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

Thursday, November 3, 2016
Columbia Ballroom (Washington Hilton)

*Names in bold indicate Presenter

Andrew C. Chang, Federal Reserve - Board of Governors and Phillip Li, Office of the Comptroller of the Currency


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 use 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. Estimating 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.