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Measurement Error in Macroeconomic Data and Economics Research: Data Revisions, Gross Domestic Product, and Gross Domestic Income

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  • Phillip Li
  • Andrew C. Chang

Abstract

We analyze the effect of measurement error in macroeconomic data on economics research using two features of the estimates of latent US output produced by the Bureau of Economic Analysis (BEA). First, we use the fact that the BEA publishes two theoretically identical estimates of latent US output that only differ due to measurement error: the more well-known gross domestic product (GDP), which the BEA constructs using expenditure data, and gross domestic income (GDI), which the BEA constructs using income data. Second, we use BEA revisions to previously published releases of GDP and GDI. Using a sample of 23 published economics papers from top economics journals that utilize GDP as a key component of an estimated model, we assess whether using either revised GDP or GDI instead of GDP in the published paper would change reported results. We find that estimating models using revised GDP generates the same qualitative result as the original paper in all 23 cases. Estimatin g models using GDI, both with the GDI data originally available to the authors and with revised GDI, instead of GDP generates larger differences in results than those obtained with revised GDP. For 3 of 23 papers (13%), the results we obtain with GDI are qualitatively different than the original published results.

Suggested Citation

  • Phillip Li & Andrew C. Chang, 2015. "Measurement Error in Macroeconomic Data and Economics Research: Data Revisions, Gross Domestic Product, and Gross Domestic Income," Finance and Economics Discussion Series 2015-102, Board of Governors of the Federal Reserve System (U.S.), revised 10 Nov 2015.
  • Handle: RePEc:fip:fedgfe:2015-102
    DOI: 10.17016/FEDS.2015.102
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    Citations

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    Cited by:

    1. Andrew C. Chang & Phillip Li, 2015. "Is Economics Research Replicable? Sixty Published Papers from Thirteen Journals Say "Usually Not"," Finance and Economics Discussion Series 2015-83, Board of Governors of the Federal Reserve System (U.S.).
    2. Jan P.A.M. Jacobs & Samad Sarferaz & Jan-Egbert Sturm & Simon van Norden, 2018. "Can GDP measurement be further improved? Data revision and reconciliation," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-15, Economic Statistics Centre of Excellence (ESCoE).
    3. Chang, Andrew C., 2017. "A replication recipe: List your ingredients before you start cooking," Economics Discussion Papers 2017-74, Kiel Institute for the World Economy (IfW).
    4. Andrew C. Chang & Phillip Li, 2017. "A Preanalysis Plan to Replicate Sixty Economics Research Papers That Worked Half of the Time," American Economic Review, American Economic Association, vol. 107(5), pages 60-64, May.
    5. Andrew C. Chang, 2018. "Nothing is Certain Except Death and Taxes : The Lack of Policy Uncertainty from Expiring "Temporary" Taxes," Finance and Economics Discussion Series 2018-041, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    Keywords

    National Income and Product Accounts; Latent Output; Measurement Error; National Statistics; GDP; Data Vintages; GDI; Real-Time Data; Gross Domestic Product; NIPA; Data Revisions; Gross Domestic Income;

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

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