Coleção de Artigos Acadêmicos

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https://repositorio.insper.edu.br/handle/11224/3227

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Seis vezes “onze ilhas”: os múltiplos sentidos de individualismo em interpretações sobre o STF
(2024) DIEGO WERNECK ARGUELHES; LUIZ FERNANDO GOMES ESTEVES
O Supremo Tribunal Federal é uma instituição “individualista”? Em três décadas de estudos acadêmicos e debates públicos, tem sido recorrente o tema de um tribunal tão dividido quanto o número de ministros, sintetizado em variadas imagens, das quais “onze ilhas” é a mais popular. Há menos consenso, na verdade, do que sugere o uso generalizado e recorrente dessa metáfora. Neste trabalho, identificamos ao menos seis sentidos possíveis de “individualismo” como chave de leitura e crítica do funcionamento do tribunal – alguns deles sobre a atuação dos(as) ministros(as) dentro do colegiado, outros enfocando essa atuação fora do processo decisório colegiado. Sem clareza quanto a essas diferentes leituras e suas condições específicas de sucesso como descrições do STF, a maleabilidade das imagens sobre a natureza ou funcionamento da instituição se torna problemática. Neste artigo, recorrendo duas décadas de trabalhos empíricos e normativos sobre o STF, pretendemos contribuir para diagnósticos sobre o funcionamento do tribunal por meio da reconstrução conceitual: (1) dos diferentes sentidos possíveis em que o Supremo pode ser “individualista”, (2) das diferentes condições de sucesso de trabalhos empíricos que pretendam testar hipóteses sobre cada uma dessas dimensões, e (3) dos diferentes aspectos de desenho institucional relacionados às distintas dimensões.
The impact of gestational weight gain on fetal and neonatal outcomes: the Araraquara Cohort Study
(2024) Victor, Audêncio; Teles, Laísla de França da Silva; Aires, Isabel Oliveira; Carvalho, Leticia Falcão de; Luzia, Liania A.; Victor, Audêncio; Teles, Laísla de França da Silva; Rinaldo Artes; RINALDO ARTES; Rondó, Patrícia H.
Background: Gestational weight gain (GWG) is an important indicator for monitoring maternal and fetal health. Objective: To evaluate the effect of GWG outside the recommendations of the Institute of Medicine (IOM) on fetal and neonatal outcomes. Study design A prospective cohort study with 1642 pregnant women selected from 2017 to 2023, with gestational age≤18 weeks and followed until delivery in the city of Araraquara, Southeast Brazil. The relationship between IOM recommended GWG and fetal outcomes (abdominal subcutaneous tissue thickness, arm and thigh subcutaneous tissue area and intrauterine growth restriction) and neonatal outcomes (percentage of fat mass, fat-free mass, birth weight and length, ponderal index, weight adequateness for gestational age by the Intergrowth curve, prematurity, and Apgar score) were investigated. Generalized Estimating Equations were used. Results: GWG below the IOM recommendations was associated with increased risks of intrauterine growth restriction (IUGR) (aOR 1.61; 95% CI: 1.14–2.27), low birth weight (aOR 2.44; 95% CI: 1.85–3.21), and prematurity (aOR 2.35; 95% CI: 1.81–3.05), and lower chance of being Large for Gestational Age (LGA) (aOR 0.38; 95% CI: 0.28–0.54), with smaller arm subcutaneous tissue area (AST) (-7.99 g; 95% CI: -8.97 to -7.02), birth length (-0.76 cm; 95% CI: -1.03 to -0.49), and neonatal fat mass percentage (-0.85%; 95% CI: -1.12 to -0.58). Conversely, exceeding GWG guidelines increased the likelihood of LGA (aOR 1.53; 95% CI: 1.20–1.96), with lower 5th-minute Apgar score (aOR 0.42; 95% CI: 0.20–0.87), and increased birth weight (90.14 g; 95% CI: 53.30 to 126.99). Conclusion: Adherence to GWG recommendations is crucial, with deviations negatively impacting fetal health. Effective weight control strategies are imperative.
