No public surveys, no data? A proposal for income forecast in brazilian municipalities
Keywords:forecast income, spatial statistics, public data, public policies, census
Objective: Due to the lack of regularity from the census in Brazil, the proposal to use alternative indicators is relevant. The population's income, primary census information, is a variable used in studies in different areas such as public policies, forecasting, and planning a new business. However, on average, this information is released every ten years in Brazil; thus, it is necessary to explore frequency variables to estimate the population's income. In this sense, this study proposes a predictive income model based on technological and communication aspects.
Method: We choose two variables: internet and cable TV access. Our study included the analysis of the 5570 Brazilian municipalities through linear (OLS) and spatial models (Spatial Auto-Regressive [SAR] and Geographically Weighted Regression [GWR]).
Results: The results with the spatial models showed better results. The autoregressive spatial regression (SAR) presented a more significant explained variance (R2 = 0.51) than the linear model (R2 = 0.41) and the GWR model (R2 = 0.44), which indicates a significant spatial dependence and contribution of the geographic perspective in modeling and explaining the phenomenon.
Conclusion: The results were found to contribute to the development of public policies in regions with difficult access to information on the population's income and with managers and companies in the technology area that seek to plan the improvement and expansion of the provision of digital communication services through a model updated with secondary public data.
Abreu, L. C. de, Elmusharaf, K., & Siqueira, C. E. G. (2021). A time-series ecological study protocol to analyze trends of incidence, mortality, lethality of COVID-19 in Brazil. Journal of Human Growth and Development, 31(3), 491–495. https://doi.org/10.36311/jhgd.v31.12667
Anselin, L., & Florax, R. (2012). New directions in spatial econometrics. Springer Science & Business Media.
Boing, A. F., Boing, A. C., & Subramanian, S. (2021). Inequalities in the access to healthy urban structure and housing: An analysis of the Brazilian census data. Cadernos de Saúde Pública, 37, e00233119. https://doi.org/10.1590/0102-311X00233119
Brasil, A. (2022, January 25). Coleta de dados do Censo Demográfico 2022 começa em 1o de agosto. Agência Brasil. https://agenciabrasil.ebc.com.br/geral/noticia/2022-01/coleta-do-censo-demografico-2022-comeca-em-1o-de-agosto
Carlsson-Szlezak, P., Reeves, M., & Swartz, P. (2020). What coronavirus could mean for the global economy. Harvard Business Review, 3(10).
Cavalcante, P., & Lotta, G. S. (2021). Boundary-Crossing Strategies: Managing Macro Policies in a Federal Government. Revista de Administração Contemporânea, 25, e200012. https://doi.org/10.1590/1982-7849rac2021200012.en
Francisco, E. D. R. (2010). INDICADORES DE RENDA BASEADOS EM CONSUMO DE ENERGIA ELÉTRICA: ABORDAGENS DOMICILIAR E REGIONAL NA PERSPECTIVA DA ESTATÍSTICA ESPACIAL. https://doi.org/10.13140/RG.2.2.36634.03524
Greene, W. H. (2000). Econometric analysis 4th edition. International Edition, New Jersey: Prentice Hall, 201–215.
