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Deepening GDP revision analysis: GDP bias breakdown and compositional change

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  • Ignacio Martínez

Abstract

This paper contributes to the GDP revision literature by developing a novel methodology to further analyse the statistical properties of GDP series. We undertake two specific analyses: (i) To identify which of the main GDP components contributes the most to the presence (or absence) of a GDP growth revision bias, and (ii) To test the presence of a significant compositional change between data vintages. We apply these methodologies to the Chilean data for the period 2006-2019. Our main results show that the absence of a GDP growth revision bias is due to compensating effects between its main components. Finally, we don't find significant evidence for a potential compositional change among different data vintages.

Suggested Citation

  • Ignacio Martínez, 2021. "Deepening GDP revision analysis: GDP bias breakdown and compositional change," Economic Statistics Series 136, Central Bank of Chile.
    • Handle: RePEc:chb:bcchee:136
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    File URL: https://www.bcentral.cl/documents/33528/133329/EEE_136.pdf
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    References listed on IDEAS

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    1. Deirdre N. McCloskey & Stephen T. Ziliak, 1996. "The Standard Error of Regressions," Journal of Economic Literature, American Economic Association, vol. 34(1), pages 97-114, March.
    2. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    3. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
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