National Security Whistleblowing. Reflections on the Rationale for Exempting from Criminal Liability the Unauthorised Disclosure of Classified Information for the Purpose of Exposing State Wrongdoing
(2024) Stoco, Tatiana de Oliveira
The disclosure of wrongdoings by whistleblowers is currently encouraged by numerous countries. However, when it comes to disclosures involving illegal state secrets in matters of national security, there is a very different legislative treatment worldwide. Whistleblowers who disclose classified information with the purpose of revealing wrongdoings are usually convicted for espionage or other re lated crimes, even if their disclosures are of great public interest. The purpose of this paper is to explain why the behaviour of such whistleblowers deserves a certain degree of leniency and how this could be legally implemented. First, the arguments for and against the disclosure of classified information will be presented. Next, the role that unauthorised disclosures of classified information play in the pursuit of state transparency will be addressed. Finally, the article will present the central arguments in favour of the legitimacy of this behaviour and analyse the legal alternatives for a complete or partial exemption from criminal liability.
A dual character theory of law
(2024) GUILHERME DA FRANCA COUTO FERNANDES DE ALMEIDA
One persistent question in jurisprudence relates to the role of morality in the concept of law. For instance, consider the question of whether unjust statutes are laws. Legal positivists say that they’re laws in every relevant sense, while natural lawyers say that they’re not. This article considers a different answer inspired by recent findings in experimental philosophy: there is one relevant sense in which unjust statutes are laws, but also a different relevant sense in which they aren’t. After considering the ways in which this alternative differs from some of the mainstream theories in general jurisprudence, the article argues that it provides more elegant solutions to two problems that have puzzled legal philosophers in the past: the paradox of customary international law and the shifts in legal discourse over history.
Capital structure determinants of private and public firms in an emerging economy: a panel data quantile regression analysis
(2024) ADRIANA BRUSCATO BORTOLUZZO; Sanvicente, Antonio Zoratto; Bortoluzzo, Maurício Mesquita
Purpose This study explores distinct capital structure patterns between private and public companies, examining the varying influence of determinants on debt choices contingent upon a firm’s existing debt position. Design/methodology/approach Employing annual data from 2012 to 2022 for 142 public firms and 660 private firms in a large emerging economy, we use quantile regression within a panel data framework to study the heterogeneous effects of debt determinants, incorporating firm and time random effects. Findings Our findings indicate that such factors as size and operating margin contribute to higher levels of debt, while investment opportunities reduce the debt level. Further analyses, when accounting for a firm’s likelihood of being publicly traded, reveal that dividend payout and operating margin significantly influence debt levels, exclusively in the presence of high debt proportions. Conversely, investment opportunities emerge as a substantial determinant in all debt scenarios. In addition, we found a strong persistence in the indebtedness of companies, and we conclude that the effect of the determinants of indebtedness is heterogeneous according to the level of debt of companies. Originality/value This research provides a comprehensive comparison between private and public firms, not only in terms of debt levels but also in key capital structure determinants, highlighting their significance within the context of varying debt levels.
The dark side of the boom: dutch disease, competition with China, and technological upgrading in colombian manufacturing
(2024) Branstetter, Lee G.; Laverde-Cubillos, N. Ricardo
The natural resource boom of the 2000s spurred growth in income and consumption in many commodity-exporting nations. However, this paper brings together a previously unused combination of data sets from Colombia to document evidence of a downside – the currency appreciation associated with this boom led to a significant and persistent decline in R&D spending and in investment in technological upgrading by Colombian manufacturing firms. Our empirical strategy exploits differences in firms' sales across products and export destinations to create firm-specific measures of exposure to exchange rate shocks both abroad and at home. We link these new measurements of exchange rate exposure with Colombian micro data on R&D investment and technology upgrading. The key finding is that real exchange rate appreciation drives significant reductions in both firm-level R&D investment and a measure of technology upgrading that includes expenditure on capital goods, technology licensing, worker training, and other expenditures related to the adoption of new technology. Even after key commodity prices dropped significantly in the mid-2010s, inducing a substantial and long-lasting Colombian currency depreciation, investments in R&D and technology upgrading remained at subdued levels. Our estimated effects suggest that the resource boom and associated appreciation had a significant and persistent negative effect on technological development of Colombian manufacturing firm, and these conclusions remain even after careful attempts to simultaneously control for rising competition with Chinese manufacturers, which also had a negative effect on Colombian firms' technology investments, and the effects of trade liberalization at home and abroad. Similarities between Colombia and other commodity-exporters suggest that the effects documented in this paper may be widespread.
