Bacharelado em Ciências Econômicas (Sede)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/7
Siglas das Coleções:
APP - Artigo Publicado em Periódico
TAE - Trabalho Apresentado em Evento
TCC - Trabalho de Conclusão de Curso
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5 resultados
Resultados da Pesquisa
Item Análise da recuperação de materiais recicláveis: uma aplicação do Propensity Score Matching na base de dados do SNIS(2023-09-14) Silva, Vicente Henrique da Costa; Araújo, Chiara Natércia França; http://lattes.cnpq.br/7273384016233113; http://lattes.cnpq.br/6905236621140933This undergraduate thesis aims to assess the impact of the implementation of Muni-cipal Integrated Solid Waste Management Plans (PMGIRS), as stipulated in Law No. 12,305/2010 - the National Solid Waste Policy. The central methodological approach utilizes the concept of Propensity Score Matching (PSM) to explore the causal effect of the presence of PMGIRS on the Recycling Material Recovery Rate. Additionally, the research incorporates the use of k-means clustering with the aim of better cha-racterizing and classifying the analyzed sample. This allows for the identification of natural data clusters and a deeper understanding of different potentials for solid was-te management in distinct municipalities. PSM is employed to create comparable groups of municipalities with and without PMGIRS, balancing observable characteris-tics and controlling for potential selection biases. The results obtained from this me-thodology will contribute to a well-founded and objective analysis of the impact of PMGIRS on municipal solid waste management. Combining PSM with clustering will enhance the analysis, enabling a more comprehensive characterization and precise classification of the studied sample.Item Localização das empresas do setor de tecnologia em Pernambuco: uma análise exploratória de dados espaciais(2022-10-13) Santana, Mariana Maria Freitas de; Silva, Diego Firmino Costa da; http://lattes.cnpq.br/8895265465747877; http://lattes.cnpq.br/3786228704990357The present research aims to analyze how technology companies are located, beyond the metropolitan region of Recife. For this, three variables were considered: total number of companies in the technology sector in the state, total number of employed persons and volume of salaries and remuneration paid. The data were obtained through the IBGE for the period between 2006 and 2019. The methodology used was the Exploratory Analysis of Spatial Data, which consists of detailing and visualizing the spatial distributions of the data studied, identifying, for example, if there are atypical locations (outliers spatial) and patterns of spatial associations (clustering and spatial clusters). More specifically, the methods used were univariate global spatial autocorrelation, which uses only one indicator for the entire region analyzed in order to find out if the data are randomly distributed or if they are linked to some systematic spatial pattern, through Moran's I coefficient. The other method is univariate local spatial autocorrelation, which checks whether global patterns of spatial autocorrelation can be associated with local patterns. The results indicated at first that the technology sector is losing its agglomeration characteristic in the Metropolitan Region of Recife, migrating to cities further away from the center such as Caruaru, Petrolina and Serra Talhada.Item Uma análise exploratória de dados espaciais para criminalidade violenta no estado de Pernambuco(2021-12-15) Silva, Thalia Ariely Marques; Araújo, Chiara Natércia França; Silva, Diego Firmino Costa da; http://lattes.cnpq.br/8895265465747877; http://lattes.cnpq.br/7273384016233113This study aims to identify spatial patterns in violent crime rates in the state of Pernambuco, northeastern Brazil, based on the Economic Theory of Crime. Through the application of the rates of CVLI (Lethal and Intentional Violent Crime) and CVP (Violent Crime against Property), which represent the rates of homicide and robbery, in the period from 2014 to 2020, as variables of interest. For this proposal, the AEDE (Spatial Data Exploration Analysis) methodology was used, with the intention of testing spatial autocorrelation and identifying spatial clusters. With this, spatial clusters were identified, for both variables, in the mesoregions: Sertão, Agreste and RMR (Metropolitan Region of Recife). In addition, it was verified the rupture of the pattern of behavior in the year 2020 in different ways for each variable under study, as a possible effect of the covid-19 pandemic. It was also noted a possibility of future study regarding the increment of the income variable with the GDP (Gross Domestic Product) per capita of each municipality, by performing a spatial analysis with bivariate Local Moran's I, which resulted in low autocorrelation.Item Desempenho médio das Gerências Regionais da Educação em Pernambuco: uma análise de aglomerado do ensino médio(2022-06-03) Santos, Paula Tárcimam Gomes; Soares, Ana Paula Amazonas; http://lattes.cnpq.br/0216127558312955; http://lattes.cnpq.br/6790001160720461The present work is of an exploratory nature, presenting an analysis of the performance of the Regional Managements of Education -GRE, in the municipalities of the State of Pernambuco. With the hypothesis that the good performance of high school GREs students in 2019 in the state of Pernambuco can contribute to regional economic performance. And GREs located spatially closer to each other may reflect more similar performances. The objective is to verify the performance of high school students from all municipalities in the state through the data provided by the 2019 SAEB, linked to the characteristics of the Schools, Directors, Teachers and Socioeconomics of the Student. Therefore, there is the intention to identify groups that present similar characteristics. For this purpose, the cluster analysis technique was used. Due to the hierarchical clustering methodology, which considered the Ward's distance (minimum variation of differences), they were performed in the Rstudio Software and analyzing the dynamics of the formation of clusters (or groups). The technique made it possible to accurately visualize, through the manipulated variables, the performance of the GRE and to know the profile of the modal student of the year 2019. The results indicate that the GRE with the best performance, with a higher average in Portuguese and Mathematics, above average of the State, are located in the Sertão of Pernambuco. And the most present profile of high school students, they declare: brown, live with parents and siblings, live in urban areas, have easy access to school, study in state schools and have the participation of parents in their school life.Item Política pública educacional e SAEB 2019: análises de agrupamento por microrregiões de Pernambuco(2022-06-03) Santos, Kleybson Rodrigo Martins; Soares, Ana Paula Amazonas; http://lattes.cnpq.br/0216127558312955; http://lattes.cnpq.br/7919130450780875Education is seen not only by common sense, but also by economic theory as one of the main factors driving development. In this context, the present work, which has an exploratory approach, aims to investigate socioeconomic issues that are capable of influencing the performance of students in the state of Pernambuco, in Brazil. For this, microdata from the Sistema de Avaliação da Educação Básica (Basic Education Assessment System, Saeb) of 2019 was used, totaling 76,596 students—after due data treatment—, also adding socioeconomic variables, with which cluster analyzes were performed by three multivariate methods (hierarchical method, K-means and PAM), in the statistical software R. The results of the tests of averages pointed out a heterogeneity in the student's performance among microregions of Pernambuco and, later, a susceptibility to overflow of policies between sets of nearby microregions was found. This work also focuses on the 2015-2025 State Education Plan, elucidating its content, goals and strategies, in order to contextualize the exploratory analysis.