No public surveys, no data? A proposal for income forecast in brazilian municipalities

Ricardo Limongi; Rafael Martins Ronqui; Pedro Paulo Coelho; Eduardo de Rezende Francisco

doi:10.5585/2023.22993

Autores/as

Ricardo Limongi Federal University of Goiás and Federal University of Uberlândia / Goiânia - GO https://orcid.org/0000-0003-3231-7515
Rafael Martins Ronqui Fundação Getulio Vargas / School of Business Administration of São Paulo, São Paulo - SP http://orcid.org/0000-0002-9588-5926
Pedro Paulo Coelho Fundação Getulio Vargas / School of Business Administration of São Paulo, São Paulo - SP http://orcid.org/0000-0001-6238-4749
Eduardo de Rezende Francisco Fundação Getulio Vargas / School of Business Administration of São Paulo, São Paulo - SP http://orcid.org/0000-0001-8895-2089

DOI:

https://doi.org/10.5585/2023.22993

Palabras clave:

previsión de ingresos, estadísticas espaciales, datos públicos, políticas públicas, censo

Resumen

Objetivo: Debido a la falta de regularidad del censo en Brasil, la propuesta de utilizar indicadores alternativos es relevante. El ingreso de la población, información primaria del censo, es una variable utilizada en estudios en diferentes áreas como las políticas públicas, la previsión y la planificación de un nuevo negocio. Sin embargo, en promedio, esta información se publica cada diez años en Brasil; por lo tanto, es necesario explorar variables de frecuencia para estimar los ingresos de la población. En este sentido, este estudio propone un modelo predictivo de ingresos basado en aspectos tecnológicos y de comunicación.

Metodo: Elegimos dos variables: acceso a internet y televisión por cable. Nuestro estudio incluyó el análisis de los 5570 municipios brasileños a través de modelos lineales (OLS) y espaciales (Spatial Auto-Regressive [SAR] y Geographically Weighted Regression [GWR]).

Resultados: Los resultados con los modelos espaciales mostraron mejores resultados. La regresión espacial autorregresiva (SAR) presentó una varianza explicada más significativa (R2 = 0.51) que el modelo lineal (R2 = 0.41) y el modelo GWR (R2 = 0.44), lo que indica una dependencia espacial significativa y aporte de la perspectiva geográfica en modelización y explicación del fenómeno.

Conclusión: Los resultados fueron encontrados para contribuir al desarrollo de políticas públicas en regiones con difícil acceso a la información sobre los ingresos de la población y con empresarios y empresas del área de tecnología que buscan planificar la mejora y ampliación de la prestación de servicios de comunicación digital a través de un modelo actualizado con datos públicos secundarios.

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Biografía del autor/a

Ricardo Limongi, Federal University of Goiás and Federal University of Uberlândia / Goiânia - GO

PhD in Business Administration in the line of Marketing Strategies from EAESP/FGV, with a doctoral internship at Cornell University under the supervision of Vithala Rao. Permanent Professor and Coordinator of the Graduate Program in Business Administration at UFG. Associate Editor of the Accounting, Management and Governance Magazine (CGG). He coordinates the MBA in Strategic Marketing. Leads research topic in the Marketing Division since 2019 at ANPAD - National Association of Graduate Studies and Research in Administration. His research has already been nominated and/or awarded by the international database Emerald (2015/2017) and scientific events such as SEMEAD (2013) and EMA (2014/2018). He had projects approved in Scientific Notices by the Goiás State Research Support Foundation (FAPEG) and by CNPQ. His research is linked to themes such as Behavioral Economics and Performances Applied to Marketing; Econometric Modeling; Experiments in Marketing and Machine Learning. He acts as coordinator of ADMKT - Teaching, Research and Extension Group in Marketing and Data Analytics (https://admkt.face.ufg.br/), created in 2012, and certified by CNPq.

