployment demonstrated a contemporaneous effect (r = 0.33). Projections indicated non-payment between 6.30% and 7.98% in December 2026, with a range of 1.68 percentage points, highlighting direct implications for provisioning in financial institutions.

Keywords: Unemployment; Predictive modeling; Monetary policy; Loss provisioning; Time series.

October 22, 2026

Stakeholder Engagement Factors in International Technology Transfer to a Public Hospital

This study described the critical factors perceived for stakeholder engagement in international technology transfer in a public hospital, with a focus on planning. The objective was to describe these conditioning factors, according to the perception of professionals. A single case study was conducted, applying a questionnaire to 25 professionals and using content analysis, complemented by descriptive tabulations. The main obstacles identified were resistance to change (72%), funding (64%), lack of communication (60%), and bureaucracy (40%). Only 28% of respondents recognized the existence of adequate tools for stakeholder management, while 48% denied it and 24% did not know. Exploratory cross-tabulations indicated variations in the assessment of influence according to time of practice, but did not establish causal relationships. Lack of engagement was associated with delays, low adherence, waste of resources, communication failures, compromised knowledge absorption, and risks to patient safety. The conclusions were limited to the perceptions of the researched group and supported preliminary recommendations for intersectoral communication and coordination.

Keywords: Case study; Project Management; Health innovation; Stakeholders; Public sector.

Economy

October 19, 2026

End of the 6×1 scale: what do the numbers allow us to conclude?

Following the promulgation of the end of the 6×1 shift system, the debate on the shorter workday moves to implementation and requires distinguishing social benefits from economic costs. The end of the 6×1 shift system transitioned from legislative discussion to a constitutional change in Brazil. On October 16, 2026, the National Congress promulgated Constitutional Amendment No. 141/2026, originating from Proposal […]

Artificial Intelligence

October 16, 2026

Why study if AI exists?

When answers become easy, learning comes to mean more than just arriving at them. Why do I need to learn this if I can ask an artificial intelligence? This type of question has accompanied education for decades. Why learn an operation if a calculator exists? Why memorize information if it can be found […]

Tax Management

October 15, 2026

Pink tax and the gender of price

How different marketing treatments for men and women are incorporated by consumption taxation Imagine a shelf on which two razors of the same brand and intended for the same purpose are displayed side by side: one has dark packaging and promises strength, precision, and efficiency; the other comes in shades of pink or […]

Health

October 13, 2026

The missing link in health transformation

Why is innovation not enough to drive changes in organizations and health systems Digital transformation has become a strategic priority for health systems worldwide. Electronic health records, artificial intelligence, telemedicine, remote monitoring, and data analysis are now part of the strategic agenda of governments and health organizations. Paradoxically, […]

Marketing

October 09, 2026

Bitcoin or pets: what Artificial Intelligence would not see

A real-life consumer intelligence case shows what gets left out of the brief A few years ago, an American insurance company hired a specialized consumer intelligence firm to answer three questions: The insurer was also considering launching paid insurance in bitcoin. At the time, the consultancy’s workflow was as follows: the analyst created a query […]

School Management

October 06, 2026

The school is not a casino: when trading cards become currency in the playground

Why, for certain students, does school manage to offer so few experiences of achievement? The World Cup is over. Brazil left the competition, the school holidays came, the final was played and the football calendar moved on. It would be reasonable to imagine that, with the end of the tournament and the return to classes, […] would also begin

Energy Transition

September 30, 2026

Renewable energies: the Brazilian advantage

Brazil needs to invest in the capacity to transform natural resources into innovation, productivity, and development. Talking about energy is talking about development. Behind industry, transportation, services, cities, and increasingly artificial intelligence, there is an energy infrastructure that sustains the economy. Understanding a country’s energy matrix is understanding […]

Data Analysis

September 30, 2026

When the data changes, has reality changed?

