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새로운 "산출-산출모형"과 "산출-산출표"를 어떻게 활용할 것인가? 투입-산출모형과 투입-산출표에 대한 대안분석을 중심으로

Publication Date
  • 산출&#8901
  • 산출모형
  • 산출&#8901
  • 산출표
  • 요인별 분해
  • 최종수요&#8231
  • 최종산출모형
  • 레온티에프 역행렬
  • 보완된 일반적 관계
  • 산출계수행렬
  • 유발계수행렬
  • Economics


How Do We Utilize a New "Output-Output Model" and "Output-Output Table" Based on an Alternative Analysis to the Input-Output Model and the Input-Output Table Gim and Kim(2008a, 2008c), recently, found out that there is no consecutive connection between the Leontief inverse and the total output and that there are some limits to compute the impact effects of the initial change of output. Thus a new "output-output(OO) model" was developed by the authors to solve the consecutive connection and overestimation problems very naturally based on the output requirements matrix for output . On the basis of the latest research findings mentioned above, the specific objectives of this paper are summarized as follows. (1) We reexamine the merits and demerits of different types of input-output(IO) models: the demand side, the supply side, and the mixed type. (2) We perform a comparative analysis between the IO and OO models in structure and characteristics and illustrate the usefulness and validity of the OO model. (3) We derive the relevant equations between the cause and effect variables, which are needed to compute induced effects, multiplier effects, and linkage effects by using the newly developed OO model and table. (4) We present some good application examples focused on the empirical economic analysis based on raw data of 『2003 Input-Output Tables』compiled by the Bank of Korea. The major findings from the empirical analysis are followed below. We calculated output, employment, and income multipliers and impact and sensitivity coefficients for final demand and output through the Leontief inverse and the output requirements matrix for output. The Spearman's rank correlation coefficients are specially computed to observe the relevant structural economic characteristics of each sector between two different employment multipliers and between two kinds of income multipliers and between two types of sensitivity coefficients. The between employment multipliers is 0.9878 and that between income multipliers is 0.9402 and that between sensitivity coefficients is 0.9962. The higher values which are more close to 1 mean that the entire priority ranks between multipliers(or coefficients) are almost the same through the whole sectors. Key Words: output-output model, output-output table, consecutive connection, output requirements matrix, input requirements matrix, complemented general relation, multi-sector multiplier, alternative model

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