Rafael Martins Ronqui, Fundação Getulio Vargas / School of Business Administration of São Paulo, São Paulo - SP

Professional Master in Management for competitiveness. Four graduate degrees. Graduated in computer engineering. Computer Technician. I have worked for over 20 years with IT, supply processes and eight years as an undergraduate professor. Ten years with SAP at Nestlé, working with some modules, currently MM and transportation, with local and global projects. I'm writing an article on the implementation of agile projects, looking for quality, another one on circular economy focused on helping the collector with IT support and published one on Big Data with NoSQL and Redis. Digital transformation projects, Power BI, RPA and Compliance. Project management. Coordination of the SAP automation process - GRC, Nestlé and Coca-Cola FEMSA. Development and implementation of systems aimed at the areas of supply chain, sales, marketing, legal and finance with more than a thousand users. Java Developer. Active participation in meetings with other markets in English and Spanish. Management of collaborators and third parties. Responsible for the transportation module in SAP, acting not only in the purchasing part, but also in what involves the other parts of the process (sales and finance). High knowledge in changing and creating master data of suppliers, materials, customers, products and data cleansing. ABAP development specifications with code and requirements. Systems with data in the cloud. IT Careers Lecturer. Use of the Scrum and PMI methodology, at Nestlé and in the classroom. Knowledge of other agile methodologies, such as SAFe. Specialist in object-oriented Java and WEB languages such as HTML 5, JavaScript, PHP and CSS. Advanced knowledge of SQL and Power BI. Supplier development. Microsoft teams and Zoom. Using the R language for analytics and big data. ChatBot implementation with curation, customer experience and big data. Use of R language

Pedro Paulo Coelho, Fundação Getulio Vargas / School of Business Administration of São Paulo, São Paulo - SP

Graduated in Economic Sciences (bachelor's degree) at the Pontifical Catholic University of São Paulo (2015) and graduated (bachelor's degree) in Geography at the University of São Paulo (2015). He is currently a Master's student in Public Administration and Government (CMAPG) at FGV-EAESP and professor of Geography at Colégio Bandeirantes. He created and developed economics and politics teaching projects at the same institution and at Colégio Ítaca (São Paulo) from 2012 to 2016. He is interested in interdisciplinary themes related to the areas of educational and socio-environmental public policies, human geography, education and industry economics public.

Eduardo de Rezende Francisco, Fundação Getulio Vargas / School of Business Administration of São Paulo, São Paulo - SP

He holds a PhD (2010) and a Master's (2006) in Business Administration from Fundação Getulio Vargas - EAESP and holds a bachelor's degree in Computer Science from the Institute of Mathematics and Statistics of the University of São Paulo (1999). He has been Vice-Coordinator of the Undergraduate Course in Business Administration at FGV EAESP since February 2019, responsible for the academic management of double degrees (with Economics and Law) and double degrees with international partner schools. He is a Career Professor at the Department of Technology and Data Science (TDS) at FGV EAESP, where he has been teaching since 2011. He teaches courses related to GeoAnalytics, Data Science, Artificial Intelligence, Big Data, Business Analytics, Applied Statistics and Spatial Statistics. He is the coordinator of the FGV Continuing Education course (FGV PEC) called Geographic Intelligence for Decision Support. He was a visiting researcher at the Department of Information Science at the University of Otago, in New Zealand. Has experience in the area of predictive models for Microcredit, Marketing, Applied Statistics, Geostatistics, Demography and Geotechnologies in general, with emphasis on Data Mining, working mainly on the following topics: Microcredit, Geomarketing, Business Intelligence, Customer Satisfaction and Integration of Technologies de Informação.
He was a professor at ESPM from 2014 to 2018. He coordinated the MBA in Big Data Applied to Marketing (EAD modality) and the Short Course "Big Data Analytics in Decision Making" at ESPM in September 2016 to December 2018. He was professor of the NDE of the Information Systems Courses (TECH) at ESPM (coordinator of the Digital Business Intelligence track) from 2014 to 2018, of the Executive MBA and of the Professional Master's Degree in Consumer Behavior (MPCC) at ESPM from 2015 to 2018 and the Graduate Course in Business Administration in 2018. He was academic coordinator of the International Module Consumer Behavior: Big Data of ESPM, conducted in January 2018 in France, Luxembourg and the United Kingdom. He is a founding partner and responsible for Business Analytics and Spatial Statistics at GisBI, a group that studies and promotes integration between Business Intelligence and GIS (since 2012). He has been a member of the Board of Trustees of Fundação SEADE (São Paulo State Data Analysis System) since September 2016.

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