An analysis of almost 20 million teaching positions-year between 2020 and 2025 shows how changes in population composition and record production can alter the interpretation of historical series Between 2020 and 2025, the number of formal teaching employment positions identified in RAIS (Annual Relation of Social Information), from the Ministry of Labor, […]

Artificial Intelligence

September 28, 2026

Artificial intelligence and the trends

Why do so many people join in on the fun with ChatGPT? I was never the trend person. I still am not. Some pass through my timeline, I see them, I find them interesting but not to the point of trying them out. This was the case, inclusive, with some recent waves of images made by artificial intelligence, like the 80s trend, the one that […]

Tax Management

September 01, 2026

Tax reform and estate planning in the countryside

Efficiency in managing taxes facilitates governance and allows for the organization of family succession. Rural wealth organization has become a strategic measure in light of the tax reform in Brazil, which came into effect this year. The planning of activities and rural wealth management, through tools such as the transition from an Individual to […]

Renata de Gaspari Valdejão Almeida

Artificial Intelligence

August 05, 2026

Inside the company and off the radar: the risks of Shadow AI

According to Microsoft, 75% of professionals already use artificial intelligence at work without company approval. The use of generative artificial intelligence is already part of the corporate routine. Tools like ChatGPT, Copilot, and other platforms help professionals produce texts, analyze data, create presentations, and accelerate tasks in practically all sectors. But this advance […]

Renata de Gaspari Valdejão Almeida

Strategy

July 02, 2026

The future as a competence

Academic interest reinforces the projection of scenarios as an essential tool for decision-making. While some companies are still trying to get the next step right, others are already working with multiple possible futures — and preparing for all of them. But after all, what does it mean to “think about the future”? Is it a trend, a strategy, or a new competence that […]

Renata de Gaspari Valdejão Almeida

Innovation

Technology

May 21, 2026

Agro SP Corridor: innovation, institutional articulation and future

Pecege commands the executive operation of the 400 km ecosystem activities that became known as the Brazilian agro Silicon Valley In 2025, in addition to taking over the management of the Piracicaba Technology Park, the Pecege Institute was also designated to command the executive operation of the State Agribusiness Innovation Corridor activities, the so-called […]

Education

April 27, 2026

How to turn a TCC into a business

New management of the Piracicaba Technology Park offers consulting to MBA graduates The new project director of the Piracicaba Technology Park (PTP), Alexandre Barreto, often says that one of the greatest rewards he has ever had in life was seeing his MBA USP/Esalq students structure companies from their final projects […]

Technology

March 20, 2026

The human repertoire in the age of AI

Critical thinking and creativity are irreplaceable in the work of a marketing professional Artificial Intelligence (AI) is capable of incredible feats, but it does not yet possess the judgment, empathy, intuition, and strategic creativity necessary to do the job of a good marketing professional. In this area, it is important to know how to use the tool to automate […]

Renata de Gaspari Valdejão Almeida

Agribusiness

Innovation

February 23, 2026

ESG as a growth strategy in a cooperative in RS

Santa Clara balances social and environmental responsibility with innovation Founded in 1911 by Italian immigrants in Carlos Barbosa, in the Serra Gaúcha region, Cooperativa Santa Clara is an example that it is possible to balance economic growth with social and environmental responsibility. From a small cheese production company, the organization has evolved into a […]

Renata de Gaspari Valdejão Almeida

Agribusiness

Innovation

January 22, 2026

Brazil free of Foot-and-Mouth Disease: what changes for Brazilian beef?

With a herd of over 200 million head of cattle, the country is currently the leader in exports. Brazil recently received, for the first time, the certification of country free of foot -and-mouth disease without vaccination, conferred by the World Organisation for Animal Health (WOAH). The seal strengthens the country’s position as a reliable supplier of meat for the […]

Renata de Gaspari Valdejão Almeida

Innovation

December 09, 2025

Innovation: the new cycle of the Piracicaba Technology Park

Instituto Pecege assumes management, betting on the creation of new businesses Starting in 2026, Instituto Pecege will assume the management of the Piracicaba Technology Park (PTP). Among its responsibilities will be the administration, operation, maintenance, and expansion of the park, in addition to fostering activities in innovation, entrepreneurship, and science and technology. The choice was made […]

Renata de Gaspari Valdejão Almeida

July 06, 2026

Large-Scale Architecture: DSR-SCRUM Change Management

Mônica Alessandra Guerios; Maria do Carmo Assis Todorov Abstract generated by ResumeAI, an artificial intelligence solution developed by Instituto Pecege focused on synthesis and writing. Architecture and urbanism are configured as essential bases in an increasingly complex and challenging urban space, where the intrinsic connection between social, environmental, and technological issues […]