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Identifying Noise Shocks: A VAR with Data Revisions

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  • RICCARDO M. MASOLO
  • ALESSIA PACCAGNINI

Abstract

We propose a new Vector Autoregression (VAR) identification strategy to study the impact of noise, in the early releases of output growth figures, which exploits the informational advantage of the econometrician. Economic agents, uncertain about the underlying state of the economy, respond to noisy early data releases. Econometricians, with the benefit of hindsight, have access to data revisions as well, which we use to identify noise shocks. A surprising report of output growth produces qualitatively similar but quantitatively smaller effects than a demand shock. We also illustrate how a noise shock cannot be identified unless ex‐post information is used.

Suggested Citation

  • Riccardo M. Masolo & Alessia Paccagnini, 2019. "Identifying Noise Shocks: A VAR with Data Revisions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(8), pages 2145-2172, December.
    • Handle: RePEc:wly:jmoncb:v:51:y:2019:i:8:p:2145-2172
    DOI: 10.1111/jmcb.12585
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    Cited by:

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    3. Kenza Benhima & Céline Poilly, 2017. "Do Misperceptions about Demand Matter? Theory and Evidence," Working Papers halshs-01518467, HAL.

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    More about this item

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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