Examining voter turnout using multiscale geographically
weighted regression: The case of Slovakia

J 2023

Examining voter turnout using multiscale geographically weighted regression: The case of Slovakia

KEVICKÝ, Dominik and Jonáš SUCHÁNEK

Basic information

Original name

Examining voter turnout using multiscale geographically weighted regression: The case of Slovakia

Authors

KEVICKÝ, Dominik (703 Slovakia, belonging to the institution) and Jonáš SUCHÁNEK

Edition

Moravian Geographical Reports, Sciendo, 2023, 1210-8812

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

50700 5.7 Social and economic geography

Country of publisher

Poland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 2.500 in 2022

RIV identification code

RIV/00216224:14310/23:00132230

Organization unit

Faculty of Science

DOI

http://dx.doi.org/10.2478/mgr-2023-0014

UT WoS

001082385900004

Keywords in English

voter turnout; parliamentary elections; theories of voter turnout; multiscale geographically weighted regression; left behind places; Slovakia

Abstract

V originále

Voter turnout is an essential aspect of elections and often reflects the attitude of a country's population towards democracy and politics. Therefore, examining the distribution of voter turnout and determining the factors that influence whether or not people will vote is crucial. This study aims to find significant factors that underlie the different levels of electoral participation across regions in Slovakia during the 2020 parliamentary elections. In this interpretation, special attention is paid to the ability of the main theories of voter turnout to explain the behaviour of Slovak voters. The primary analytical tool is multiscale geographically weighted regression, which represents an advanced local regression modelling variant. The results indicate that the multiscale geographically weighted regression is superior to the global ordinary least square model in virtually all aspects. Voter turnout is generally higher in economically and socially prosperous localities and regions, which is in line with the societal modernisation theory. Additionally, factors connected to mobilisation theory and the concept of 'left behind places' also proved to be valuable. However, in other cases, such as with the share of retirees and potential habitual voting, the outcomes were not overly convincing, and further research is required.

Citovat

KEVICKÝ, Dominik and Jonáš SUCHÁNEK. Examining voter turnout using multiscale geographically weighted regression: The case of Slovakia. Moravian Geographical Reports. Sciendo, 2023, vol. 31, No 3, p. 153-164. ISSN 1210-8812. Available from: https://dx.doi.org/10.2478/mgr-2023-0014.

@article{2339121,
   author = {Kevický, Dominik and Suchánek, Jonáš},
   article_number = {3},
   doi = {http://dx.doi.org/10.2478/mgr-2023-0014},
   keywords = {voter turnout; parliamentary elections; theories of voter turnout; multiscale geographically weighted regression; left behind places; Slovakia},
   language = {eng},
   issn = {1210-8812},
   journal = {Moravian Geographical Reports},
   title = {Examining voter turnout using multiscale geographically weighted regression: The case of Slovakia},
   url = {https://doi.org/10.2478/mgr-2023-0014},
   volume = {31},
   year = {2023}
}

TY  - JOUR
ID  - 2339121
AU  - Kevický, Dominik - Suchánek, Jonáš
PY  - 2023
TI  - Examining voter turnout using multiscale geographically weighted regression: The case of Slovakia
JF  - Moravian Geographical Reports
VL  - 31
IS  - 3
SP  - 153-164
EP  - 153-164
PB  - Sciendo
SN  - 12108812
KW  - voter turnout
KW  - parliamentary elections
KW  - theories of voter turnout
KW  - multiscale geographically weighted regression
KW  - left behind places
KW  - Slovakia
UR  - https://doi.org/10.2478/mgr-2023-0014
N2  - Voter turnout is an essential aspect of elections and often reflects the attitude of a country's population towards democracy and politics. Therefore, examining the distribution of voter turnout and determining the factors that influence whether or not people will vote is crucial. This study aims to find significant factors that underlie the different levels of electoral participation across regions in Slovakia during the 2020 parliamentary elections. In this interpretation, special attention is paid to the ability of the main theories of voter turnout to explain the behaviour of Slovak voters. The primary analytical tool is multiscale geographically weighted regression, which represents an advanced local regression modelling variant. The results indicate that the multiscale geographically weighted regression is superior to the global ordinary least square model in virtually all aspects. Voter turnout is generally higher in economically and socially prosperous localities and regions, which is in line with the societal modernisation theory. Additionally, factors connected to mobilisation theory and the concept of 'left behind places' also proved to be valuable. However, in other cases, such as with the share of retirees and potential habitual voting, the outcomes were not overly convincing, and further research is required.
ER  -

KEVICKÝ, Dominik and Jonáš SUCHÁNEK. Examining voter turnout using multiscale geographically weighted regression: The case of Slovakia. \textit{Moravian Geographical Reports}. Sciendo, 2023, vol.~31, No~3, p.~153-164. ISSN~1210-8812. Available from: https://dx.doi.org/10.2478/mgr-2023-0014.

Detailed Information on Publication Record