Rounding Error: A Distorting Influence on Index Data
指出指数数据中常见的四舍五入误差会扭曲方差性质、改变时间序列模型的滞后分布并导致系数估计偏差，例如用官方CPI计算通胀率时会出现异常波动，建议使用更高精度的数据来避免这些问题。
Rounding error is an important source of measurement error that is common in index data. The problem can be traced to rounding that occurs to limit the number of digits after the decimal place to be reported in rebased index data. Rounding error introduces distortions that affect variance properties, alter the lag distributions of time series models, and cause a systematic bias in estimated coefficients. For instance, spuriously choppy inflation rates are obtained when constructed using the official CPI, rebased with 1982-84 = 100. Fortunately, the distortions can be generally avoided by using versions of data that have greater precision.