Stochastic Volatility Models with Skewness Selection
(2024) Martins, Igor; HEDIBERT FREITAS LOPES
This paper expands traditional stochastic volatility models by allowing for time-varying skewness without imposing it. While dynamic asymmetry may capture the likely direction of future asset returns, it comes at the risk of leading to overparameterization. Our proposed approach mitigates this concern by leveraging sparsity-inducing priors to automatically select the skewness parameter as dynamic, static or zero in a data-driven framework. We consider two empirical applications. First, in a bond yield application, dynamic skewness captures interest rate cycles of monetary easing and tightening and is partially explained by central banks’ mandates. In a currency modeling framework, our model indicates no skewness in the carry factor after accounting for stochastic volatility. This supports the idea of carry crashes resulting from volatility surges instead of dynamic skewness.
A aprendizagem da Libras na formação inicial de professores/Libras learning in initial teacher training
(2024) Lopes, Raquel Aparecida; Seixas, Catharine Prata; Neves, Sylvia Lia Grespan
Este estudo tem como objetivo examinar evidências da aprendizagem da Língua Brasileira de Sinais (Libras) por estudantes do curso de Pedagogia, além de refletir sobre a inclusão da disciplina de Libras no ensino superior e sua relevância na formação inicial de professores. Foi adotada uma abordagem qualitativa, investigando-se 10 estudantes de uma instituição privada de ensino superior no Estado de São Paulo. Os dados foram coletados por meio de um instrumento no qual o pesquisador apresenta 2 frases em Libras, que os estudantes devem identificar e registrar. A análise dos dados revelou um baixo domínio dos estudantes na compreensão de estruturas frasais em Libras, indicando despreparo para atuar na educação de pessoas surdas e a necessidade de reavaliar a organização da disciplina de Libras nos currículos do ensino superior
Determinant factors of banking proftability: an application of quantile regression for panel data
(2024) ADRIANA BRUSCATO BORTOLUZZO; Ciganda, Rodrigo Ricardo; Bortoluzzo, Mauricio Mesquita
This study examines the determinants of bank proftability using a quantile regression approach, ofering insights into factors afecting banks across diferent percentiles of proftability. Utilizing a comprehensive database from Orbis covering 1200 top-market institutions across 101 countries, the research uniquely employs dynamic panel quantile regression while addressing sample survival bias. Our fndings highlight that bank size and capital adequacy nega tively impact proftability, whereas market value exerts a positive infuence on higher proftability banks. Credit risk afects proftability diferently across levels of proftability, and infation rate shows signifcance only for higher proft ability banks. The study contributes to the existing literature by ofering valuable insights into the factors determining bank proftability and how they behave at diferent percentiles in the sample, suggesting the importance of bank efciency and competition in promoting economic growth
Access to fresh food in vulnerable urban areas: a classificatory study of slums and formal establishments in São Paulo
(2024) ANDRÉ LUIS DE CASTRO MOURA DUARTE; VINICIUS PICANÇO RODRIGUES; Alves, Raquel Carolinne Freitas; Oliveira, Gustavo Magalhães de
The environment significantly influences individuals’ food choices. Vulnerable urban areas, such as favelas, can have a decisive impact on discouraging the consumption of fresh, nutritionally rich foods. This issue is exacerbated by the urban infrastructure required to deliver fresh foods to these locations. Therefore, it is essential to understand the context of the favelas in the municipality of São Paulo in terms of the food environment and infrastructure to support the design of public policies that enhance the presence of minimally processed foods in these areas. We applied the k-means clustering method to two datasets: the food environment of favelas, characterized by food establishments, and the urban infrastructure of the favelas in the municipality of São Paulo. Of the city’s 1,701 favelas, only 271 have formally registered food establishments. Larger favelas with better urban infrastructure generally exhibited a food environment with greater access to fresh foods. The results suggest that investing in urban infrastructure can increase access to fresh foods in these areas. It is also necessary to consider local specificities to find effective solutions that increase the availability of minimally processed foods, thereby improving the population’s quality of life and health.