IBGE. (2021, December 13). IBGE reafirma plena confiança no orçamento de R$ 2,292 bilhões para o Censo 2022. https://www.ibge.gov.br/novo-portal-destaques/32553-ibge-reafirma-plena-confianca-no-orcamento-de-r-2-292-bilhoes-para-o-censo-2022.html
IBGE. (2023). IBGE | Portal do IBGE | IBGE. https://www.ibge.gov.br/
Jannuzzi, P. de M. (2018). A importância da informação estatística para as políticas sociais no Brasil: Breve reflexão sobre a experiência do passado para considerar no presente. SciELO Brasil. https://doi.org/10.20947/S0102-3098a0055
Janowicz, K., Gao, S., McKenzie, G., Hu, Y., & Bhaduri, B. (2020). GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond. International Journal of Geographical Information Science, 34(4), 625–636. https://doi.org/doi.org/10.1080/13658816.2019.1684500
Kabudula, C. W., Houle, B., Collinson, M. A., Kahn, K., Tollman, S., & Clark, S. (2017). Assessing Changes in Household Socioeconomic Status in Rural South Africa, 2001–2013: A Distributional Analysis Using Household Asset Indicators. Social Indicators Research, 133(3), 1047–1073. https://doi.org/10.1007/s11205-016-1397-z
Lascala, A. J., Silva, B. M. A., & de Rezende Francisco, E. (2018). Organização partidária e votos no Legislativo: Estudo das organizações municipais do PT e PSDB no estado de São Paulo a partir da composição e influência geográfica Party organization and votes in the legislature: Study of the municipal organizations of the PT and PSDB in Sao Paulo state from the composition and geographical influence. Revista Brasileira de Pesquisas de Marketing, Opinião e Mídia, 11(2), 175–189.
Lotta, G., & Pires, R. (2023). Public Policy Implementation in a Context of Extreme Inequality: Between Universalist Ambitions and Practical Selectivity. https://doi.org/10.1108/978-1-80262-655-120231019
Lü, G., Batty, M., Strobl, J., Lin, H., Zhu, A.-X., & Chen, M. (2019). Reflections and speculations on the progress in Geographic Information Systems (GIS): A geographic perspective. International Journal of Geographical Information Science, 33(2), 346–367. https://doi.org/10.1080/13658816.2018.1533136
Mari, A. (2020, November 10). Digital Services Surge Among Poor Brazilians Amid Pandemic. Forbes. https://www.forbes.com/sites/angelicamarideoliveira/2020/11/10/digital-services-surge-among-poor-brazilians-amid-pandemic/
Rehman, A. U., Saleem, R. M., Shafi, Z., Imran, M., Pradhan, M., & Alzoubi, H. M. (2022). Analysis of Income on the Basis of Occupation using Data Mining. 1–4. https://doi.org/10.1109/ICBATS54253.2022.9759040
Sami, J. (2011). Multivariate cointegration and causality between exports, electricity consumption, and real income per capita: Recent evidence from Japan. International Journal of Energy Economics and Policy, 1(3), 59–68.
Santos, M. (1978). Por uma geografia nova da crítica da geografia a uma geografia crítica.
Santos, M. (2002). A natureza do espaço: Técnica e tempo, razão e emoção (Vol. 1). Edusp.
Santos, M. (2012). Metamorfoses do espaço habitado: Fundamentos teóricos e metodológicos da geografia.
Santos, M., & Silveira, M. L. (2001). O Brasil: Território e sociedade no
início do século XXI.
Schabenberger, O., & Gotway, C. A. (2017). Statistical methods for spatial data analysis. CRC press.
SEADE. (2021). Conjunto de dados—SEADE Repositório. https://repositorio.seade.gov.br/dataset/
Silva, J. J. O., Zerboni, F., & Prado, M. (2012). Lubrax by Petrobras. Emerald Emerging Markets Case Studies, 2(8), 1–25. https://doi.org/10.1108/20450621211291798
Toledo Villacís, M. (2021). Estrategias post-COVID 19 para reactivar el Turismo local en el Ecuador: Caso provincia de Tungurahua. Green World Journal, 2021, Vol. 4, Num. 1-003, p. 1-12. https://dspace.uib.es/xmlui/handle/11201/155324
Walker, K. (2023). Analyzing us census data: Methods, maps, and models in R. CRC Press.
Widjaja, T., & Gregory, R. W. (2020). Monitoring the Complexity of IT Architectures: Design Principles and an IT Artifact. Journal of the Association for Information Systems, 21(3), 4. https://doi.org/10.17705/1jais.00616
World, H. O. (2023). Global research on coronavirus disease (COVID-19). https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov
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