Modelling abstention rate using spatial regression

Bibliographic Details
Main Author: Mota, Afonso Manita Santos
Publication Date: 2019
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/64940
Summary: Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
id RCAP_69f66de507f1fb230aa4247d1c8d35ab
oai_identifier_str oai:run.unl.pt:10362/64940
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Modelling abstention rate using spatial regressionVoter turnoutAbstention rateSociological VariablesEconomic VariablesSpatial AnalysisGeographically Weighted RegressionSpatial Non-StationarityDissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementDuring the last few elections that were held in Portugal, there have been very low percentages of voter turnout. This will obviously impact the result of those elections and can maybe be related to the general disenchantment of the population regarding the country’s recent political environment. This study aims to contribute to a better understanding of the patterns in the abstention rate of the last elections in Portugal. Sociological and economic variables such as age, unemployment rate, education level and many others will be used in trying to find out if they influence the abstention rate. It is logical to assume that the abstention rate in a certain municipality will be related to the abstention in neighboring municipalities. Therefore, the study also investigates if there is spatial autocorrelation in the abstention rates. Modeling a phenomenon like this with a simple linear regression model, estimated by Ordinary Least Squares (OLS), will render less efficient and biased results because of the spatial correlation of the observations and possible spatial clustering of values. Spatial regression methods have been proposed to overcome these drawbacks, particularly the Geographically Weighted Regression (GWR). This method will take into account possible local influences, allowing the coefficients of the model to vary depending on the geographic location, possibly obtaining a more appropriate fit. Many different OLS and GWR models were investigated by considering different combinations of explanatory variables and diagnosing their results through statistical tests and goodness-of-fit measures. Results show that indeed the data exhibits a non-random spatial pattern, and that a GWR model is a better approach in modeling abstention rates, when compared to an OLS model. Hence, the percentage of voter turnout in a municipality is likely to be better modelled taking into account its geographic location.Costa, Ana Cristina Marinho daRUNMota, Afonso Manita Santos2019-03-29T17:36:56Z2019-03-152019-03-15T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/64940TID:202208214enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:38:18Zoai:run.unl.pt:10362/64940Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:09:27.611732Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Modelling abstention rate using spatial regression
title Modelling abstention rate using spatial regression
spellingShingle Modelling abstention rate using spatial regression
Mota, Afonso Manita Santos
Voter turnout
Abstention rate
Sociological Variables
Economic Variables
Spatial Analysis
Geographically Weighted Regression
Spatial Non-Stationarity
title_short Modelling abstention rate using spatial regression
title_full Modelling abstention rate using spatial regression
title_fullStr Modelling abstention rate using spatial regression
title_full_unstemmed Modelling abstention rate using spatial regression
title_sort Modelling abstention rate using spatial regression
author Mota, Afonso Manita Santos
author_facet Mota, Afonso Manita Santos
author_role author
dc.contributor.none.fl_str_mv Costa, Ana Cristina Marinho da
RUN
dc.contributor.author.fl_str_mv Mota, Afonso Manita Santos
dc.subject.por.fl_str_mv Voter turnout
Abstention rate
Sociological Variables
Economic Variables
Spatial Analysis
Geographically Weighted Regression
Spatial Non-Stationarity
topic Voter turnout
Abstention rate
Sociological Variables
Economic Variables
Spatial Analysis
Geographically Weighted Regression
Spatial Non-Stationarity
description Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
publishDate 2019
dc.date.none.fl_str_mv 2019-03-29T17:36:56Z
2019-03-15
2019-03-15T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/64940
TID:202208214
url http://hdl.handle.net/10362/64940
identifier_str_mv TID:202208214
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833596475881291776

Similar Items