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Área Temática ENEI: 1.2-Competição, preços e estruturas de mercado RESUMO Este trabalho tem como objetivo investigar o impacto que o uso do mobile e do home banking tiveram sobre as tarifas bancárias no Brasil entre 2011 e 2018. Inicialmente, apresenta-se uma evolução temporal do e-banking no Brasil. Em seguida, trata-se dos efeitos do e-banking sobre a concorrência, através do modelo de rede-cidade de Wang e Wang (2018), uma evolução dos modelos seminais de cidade linear de Hotteling (1929) e cidade circular de Salop (1979). Por fim, mostra-se o estudo empírico realizado, através do qual se conclui que as tarifas bancárias foram impactadas pelas plataformas digitais. Os resultados indicam que a diminuição dos custos de transporte, propiciada pela digitalização financeira, reduziu o preço das tarifas bancárias aos consumidores no período analisado.

The choice of a higher education course is one of the most important decisions individuals make, as it usually directs the choice of career or profession. Therefore, it is a complex decision, and it is thus possible that young individuals rely on heuristics and biases to facilitate the decision-making process. Considering that, we explored whether and how heuristics and biases affected college students’ judgments and decisions regarding courses. We developed a questionnaire and applied it to a sample of students in Brazil, and we analyzed the collected data using CATPCA and additional statistical methods. We found that students suffered from sunk-cost bias, in addition to the anchoring and representativeness heuristics. Additionally, we found no evidence of a framing effect. We conclude that heuristics and biases were relevant factors in students’ judgments and decisions, but they did not dominate them, operating, instead, in conjunction with traditional aspects of analysis and choice.

With the end of the recession from 2014 to 2016, Brazil began a gradual recovery process, with a positive impact on some economic variables-among them, credit financing. Despite this, a robust recovery was not seen in 2019, and 2020 was marked by the arrival of the Covid-19 pandemic, which raises questions about the stability of the financial system and the control of defaults. Considering this, the present study explores how macroeconomic variables affected the default of a financial institution's credit portfolio between January 2014 and April 2019. To perform this analysis, we built a Vector Error Correction (VEC) model that captured the long-term relationships between the default of different credit products and the selected macroeconomic variables. The results indicate that the macroeconomic variables do in fact impact default, however, this behavior is not homogeneous. In general, different credit products respond in different ways to each of the macroeconomic entities: while part of our findings is in line with others in the literature, we also found surprising results for some of the studied relationships. Contribution/Originality: This study contributes to the existing literature by demonstrating, through a case study in Brazil, the unique effects of the macroeconomic environment on the default of different and specific credit products, while most of the recent research focuses on aggregated data or default indexes. 1. INTRODUCTION After the economic recession that hit Brazil between 2014 and 2016 (CODACE-Economic Cycles Dating Committee, 2017) the first signs of a gradual recovery were confirmed in 2017, when-after a real 8.6% drop during the crisis-there was a 1.3% growth in Gross Domestic Product (GDP) (IBGE-Brazilian Institute of Geography and Statistics, 2019). This recovery continued throughout 2018 and 2019, with positive impacts on different Brazilian macroeconomic variables in a period of historically low inflation and interest rates. However, this gradual improvement was interrupted by the Covid-19 crisis, which still sows uncertainty about the future of the Brazilian and global economy (BACEN-Central Bank of Brazil, 2020b). Among the variables that were affected by this uncertainty are credit financing and default-both for individuals and companies. With regards to individuals, the increase in consumer confidence at the beginning of the economic recovery in Brazil resulted in annual credit growth rates of 8.4% in December 2018-the highest level since December 2015, when this rate was 7.2%-maintaining the pace of growth until the end of 2019 (BACEN-Central Bank of Brazil, 2020b). The types of credit that grew the most were consumer-oriented (credit card), vehicle