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금융위기 이후 경제학의 새로운 분석도구로서의 복잡계 이론

Complex Systems Theory as a New Economic Analysis Tool after the Financial Crisis

박하일|이대엽
이화사회과학원 (Ewha Institute of Social Sciences(EISS))|2012.12|사회과학연구논총 (Ewha Journal of Social Sciences)|제28권 |pp. 71-102|DOI 10.16935/ejss.2012.28..003

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참고문헌

키워드

시스템 리스크Systemic Risk행위자 기반 모형Agent-Based ModelComplex Network복잡계Complex System복잡 네트워크임계 전환Critical Transition
주제분류사회과학일반

초록

복잡계 이론은 시스템 동학의 갑작스런 변화를 설명하고 이를 사전에 예측하기 위해 발전해 왔으며 이와 관련된 복잡계 이론의 연구들은 최근의 금융위기를 이해하는 데 새로운 시각을 제시한다. 복잡계 이론은 복잡계를 구성하는 개별 구성요소들보다는 개별 구성요소들 간의 복잡한 상호작용이 야기하는 출현적 현상에 주목한다는 점에서 금융 시스템에서의 출현적 현상인 시스템 리스크를 이해하는데 기여하고 있다. 복잡계 이론은 향후 다음과 같은 분야에서 활용도가 높아질 것으로 예상된다. 복잡 네트워크 이론은 시스템 리스크의 측정 등 거시건전성의 부문 간 차원을 이해하는 데 유용하며, 복잡계의 임계 전환(critical transition)은 거시건전성의 동태적 차원을 분석하는 데 활용될 수 있다. 또한 행위자 기반 모형(ABM)은 현실의 복잡한 측면들을 모형에 도입하고 경제주체의 제한된 합리성과 학습 등을 중시한다는 점에서 경제주체의 높은 합리성을 가정하고 있는 동태적․확률적 일반균형(DSGE) 모형과 상호 보완적 역할을 수행할 것으로 기대된다.

Abstract

Complex systems theory has been developed to explain sudden changes in system dynamics and to make ex-ante predictions on such changes. Relevant studies on this theory provide new perspectives for understanding the recent financial crisis. Complex systems theory help understand systemic risk which is an emergent phenomenon in a financial system, in that it focuses on the emergent property resulting from complex interactions among individual components rather than on each component comprising the complexity. The use of complex systems theory is expected to increase in areas as follows. First, complex networks theory is useful in understanding the cross-sectional aspect of macro-prudentiality like the evaluation of systemic risk. Second, the studies on the critical transition of complex systems can shed some light on the dynamic aspect of macro-prudentiality. Also, an Agent-Based Model (ABM) is expected to play complementary roles to a Dynamic Stochastic General Equilibrium (DSGE) model which assumes high rationality of economic agents, in that agent-based modeling includes complex aspects of the real world into the model and places importance on the bounded rationality and learning of economic agents.

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