dc.contributor | Zanini, Roselaine Ruviaro | |
dc.contributor | http://lattes.cnpq.br/4332331006565656 | |
dc.contributor | Cruz, Rafael Cabral | |
dc.contributor | http://lattes.cnpq.br/1246969166762146 | |
dc.contributor | Souza, Adriano Mendonça | |
dc.contributor | http://lattes.cnpq.br/5271075797851198 | |
dc.creator | Noronha, Maiara de Oliveira | |
dc.date.accessioned | 2019-09-11T21:03:29Z | |
dc.date.accessioned | 2022-10-07T23:48:12Z | |
dc.date.available | 2019-09-11T21:03:29Z | |
dc.date.available | 2022-10-07T23:48:12Z | |
dc.date.created | 2019-09-11T21:03:29Z | |
dc.date.issued | 2017-08-11 | |
dc.identifier | http://repositorio.ufsm.br/handle/1/18200 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/4041662 | |
dc.description.abstract | The debate on the causes of climate and environmental changes is structured by studies that point out, as one of the main factors, the increase of energy demand. Renewable sources are relevant in a country's energy planning because they are linked to the creation of opportunities for technological, economic and productive development guided by the principles of sustainability. Thus, the objective of this study was to investigate the relation between the capacity of electric generation by renewable sources and Brazilian macroeconomic variables. The analysis of the interrelationships between electricity generation capacity and economic growth in Brazil, from April 2009 to March 2017, was carried out by means of the Autoregressive Vectors methodology. It was possible to verify that the variance of employment is explained by renewable sources: hydroelectric in 7.71%, biomass in 1.99%, wind energy in 3.13% and solar energy in 10.58%, while the GDP variance is explained by 3.15% for hydroelectric energy, 0.06% for biomass, 1.70% for wind energy and 17.38% for solar energy. The export variance is explained by renewable sources: hydroelectric 2.48%, biomass 0.39%, wind energy 2.34% and solar energy 17.58%. Finally, the variance of the minimum wage is explained by hydroelectric energy in 1.48%, biomass in 5.09%, wind energy in 9.09% and solar energy in 10.67%. Thus, the analysis of the Response Impulse Function and the Decomposition of Variance allowed us to verify that the installed capacity for the production of electric energy exerts influence on the Brazilian macroeconomic variables considered in this study. | |
dc.publisher | Universidade Federal de Santa Maria | |
dc.publisher | Brasil | |
dc.publisher | Engenharia de Produção | |
dc.publisher | UFSM | |
dc.publisher | Programa de Pós-Graduação em Engenharia de Produção | |
dc.publisher | Centro de Tecnologia | |
dc.rights | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.subject | Energias renováveis | |
dc.subject | Energias não-renováveis | |
dc.subject | Crescimento econômico | |
dc.subject | Modelo vetor autorregressivo | |
dc.subject | Renewable energy | |
dc.subject | Non-renewable energies | |
dc.subject | Socioeconomic development | |
dc.subject | Autoregressive vector model | |
dc.title | A relação entre a capacidade de geração elétrica por fontes renováveis e não-renováveis e o crescimento econômico no Brasil | |
dc.type | Dissertação | |