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Voter Turnout in Portugal: a Geographical Perspective

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Voter Turnout in Portugal: a Geographical Perspective VOTER TURNOUT IN PORTUGAL: A GEOGRAPHICAL PERSPECTIVE Liliana Alexandra Silvério Raposo Guerreiro da Câmara Manoel Dissertation presented as partial requirement for obtaining the Master’s degree in Statistics and Information Management i NOVA Information Management School Instituto Superior de Estatística e Gestão de Informação Universidade Nova de Lisboa VOTER TURNOUT IN PORTUGAL: A GEOGRAPHICAL PERSPECTIVE Liliana Alexandra Silvério Raposo Guerreiro da Câmara Manoel Dissertation presented as partial requirement for obtaining the Master’s degree in Statistics and Information Management, with a specialization in Information Analysis and Management. Advisor: Pedro da Costa Brito Cabral, PhD Co‐supervisor: Ana Cristina Marinho da Costa, PhD August 2019 ii DEDICATION (OPTIONAL) To Nuninho, who sleeps while I write. ii ACKNOWLEDGEMENTS To my supervisors, Professor Ana Cristina Costa and Professor Pedro Cabral, for all the support, patience and knowledge. Without them, this would be impossible. To Nuno, for his encouragment, support and love. iii ABSTRACT The decline of voter turnout in Portugal has been confirmed in the last legislative election of 2015. This fact, together with the unquestionable democratic value associated with the act of voting, leads to the discussion of the issue and emphasizes the need for additional investigation concerning the portuguese context. Particularly, it is crucial to identify the characteristics of citizens who vote, to better understand the phenomenon and think about solutions. This work aims to identify the most significant sociodemographic variables in explaining voter turnout in continental Portugal and describe the relationship between those variables and voter turnout, including the geographical variation existing across the municipalities. Data related to sociodemographic variables are provided from population census 2011, and turnout results concerns the legislative election of the same year. The chosen variables have been addressed in literature, both in meta-analyses studies and in country level empirical investigation. The analysis starts with the conventional Ordinary Least Squares (OLS), and continue with more spatially sensitive methods, namely Geographically Weighted Regression (GWR) and its semiparametric extension (SGWR). The final method, SGWR, enables the investigation of local variations in turnout values, simultaneously considering that its relationship with some variables might not vary over space. Results show that turnout is a complex process, influenced by a set of sociodemographic variables. While some variables affect turnout differently over the country (percentage of family cores with children aged less than 15, and percentage of owner-occupied houses), others affect it uniformly (percentage of graduated residents, percentage of classic families, and distance to Lisbon or Oporto – the nearest). This highlights the use of a semiparametric approach to better understand turnout and for further research on voting issues. KEYWORDS Portugal; voter turnout; sociodemographic variables; semiparametric geographically weighted regression (SGWR); spatial variability. iv INDEX 1. Introduction .................................................................................................................. 1 1.1. Background ............................................................................................................ 1 1.2. Study relevance ..................................................................................................... 4 1.3. Study objectives..................................................................................................... 5 2. Literature review .......................................................................................................... 6 2.1. Results of empirical work around the world ......................................................... 6 2.1.1. Sociodemographic variables........................................................................... 6 2.1.2. Institutional variables ................................................................................... 14 2.1.3. Political variables .......................................................................................... 17 2.2. Studies concerning the portuguese context ....................................................... 18 2.2.1. Sociodemographic variables......................................................................... 18 2.2.2. Political and institutional variables .............................................................. 21 3. Methodology .............................................................................................................. 23 3.1. Data ..................................................................................................................... 24 3.2. Analysis ................................................................................................................ 26 3.2.1. Ordinary Least Squares................................................................................. 26 3.2.2. Geographically Weighted Regression .......................................................... 27 3.2.3. Semiparametric Geographically Weighted Regression ................................ 27 4. Results......................................................................................................................... 29 4.1. OLS and variables selection ................................................................................. 29 4.2. GWR ..................................................................................................................... 30 4.3. SGWR ................................................................................................................... 32 5. Conclusion .................................................................................................................. 40 5.1. Discussion and limitations ................................................................................... 40 5.2. Recommendations for future works ................................................................... 43 References ....................................................................................................................... 44 v LIST OF FIGURES Figure 1 - Overview of the methodological framework. .......................................................... 23 Figure 2 - OLS standard residuals. ............................................................................................ 30 Figure 3 - Model GWR 1 standard residuals. ........................................................................... 32 Figure 4 - Model SGWR 4 standard residuals. .......................................................................... 34 Figure 5 - Model SGWR 4 local R2. ........................................................................................... 35 Figure 6 - Model SGWR 4 local coefficient estimates of variable «percentage of family cores with children aged less than 15 (P_Nucle_F1)». .............................................................. 36 Figure 7 - Model SGWR 4 local standard errors of variable «percentage of family cores with children aged less than 15 (P_Nucle_F1)». ...................................................................... 37 Figure 8 - Model SGWR 4 local coefficient estimates of variable «percentage of owner- occupied houses (P_Res_Hab)». ...................................................................................... 38 Figure 9 - Model SGWR 4 local standard errors of variable «percentage of owner-occupied houses (P_Res_Hab)». ...................................................................................................... 39 vi LIST OF TABLES Table 1 - Initial variables of the study. ..................................................................................... 25 Table 2 - OLS results. ................................................................................................................ 29 Table 3 - OLS diagnostics. ......................................................................................................... 29 Table 4 - Comparison of OLS and GWR models. ...................................................................... 31 Table 5 - Comparison of SGWR models results. ....................................................................... 33 Table 6 - Model SGWR 4 global variables estimates. ............................................................... 35 vii LIST OF ABBREVIATIONS AND ACRONYMS AICc Corrected Akaike Information Criterion GWR Geographically Weighted Regression OLS Ordinary Least Squares SGWR Semiparametric Geographically Weighted Regression VIF Variance Inflation Factor viii 1. INTRODUCTION Voter turnout is a fundamental issue in any democracy (Douglas, 2013; M. N. Franklin, 2004; Ribeiro, Borba, & da Silva, 2015) and, although it is not the only form of political participation, its importance is undeniable (Aldrich, 1993; Fornos, Power, & Garand, 2004). There have been a number of studies focusing on the causal determinants of voting behavior (Finkel, 1985; Geys, 2006; Ribeiro et al., 2015), concerning consolidated democracies but also newly democratic regimes (Fornos et al., 2004). Accordingly, it is important to identify, in Portugal, factors that influence voting. 1.1. BACKGROUND Voter turnout is the total number of eligible voters who participate in an election. This is strongly related with other usual concept, the electoral absenteeism – the difference
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