ON THE BIAS OF MULTIPLIER ESTIMATES*
研究了当基础数据随机时乘数矩阵的偏误，指出传统方法会导致交易表偏误，而采用从业者视角时，乘数矩阵每行内的偏误加权平均为零，结果与RAS更新程序直接相关。
ABSTRACT. This paper considers the bias of the matrix of multipliers when the underlying data are random. The traditional approach is to specify the stochastic nature of the input coefficients directly. It is shown that this approach implies a transactions table which is biased in a most unbalanced way. Next the practitioner's point of view, i.e., taking the transactions table as the source of random errors, is adopted. One of the results states that, within each row of the multiplier matrix, either the biases are zero, or positive biases are canceled out by negative biases in the sense that their weighted average is zero. The conditions are based on the idea that information on aggregates is more exact than information on their details. The usual asumptions of independence and unbiasedness of the individual errors are avoided. The results are shown to have a direct interpretation in connection with the RAS‐updating procedure.