An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods

Timothy Erickson, A. Pakes
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引用次数: 51

Abstract

Until recently the Consumer Price Index consisted solely of "matched model" component indexes. The latter are constructed by BLS personnel who visit stores and compare prices of goods with the same set of characteristics over successive periods. This procedure is subject to a selection bias. Goods that were not on the shelves in the second period were discarded and hence never contributed price comparisons. The discarded goods were disproportionately goods which were being obsoleted and had falling prices. Pakes (2003) provided an analytic framework for analyzing this selection effect and showed both that it could be partially corrected using a particular hedonic technique and that the correction for his personal computer example was substantial. The BLS staff has recently increased the rate at which they incorporate techniques to correct for selection effects in their component indexes. However recent work shows very little difference between hedonic and matched model indices for non computer components of the CPI. This paper explores why. We look carefully at the data on the component index for TVs and show that differences between the TV and computer markets imply that to obtain an effective selection correction we need to use a more general hedonic procedure than has been used to date. The computer market is special in having well defined cardinal measures of the major product characteristics. In markets where such measures are absent we may need to allow for selection on unmeasured, as well as measured, characteristics. We develop a hedonic selection correction that accounts for unmeasured characteristics, apply it to TVs, and show that it yields a much larger selection correction than the standard hedonic. In particular we find that matched model techniques underestimate the rate of price decline by over 20%.
CPI的实验性成分指数:从计算机年度数据到其他商品的月度数据
直到最近,消费者价格指数仅由“匹配模型”成分指数组成。后者是由劳工统计局的工作人员构建的,他们访问商店并在连续的时期内比较具有相同特征的商品的价格。这一程序存在选择偏差。在第二阶段,没有在货架上的商品被丢弃,因此从来没有参与价格比较。被丢弃的货物是不成比例的正在被淘汰和价格下降的货物。Pakes(2003)为分析这种选择效应提供了一个分析框架,并表明它可以使用特定的享乐技术部分纠正,并且他的个人电脑示例的纠正是实质性的。劳工统计局的工作人员最近提高了他们在组成指数中采用技术来纠正选择效应的比率。然而,最近的研究表明,对于CPI的非计算机组成部分,享乐指数和匹配模型指数之间的差异很小。本文探讨了其中的原因。我们仔细研究了电视成分指数的数据,发现电视和电脑市场之间的差异意味着,为了获得有效的选择修正,我们需要使用一种比迄今为止使用的更普遍的享乐程序。计算机市场的特殊之处在于对主要产品特性有明确的基本衡量标准。在缺乏此类衡量标准的市场中,我们可能需要允许对未衡量特征和已衡量特征进行选择。我们开发了一种享乐选择校正,它可以解释未测量的特征,并将其应用于电视,并表明它产生的选择校正比标准享乐大得多。特别是,我们发现匹配的模型技术低估了20%以上的价格下降率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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