The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Autologistic models with an application to US presidential primaries considering spatial and temporal dependence

미국 대통령 예비선거에 적용한 시공간 의존성을 고려한 자기로지스틱 회귀모형 연구

  • Yeom, Ho Jeong (Department of Information and Industrial Engineering, Yonsei University) ;
  • Lee, Won Kyung (Department of Information and Industrial Engineering, Yonsei University) ;
  • Sohn, So Young (Department of Information and Industrial Engineering, Yonsei University)
  • 염호정 (연세대학교 정보산업공학과) ;
  • 이원경 (연세대학교 정보산업공학과) ;
  • 손소영 (연세대학교 정보산업공학과)
  • Received : 2017.01.05
  • Accepted : 2017.03.16
  • Published : 2017.04.30
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Abstract

The US presidential primaries take place sequentially in different places with a time lag. However, they have not attracted as much attention in terms of modelling as the US presidential election has. This study applied several autologistic models to find the relation between the outcome of the primary election for a Democrat candidate with socioeconomic attributes in consideration of spatial and temporal dependence. According to the result applied to the 2016 election data at the county level, Hillary Clinton was supported by people in counties with high population rates of old age, Black, female and Hispanic. In addition, spatial dependence was observed, representing that people were likely to support the same candidate who was supported from neighboring counties. Positive auto-correlation was also observed in the time-series of the election outcome. Among several autologistic models of this study, the model specifying the effect of Super Tuesday had the best fit.

미국 대통령 예선은 선거인단이 시차를 두고 여러 회에 걸쳐 진행되는 특징이 있음에도 많은 연구가 진행되지 않았다. 본 연구에서는 다양한 자기로지스틱 모형을 통해 미국 대통령 예비선거 결과와 사회경제적 변수간의 시공간 의존성의 관계를 파악하고자 한다. 2016년 데이터에 적용한 분석결과 각 카운티의 노년층, 흑인, 여성 그리고 히스패닉 인구 비율이 높은 지역일수록 힐러리 클린턴을 지지할 확률이 높은 것으로 나타났다. 또한, 주변 카운티에서 많은 지지를 받은 후보가 이웃 지역에서도 많이 지지를 받을 확률이 높고 이전 선거에서 많은 지지를 받는 것과 다음 선거 지역의 결과 간의 상관관계도 확인되었다. 시공간 의존성을 알아보기 위한 모형 중에서 슈퍼화요일의 선거 결과가 이후 선거와 관련이 있다고 가정한 모형의 설명력이 가장 높은 것으로 판명되었다.

Keywords

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