Bio
Dr. Philipp Ehrl is a Professor at the School of Public Policy and Government of Fundação Getulio Vargas (FGV EPPG) in Brasília, Brazil. He holds a Doctorate in Economics from the University of Passau. His research spans diverse areas including telecommunications policy, financial regulation, and behavioral economics, with a particular focus on the Brazilian context. Dr. Ehrl has authored numerous papers on topics such as the design evaluation of universalization funds for telecommunication services, the pricing of subordinated financial notes, mobile internet access and data plan choice, and credit card interest rate regulation. With an h-index of 10 and over 350 citations, his work contributes significantly to the fields of economics and public policy.
Educational Journey
Universidade de São Paulo
Dr. in Economics • Economics
2014Experience
FGV EPPG
0 - 0Professor
2023 - Present • School of Public Policy and GovernmentAssociate Professor
2016 - 2023 • EconomicsEditors Role
Reviewer
GJHSS
2024 - PresentResearch
Design Evaluation of the Universalization Fund for Telecommunication Services in Brazil
The Universalization Fund for Telecommunications Services (Fust) was designed in 2000 to provide public investments to expand services in areas that needed to be better covered by the telecom carries. However, since its creation, the fund lacks effectiveness. The study seeks to evaluate this public policy and explain the practically non-existent results and impacts until now. Our contribution is to structure this public policy using a logic model and the program theory of change to understand and evaluate the fund’s regulatory design. The analysis recognizes that the recent changes in Fust’s legislation have improved its architecture and governance, following suggestions from the international literature on universalization funds. Nonetheless, some additional regulatory adjustments are suggested, such as creating more restrictive mechanisms to block or reallocate the fund’s revenues, keeping its steering committee active, discussing new sources of revenue, and improving communication and transparency.
Subordinated Financial Notes: An Analysis of the Factors That Explain Their Price
A Letra Financeira Subordinada (LFS) é um tipo de instrumento que possibilita a captação com efeito na composição de capital do banco. O investimento nesse papel é considerado de alto risco para o investidor, pois existe a possibilidade de perda do rendimento em caso da não geração de lucro do banco emissor e perda do valor principal em caso de falência. Para compreender as caracterÃsticas da LFS foram analisadas a legislação e as normas que tratam sobre o instrumento financeiro. Posteriormente estimou-se o valor de negociação de LFS no mercado secundário a partir de variáveis econômicas e de crédito, através de regressão linear múltipla. A análise de correlação demonstrou que as variáveis de valor da LFS estão mais correlacionadas com as variáveis de crédito do que com as variáveis econômicas. O resultado da regressão principal mostrou que o estoque das carteiras de crédito do banco e o nÃvel do PIB possuem o maior poder explicativo sobre o preço dos LFS.
Credit Card Interest Rate Regulation in Brazil Behavioral Biases Present in the Market and Possible Impacts
O presente estudo analisa as implicações econômicas e comportamentais associadas à regulação das taxas de juros no mercado de cartões de crédito no Brasil, com foco na recente regulamentação que estabeleceu limites para juros e encargos financeiros em operações de crédito rotativo e parcelado. A pesquisa contextualiza a importância dos cartões de crédito como meio de pagamento, destacando o impacto das altas taxas de juros e inadimplência no sistema financeiro. A análise abrange fatores estruturais, como o custo do crédito e os vieses comportamentais que influenciam as decisões dos consumidores e empresas, discutindo os possÃveis efeitos da regulação, incluindo mudanças nas estratégias dos emissores, redução da oferta de crédito e o papel do parcelamento sem juros no consumo. O trabalho também propõe reflexões sobre educação financeira e incentivos ao uso consciente do crédito como ferramentas para uma inclusão financeira mais sustentável.
Understanding Mobile Internet Access and Data Plan Choice in Brazil: A Machine Learning Approach
This paper applies the Elastic Net Machine Learning technique to choose the variables that best represent the characteristics of mobile internet use in Brazil. We use regularized models to estimate the importance of a large number of variables, including socioeconomic attributes, internet and device utilization patterns, and digital skills to explain (a) access to the internet through mobile devices and (b) choice of mobile data plan. After identifying the most important variables, we estimate their marginal effects on the two dependent variables with nonlinear econometric models. The results suggest that socioeconomic characteristics and user skills have significant explanatory power in both estimations. Specifically, barriers such as age, income, and skill gaps persist, hindering inclusive mobile internet adoption. Conditional on mobile internet use, these characteristics are more common among postpaid internet data plan subscribers. Moreover, communication skills like messaging and social media use stand out regarding internet access, whereas internet utilization patterns (on the move and at work) have high explanatory power in the data plan choice.
