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Testing for News and Noise in Non-Stationary Time Series Subject to Multiple Historical Revisions

Author

Listed:
  • Alain Hecq
  • Jan P.A.M. Jacobs
  • Michalis P. Stamatogiannis

Abstract

Before being considered definitive, data currently produced by statistical agencies undergo a recurrent revision process resulting in different releases of the same phenomenon. The collection of all these vintages is referred to as a real-time data set. Economists and econometricians have realized the importance of this type of information for economic modeling and forecasting. This paper focuses on testing non-stationary data for forecastability, i.e., whether revisions reduce noise or are news. To deal with historical revisions which affect the whole vintage of time series due to redefinitions, methodological innovations etc., we employ the recently developed impulse indicator saturation approach, which involves potentially adding an indicator dummy for each observation to the model. We illustrate our procedures with the U.S. Real Gross National Product series from ALFRED and find that revisions to this series neither reduce noise nor can be considered as news.

Suggested Citation

  • Alain Hecq & Jan P.A.M. Jacobs & Michalis P. Stamatogiannis, 2016. "Testing for News and Noise in Non-Stationary Time Series Subject to Multiple Historical Revisions," CIRANO Working Papers 2016s-01, CIRANO.
    • Handle: RePEc:cir:cirwor:2016s-01
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    1. M. Mogliani & T. Ferrière, 2016. "Rationality of announcements, business cycle asymmetry, and predictability of revisions. The case of French GDP," Working papers 600, Banque de France.

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    More about this item

    Keywords

    Data revision; Non-Stationary Data; News-Noise Tests; Structural Breaks;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • 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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