重新设计国家主要经济指标

Gabriel Ehrlich, J. Haltiwanger, Ron S. Jarmin, David Johnson, M. Shapiro
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引用次数: 12

摘要

从企业和家庭收集数据的传统方法面临越来越大的挑战。这些问题包括调查回复率下降,传统数据收集模式成本上升,以及难以跟上经济快速变化的步伐。几乎所有市场交易的数字化为重新设计关键的国家经济指标提供了潜力。统计系统面临的挑战是如何在这种数据丰富的环境中运行。本文关注的是在源头收集项目级数据的机会,以及使用与这种数据基础设施相一致的测量方法构建关键指标的机会。无处不在的交易数字化使得价格和数量可以在源头上同时收集或汇总。这种新的经济统计架构带来了销售项目快速变化带来的挑战。本文探讨了最近提出的在大规模项目级数据中估计价格和数量指标的一些技术。虽然这些方法显示出巨大的希望,但在它们准备作为官方经济统计的基础之前,还需要进行大量的研究。最后,本文论述了数据收集交易对建立国家统计的影响,以及21世纪统计机构的能力和组织。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Re-Engineering Key National Economic Indicators
Traditional methods of collecting data from businesses and households face increasing challenges. These include declining response rates to surveys, increasing costs to traditional modes of data collection, and the difficulty of keeping pace with rapid changes in the economy. The digitization of virtually all market transactions offers the potential for re-engineering key national economic indicators. The challenge for the statistical system is how to operate in this data-rich environment. This paper focuses on the opportunities for collecting item-level data at the source and constructing key indicators using measurement methods consistent with such a data infrastructure. Ubiquitous digitization of transactions allows price and quantity be collected or aggregated simultaneously at the source. This new architecture for economic statistics creates challenges arising from the rapid change in items sold. The paper explores some recently proposed techniques for estimating price and quantity indices in large scale item-level data. Although those methods display tremendous promise, substantially more research is necessary before they will be ready to serve as the basis for the official economic statistics. Finally, the paper addresses implications for building national statistics from transactions for data collection and for the capabilities and organization of the statistical agencies in the 21st century.
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