Media manipulation in young democracies: evidence from the 1989 brazilian presidential election
(2024) Cavgias, Alexsandros; Corbi, Raphael; Meloni, Luis; Novaes, Lucas M.
We investigate how dominant media networks can manipulate voters in young democracies. During the first presidential election after the democratic transition in Brazil, TV Globo, the largest and most-watched network in the country, unexpectedly manipulated the news coverage of the last debate 2 days before the decisive second round. In a video segment, Globo unfavorably depicted the left-wing candidate, Luiz Inácio Lula da Silva. Using the geographical distribution of broadcaster-specific TV signals and the timing of election events, we identify the effect of the manipulation net of the effect of the debate itself, showing that Globo’s misleading reporting caused Lula to lose millions of votes. Our results showcase how the media can reshape an election in a single stroke, especially where the media is concentrated and politically inexperienced voters have few other sources of information.
Probabilistic Nearest Neighbors Classification
(2024) Fava, Bruno; PAULO CILAS MARQUES FILHO; HEDIBERT FREITAS LOPES
Analysis of the currently established Bayesian nearest neighbors classification model points to a connection between the computation of its normalizing constant and issues of NP-completeness. An alternative predictive model constructed by aggregating the predictive distributions of simpler nonlocal models is proposed, and analytic expressions for the normalizing constants of these nonlocal models are derived, ensuring polynomial time computation without approximations. Experiments with synthetic and real datasets showcase the predictive performance of the proposed predictive model.
All-cause, cardiovascular, and respiratory mortality and wildfire-related ozone: a multicountry two-stage time series analysis
(2024) Chen, Gongbo; Guo, Yuming; Yue, Xu; Xu, Rongbin; Yu, Wenhua; Ye, Tingting; Tong, Shilu; Gasparrini, Antonio; Bell, Michelle L; Armstrong, Ben; Schwartz, Joel; Jaakkola , Jouni J K; Lavigne , Eric; Saldiva, Paulo Hilario Nascimento; Kan, Haidong; Royé, Dominic; Urban, Aleš; Vicedo-Cabrera, Ana Maria; Tobias, Aurelio; Forsberg, Bertil; Sera, Francesco; Lei, Yadong; Abramson, Michael J; Li, Shanshan
Technological Adoption: The Case of PIX in Brazil
(2024) Gabriel Bernardes Amboage; GUILHERME FOWLER DE AVILA MONTEIRO; ADRIANA BRUSCATO BORTOLUZZO
Purpose This study investigates the primary determinants of consumers' intention to adopt PIX as a payment method in Brazil, as well as their actual usage behavior. Design/methodology/approach The study employs the Unified Theory of Acceptance and Use of Technology (UTAUT) to analyze both the intention to use and the actual period of use of PIX technology as a measure of practical usage. With this approach, researchers can determine whether people’s intention to use PIX translates into a higher rate of technology adoption and effective and sustained usage. The study collected data from 659 consumers across Brazil through a questionnaire and used structural equation analysis to analyze the data. Findings Research suggests that the intention to adopt PIX as a payment method is mainly determined by the perceived value, performance expectancy, and the habit of using mobile internet. Positive associations are also confirmed between adoption intention, the effective usage time of PIX, and the habit of using mobile internet in conjunction with PIX use. Originality/value The study’s uniqueness stems from its focus on the PIX usage, which is becoming the primary payment method in Brazil. It also measures the practical usage of the technology by examining the duration of user experience. This enables the assessment of whether the intention to use PIX effectively translates into a higher speed of technology adoption.
