Analytical Bias Reduction for Small Samples in the U.S. Consumer Price Index
针对美国劳工统计局计算消费者价格指数时小样本导致的偏差，提出一种基于随机展开二阶项的廉价调整方法，并分解出1999-2003年间CPI-U与C-CPI-U差异中63%源于有限样本偏差。
The U.S. Bureau of Labor Statistics (BLS) faces sample size constraints when computing its Consumer Price Index (CPI–U). The samples are not sufficiently large for the index to equal a true “fixed basket” price index. This study adjusts for this small-sample bias by estimating the second order of a stochastic expansion of the index. Unlike increasing sample size, this adjustment is inexpensive because it uses the same data used to compute the CPI–U. From the beginning of 1999 to the end of 2003, we estimate that 63% of the difference between the BLS superlative index (C–CPI–U) and the CPI–U is the result of finite-sample bias, and the other 37% is commodity substitution bias.