의제설정이론에서 그랜저 인과관계 모형의 방법론적 타당성 연구

국문 초록 (Abstract)

이 글은 의제설정이론의 기존 연구방법을 검토하고, 동태적 분석을 통한 새로운 방법론적 대안을 제시한다. 의제설정 효과 연구에선 미디어, 수용자, 정부라는 세의제 간에 서로 영향을 주고받는다는 상호관계가 존재한다고 가정한다. 하지만 이러한 상호 인과관계의 영향력이 효과적으로 통제되지 않았다. 이러한 한계는 그동안 대다수 의제설정연구가 횡단면적 분석으로 이루어졌으며, 전후관계를 충분하게 고려하지 못했기 때문에 발생했다. 의제설정 과정은 본질적으로 정태적이기 보다는 시간에 따라 변화하는 동태적인 구조를 지닌다. 따라서 이 글은 의제설정 가설 검정에서 시계열 분석의 벡터자기회귀(VAR) 모형을 적용해 그랜저 인과관계가 존재하는지를 파악할 것을 제안한다. 벡터자기모형은 ① 변수 간의 관계를 일방향이 아닌 쌍방향적으로 규명할 수 있으며, ② 시간의 순서에 따라 의제설정효과의 전후관계를 밝혀낼 수 있으며, ③ 기본적 시계열분석에서 할 수 없는 세변수 이상을 동시에 측정할 수 있으며, ④ 의제의 속성별 특성을 구분해 측정할 수 있으며, ⑤ 개별적인 미시적 분석이 아니라 거시적이고 집합적인 차원에서 의제 간 상관관계를 밝혀낼 수 있다는 장점을 제공한다. 의제설정 연구에서 시간의 개념과 자기상관성을 고려해야 하며, 비선형성과 역동성 그리고 항상성의 관점에서 의제설정 가설을 보다 정확하게 검정해야 한다는 점을 중심으로 토론했다.

다국어 초록 (Multilingual Abstract)

Briefly reviewing the existing literature on agenda-setting theory, we suggest a multivariate time series approach for the dynamic analysis of agenda-setting hypothesis. It has been assumed in agenda-setting effects research that the media agenda has influence on both the audience and government agendas sequentially, and these two agendas also affect the media agenda reciprocally. Nevertheless, these non-recursive relationships have not been fully calculated due to methodological limitations. Most agenda setting research has been conducted based on cross-sectional data. Researchers have yet to determine conclusively the “before-after” relationships of how the media agenda influences the audience and government agendas respectively. The principle process of agenda-setting is not static but dynamic as researchers include time-lag lengths into their model. Thus, we suggest that communication researchers use the vector autoregression (VAR) model for their agenda-setting research since it has proven to be especially useful for describing the dynamic behavior of time-series agenda variables. Moreover, we contend that communication researchers should conduct Granger causality tests when they examine the agenda-setting hypothesis. The VAR model offers more accurate identification of the non-recursive influence of independent variables on the dependent ones. In addition, it can show the “before-after” relationship by incorporating time-lag lengths in the model. The VAR model can also include more than three variables in the time-series analysis, and it measures the influence of media agenda attributes. Overall, the VAR model holds advantages by using aggregate data at the macro-level to figure out the media coverage’s effect on both audience and government agendas after controlling the exogenous variables. From the multivariate time-series perspective, we discuss the possible contribution of the VAR model to the dynamic analysis of agenda-setting research.

목차 (Table of Contents)

• 1. 의제설정 연구방법론에 대한 문제제기
• 2. 기존 의제설정 연구방법론 검토
• 3. 시계열 디자인의 한계와 가능성
• 4. VAR 시계열 분석 적용연구
• 5. 결론 및 논의
• 참고문헌
• 부록
• abstract

참고문헌 (Reference)

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