Decoupling Shrinkage and Selection in Gaussian Linear Factor Analysis
(2024) Bolfarine, Henrique; Carvalho, Carlos M.; HEDIBERT FREITAS LOPES; Murray, Jared S.
Factor analysis is a popular method for modeling dependence in multivariate data. However, determining the number of factors and obtaining a sparse orientation of the loadings are still major challenges. In this paper, we propose a decision-theoretic approach that brings to light the relationship between model fit, factor dimension, and sparse loadings. This relation is done through a summary of the information contained in the multivariate posterior. A two-step strategy is used in our method. First, given the posterior samples from the Bayesian factor analysis model, a series of point estimates with a decreasing number of factors and different levels of sparsity are recovered by minimizing an expected penalized loss function. Second, the degradation in model fit between the posterior of the full model and the recovered estimates is displayed in a summary. In this step, a criterion is proposed for selecting the factor model with the best trade-off between fit, sparseness, and factor dimension. The findings are illustrated through a simulation study and an application to personality data. We used different prior choices to show the flexibility of the proposed method.
Wildfire-sourced fine particulate matter and preterm birth risks in Brazil: A nationwide population-based cohort study
(2024) Zhang, Yiwen; Huang, Wenzhong; Xu, Rongbin; Ye, Tingting; Chen, Gongbo; Yue, Xu; Coêl , Micheline de Sousa Zanotti Stagliorio; Saldiva, Paulo Hilario Nascimento; Song, Jiangning; Guo, Yuming; Li, Shanshan
Wildfire-specific particulate matter with diameters ≤ 2.5 µm (PM2.5) is the key component of wildfire smoke, with potentially higher toxicity than PM2.5 from other sources. In this nationwide population-based cohort study, we included 22,163,195 births from Brazil during 2010–2019. Daily wildfire-specific PM2.5 was estimated through the chemical transport model. Time-varying Cox proportional hazards models were used to characterize the exposure-time-response (E-T-R) relationship between weekly wildfire-specific PM2.5 exposure and preterm birth (PTB) risks, followed by subgroup analyses. A 10 µg/m3 increment in wildfire-specific PM2.5 was associated with a hazard ratio of 1.047 (95 % confidence interval [CI]: 1.032–1.063) for PTB. Stronger associations between wildfire-specific PM2.5 and PTB were observed during earlier pregnancy, among female infants, and pregnant women < 18 years old, in ethnic minorities, with a length of education ≥ 11 years, from low-income or high temperature municipalities, and residing in North/Northeast regions. An estimated 1.47 % (95 % CI: 1.01 %–1.94 %) of PTBs were attributable to wildfire-specific PM2.5 in Brazil, increasing from 2010 to 2019. The PTBs attributable to wildfire-specific PM2.5 surpassed those attributed to non-wildfire PM2.5 (0.31 %, 95% CI: 0.09 %–0.57 %). Wildfire emerged as a critical source contributing to the PM2.5-linked PTBs. Prioritized fire management and emission control strategies are warranted for PTB prevention.
Digital Twin data architecture for Product-Service Systems
(2024) Durão, Luiz Fernando C.S.; Zancul, Eduardo; Schützer, Klaus
The digital representation of physical products by Digital Twins has been increasingly perceived as a relevant enabler for Product-Service Systems (PSS). Digital Twins concentrate product data that can be applied to generate insights and thus support value-added services. However, the literature on the intersection between Digital Twin and PSS has only recently started to receive more attention. There are still research gaps related to the required data and systems integration. In this context, this research aims to propose a Digital Twin data architecture to support Product-Service Systems operation. A Design Science Research (DSR) approach is applied, and the proposed architecture has been implemented and tested. Assessment results indicated that the proposed Digital Twin architecture fulfills the four requirements established from the literature: 1) facilitate and support the service offering; 2) acquire and transmit field operation and customer data; 3) integrate design and manufacturing data; 4) guarantee real-time monitoring, data integration, and data fidelity. The presented results provide an original contribution to the research area and can serve as a reference for applying Digital Twin to support PSS in practice.
