The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Time series analysis for the amount of medicine from the Korea Consumer Agency

한국 소비자원 의료분야 처리금액에 대한 시계열 분석

  • Hee Song Kang (Korea Research Institute for Local Administration Office of Planning and Coordination) ;
  • Sukhui Kwon (Interdisciplinary Program in Big Data, Chungbuk National University) ;
  • SungDuck Lee (Department of Information & Statistics, Chungbuk National University)
  • 강희송 (한국지방행정연구원 기획조정실) ;
  • 권숙희 (충북대학교 빅데이터협동과정) ;
  • 이성덕 (충북대학교 정보통계학과)
  • Received : 2022.08.19
  • Accepted : 2022.09.13
  • Published : 2023.02.28
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Abstract

The amount of money processed in medicine from the Korea Consumer Agency was studied by the various time series models. The medical data set from the Korea Consumer Agency were consisted of counseling, damage relief and conciliation. For the analysis of time series, autoregressive moving average model, vector autoregressive model and the transfer function model were used. We considered the stationarity and cross correlation function for the identification and fitting. As a result, the transfer function model showed a better prediction. Whereas, the vector autoregressive model also provided good information for the degree and duration of the influence of variables.

한국 소비자원의 의료 분야 처리금액 자료에 대한 시계열 모형을 이용한 실증 분석을 연구하였다. 의료분야 처리금액 시계열 자료는 상담 처리금액, 피해 구제금액, 분쟁 조정 처리금액으로 나뉜 3개 변수를 사용하였고 분석에 사용된 시계열 모형은 ARIMA 모형, 벡터 자기회귀 모형 그리고 전이 함수를 이용한 시계열 모형이다. 이들 중 전이 함수를 이용한 시계열 모형이 단기 예측면에서 가장 우수한 예측력을 보였고 벡터자기회귀 모형도 변수간 영향력과 기간을 파악하는데 유용한 정보를 제공하였다.

Keywords

Acknowledgement

이 논문은 충북대학교 국립대학육성사업(2022)지원을 받아 작성되었음.

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