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Micro and Macro Data Integration: The Case of Capital

Randy Becker (), John Haltiwanger, Ron Jarmin (), Shawn Klimek () and Daniel Wilson ()

Working Papers from U.S. Census Bureau, Center for Economic Studies

Abstract: Micro and macro data integration should be an objective of economic measurement as it is clearly advantageous to have internally consistent measurement at all levels of aggregation – firm, industry and aggregate. In spite of the apparently compelling arguments, there are few measures of business activity that achieve anything close to micro/macro data internal consistency. The measures of business activity that are arguably the worst on this dimension are capital stocks and flows. In this paper, we document, quantify and analyze the widely different approaches to the measurement of capital from the aggregate (top down) and micro (bottom up) perspectives. We find that recent developments in data collection permit improved integration of the top down and bottom up approaches. We develop a prototype hybrid method that exploits these data to improve micro/macro data internal consistency in a manner that could potentially lead to substantially improved measures of capital stocks and flows at the industry level. We also explore the properties of the micro distribution of investment. In spite of substantial data and associated measurement limitations, we show that the micro distributions of investment exhibit properties that are of interest to both micro and macro analysts of investment behavior. These findings help highlight some of the potential benefits of micro/macro data integration.

New Economics Papers: this item is included in nep-mac
Date: 2005-05
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https://www2.census.gov/ces/wp/2005/CES-WP-05-02.pdf First version, 2005 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:cen:wpaper:05-02

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