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Evolving Measurement for an Evolving Economy: Thoughts on 21st Century US Economic Statistics

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  • Ron S. Jarmin

Abstract

The system of federal economic statistics developed in the 20th century has served the country well, but the current methods for collecting and disseminating these data products are unsustainable. These statistics are heavily reliant on sample surveys. Recently, however, response rates for both household and business surveys have declined, increasing costs and threatening quality. Existing statistical measures, many developed decades ago, may also miss important aspects of our rapidly evolving economy; moreover, they may not be sufficiently accurate, timely, or granular to meet the increasingly complex needs of data users. Meanwhile, the rapid proliferation of online data and more powerful computation make privacy and confidentiality protections more challenging. There is broad agreement on the need to transform government statistical agencies from the 20th century survey-centric model to a 21st century model that blends structured survey data with administrative and unstructured alternative digital data sources. In this essay, I describe some work underway that hints at what 21st century official economic measurement will look like and offer some preliminary comments on what is needed to get there.

Suggested Citation

  • Ron S. Jarmin, 2019. "Evolving Measurement for an Evolving Economy: Thoughts on 21st Century US Economic Statistics," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 165-184, Winter.
  • Handle: RePEc:aea:jecper:v:33:y:2019:i:1:p:165-84
    Note: DOI: 10.1257/jep.33.1.165
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    More about this item

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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