dc.contributor | Weise, Andreas Dittmar | |
dc.contributor | http://lattes.cnpq.br/1329623071793399 | |
dc.contributor | Jacobi, Luciane Flores | |
dc.contributor | Schmidt, Carla Adriana Pizarro | |
dc.creator | Battisti, Juliane de Freitas | |
dc.date.accessioned | 2023-03-16T11:58:20Z | |
dc.date.accessioned | 2023-09-04T19:31:54Z | |
dc.date.available | 2023-03-16T11:58:20Z | |
dc.date.available | 2023-09-04T19:31:54Z | |
dc.date.created | 2023-03-16T11:58:20Z | |
dc.date.issued | 2018-02-02 | |
dc.identifier | http://repositorio.ufsm.br/handle/1/28219 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8626489 | |
dc.description.abstract | In recent decades, the real estate market has been volatile in terms of economic behavior. This volatility happens due to several factors. Because of this, market monitoring is extremely important so that it is possible to point out the economic indicators that influence rental costs and how much each one impacts. In order to justify this dissertation, a bibliometric analysis was carried out by means of a quantitative descriptive approach, describing, evaluating and relating the main studies found. The specific objectives of this work were to survey the economic indicators and verify the condition of the residential real estate business, to analyze the influences of the data together with their impacts, verifying the most relevant factors of the Brazilian economy and, finally, to establish a mathematical model that describes the relationship between variables. The applied methodology was a statistical method of correlation and regression that are considered strongly related techniques, whose objective is to estimate a relationship that may exist between variables. It carried out the historical survey of the indicators for the years 2008 to 2016 in order to obtain the results. The model found showed an adjusted R² of 99.1%, providing a good adjustment that describes the rent value. The variables that compose this model appear in isolated or combined ways, being: the unemployment rate, SELIC, PIB and the Price of the Property. With the proposed model it is possible to verify which indicators have a greater relation with the rent price. | |
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 | Mercado imobiliário | |
dc.subject | Indicador econômico | |
dc.subject | Aluguel | |
dc.subject | Correlação | |
dc.subject | Regressão | |
dc.subject | Real estate market | |
dc.subject | Rent | |
dc.subject | Economic indicator | |
dc.subject | Correlation | |
dc.subject | Regression | |
dc.title | Análise da influência dos indicadores econômicos no custo do aluguel residencial no mercado de São Paulo | |
dc.type | Dissertação | |