关键词: 社会核算矩阵, 平衡方法, 加权, 离差熵平方期望, 先验信息

Abstract: Considering the defects of the RAS and Cross-Entropy(CE) approaches that losing the priori information when they are applied for the balance of the Social Accounting Matrix(SAM), this paper proposes the weighted approach which is based on minimizing the expectation of the deviation entropy square. And it constructs the weighting matrix in accordance with the degree of the prior information. Meanwhile, this paper takes the Chinese unbalanced SAM in 2007 as an example, and compares the real effects of balancing among RAS approach, CE approach and weighted approach based on minimizing the expectation of the deviation entropy square. And the results show that: RAS approach gets the results with a larger deviation, while the results produced by CE approach and weighted approach based on minimizing the expectation of the deviation entropy square are more accurate. Furthermore, weighted approach based on minimizing the expectation of the deviation entropy square can make flexible and effective use of the prior information and avoiding this deadweight loss of effective information, but RAS and CE approaches do not have this advantage.