捷克共和国的消费价格指数 - 新来源和数据处理

Jaroslav Sixta, Petr Musil
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引用次数: 0

摘要

消费价格指数自 20 世纪 90 年代在捷克共和国发布以来,多年来一直是人们关注的焦点,但最近的价格增长引发了更多关于价格统计方法和数据来源的问题。用户感兴趣的不仅是数字本身,还有影响解释的统计问题以及经常被用作通货膨胀率近似值的消费价格指数的质量。本文介绍了捷克统计局编制的价格统计数据,并特别关注数据来源,尤其是扫描仪数据。论文解释了官方统计编制中如何采用机器学习等先进的统计方法。我们认为,官方统计正处于历史的转折点上,现代统计方法将在这里得到应用。我们的论文展示了机器学习程序在消费价格指数扫描数据中的应用。所使用的方法基于逻辑回归和强大的 Python 解决方案,可提供快速、高质量的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consumer Price Index in the Czech Republic – New Sources and Data Processing
Consumer price index has been in the centre of interest for many years, since being published in 1990s in the Czech Republic but recent price growth raised more questions on methodology and data sources used in price statistics. Users are interested not only in the figures itself but also in statistical issue influencing interpretation and the quality of consumer price index that is often used as an approximation of inflation rate. The paper introduces price statistics compiled by the Czech Statistical Office and it specifically focuses on data sources and in particular scanner data. The paper explains how advanced statistical methods such as machine learning are implemented in official statistical production. We think that the official statistics is being on the historical junction where modern methods are going to be implemented. Our paper shows the usage of machine learning procedures applied on scanner data within consumer price index. Used method is based on logistic regression and powerful Python solution and that provides fast and high quality results.
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