MEASURING THE IMPACT OF PRODUCTION SECTORS ON PER CAPITA INCOME OF SANTA CATARINA MUNICIPALITIES: AN ECONOMETRIC ANALYSIS
DOI:
https://doi.org/10.54805/RCE.2527-1180.v6.n1.128Keywords:
Production Sectors, Per capita income, Panel data regression, EconometricsAbstract
The aim of this study is to measure, through panel data regression models, the degree of association between sectoral gross value added (GVA) and per capita income. For this, a survey was conducted with 295 municipalities in the State of Santa Catarina in the period 2010-2014. As a method, we chose to develop panel data regression models (pooled, within, random), to verify the degree of association between the variables GDP per capita (dependent variable), industry, services and agriculture (independent variables) . Data referring to the VAB and per capita income series were obtained through the database of the State Secretariat for Sustainable Economic Development of Santa Catarina (SEDES). The results obtained point to the relevance of the industrial sector regarding the generation of wealth in the municipalities analyzed, given that, of the three sectors analyzed, it was the only one that presented positive effects in relation to the response variable (per capita income). The agricultural and service sectors showed significant negative effects. It was also verified, through statistical tests, that the fixed effects model is more efficient for the defined purpose when compared to the others. The main contribution of this research is the use of the panel data model to estimate parameters in GDP aggregates of a state of the federation (SC). In addition, the article was written with the R markdown tool (RStudio), which allows R codes to be embedded in the text. In this way, the research can also be used as a regression tutorial in R..
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