DSSE: An environment for simulation of reinforcement learning-empowered drone swarm maritime search and rescue missions
(2024) Falcão, Renato Laffranchi; Oliveira, Jorás Custódio Campos de; Andrade, Pedro Henrique Britto Aragão; Rodrigues, Ricardo Ribeiro; FABRÍCIO JAILSON BARTH; Brancalion, José Fernando Basso
Wildfire-related PM2.5 and cardiovascular mortality: A difference-in-differences analysis in Brazil
(2024) Gao, Yuan; Huang, Wenzhong; Yu, Pei; Xu, Rongbin; Gasevic, Danijela; Yue, Xu; Coêlho, Micheline de Sousa Zanotti Stagliorio; Saldiva, Paulo Hilario Nascimento; Guo, Yuming; Li, Shanshan
Brazil has experienced unprecedented wildfires recently. We aimed to investigate the association of wildfire-related fine particulate matter (PM2.5) with cause-specific cardiovascular mortality, and to estimate the attributable mortality burden. Exposure to wildfire-related PM2.5 was defined as exposure to annual mean wildfire-related PM2.5 concentrations in the 1-year prior to death. The variant difference-in-differences method was employed to explore the wildfire-related PM2.5-cardiovascular mortality association. We found that, in Brazil, compared with the population in the first quartile (Q1: ≤1.82 μg/m3) of wildfire-related PM2.5 exposure, those in the fourth quartile (Q4: 4.22–17.12 μg/m3) of wildfire-related PM2.5 exposure had a 2.2% (RR: 1.022, 95% CI: 1.013–1.032) higher risk for total cardiovascular mortality, 3.1% (RR: 1.031, 95% CI: 1.014–1.048) for ischaemic heart disease mortality, and 2.0% (RR: 1.020, 95% CI: 1.002–1.038) for stroke mortality. From 2010 to 2018, an estimation of 35,847 (95% CI: 22,424–49,177) cardiovascular deaths, representing 17.77 (95% CI: 11.12–24.38) per 100,000 population, were attributable to wildfire-related PM2.5 exposure. Targeted health promotion strategies should be developed for local governments to protect the public from the risk of wildfire-related cardiovascular premature deaths.
"They don’t let us speak”: gender, collegiality, and interruptions in deliberations in the Brazilian Supreme Court
(2024) DIEGO WERNECK ARGUELHES; Alvim, Juliana Cesario; Nogueira, Rafaela; Wang, Henrique
In this paper, we examine a database containing court rulings and debates (acórdãos) of the Brazilian Supreme Court (“STF”) spanning from 1999 to 2018. Our objective is to analyze the relationship between gender and how judges behave when interacting with each other. Specifically, we investigate whether female judges are more likely to be interrupted by their colleagues during oral debates. Our data are built on real-time public interactions between the judges, as recorded in the Court's transcripts. The results show that female STF judges are interrupted more often than their male counterparts. While male judges display no specific effects, all three female judges in our data display a very significant and positive probability of being interrupted, as compared to their male colleagues participating in the same deliberations. These results show that, even in institutions designed to protect rights of political minorities, including women, gender dynamics, stereotypes and hierarchies can affect the functioning of courts in visible ways, with potential impacts on the rest of the judiciary and the legal profession. They also suggest that merely increasing the number of female judges, without addressing underlying gender dynamics and procedural rules in the judicial decision-making process, is insufficient to tackle the disadvantages women face within those institutions.

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