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Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?

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  • Hecq, Alain
  • Telg, Sean
  • Lieb, Lenard

Abstract

This paper investigates the effect of seasonal adjustment filters on the identification of mixed causal-noncausal autoregressive (MAR) models. By means of Monte Carlo simulations, we find that standard seasonal filters might induce spurious autoregressive dynamics, a phenomenon already documented in the literature. Symmetrically, we show that those filters also generate a spurious noncausal component in the seasonally adjusted series. The presence of this spurious noncausal feature has important implications for modelling economic time series driven by expectation relationships. An empirical application on European inflation data illustrates these results. In particular, whereas several inflation rates are forecastable on seasonally adjusted series, they appear to be white noise using raw data.

Suggested Citation

  • Hecq, Alain & Telg, Sean & Lieb, Lenard, 2016. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," MPRA Paper 74922, University Library of Munich, Germany, revised 04 Nov 2016.
    • Handle: RePEc:pra:mprapa:74922
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    Cited by:

    1. Gianluca Cubadda & Alain Hecq & Sean Telg, 2019. "Detecting Co‐Movements in Non‐Causal Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(3), pages 697-715, June.
    2. Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
    3. Hecq, Alain & Voisin, Elisa, 2021. "Forecasting bubbles with mixed causal-noncausal autoregressive models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 29-45.
    4. Barend Abeln & Jan P. A. M. Jacobs, 2023. "CAMPLET: Seasonal Adjustment Without Revisions," SpringerBriefs in Economics, in: Seasonal Adjustment Without Revisions, chapter 0, pages 7-29, Springer.
    5. Fries, Sébastien & Zakoian, Jean-Michel, 2019. "Mixed Causal-Noncausal Ar Processes And The Modelling Of Explosive Bubbles," Econometric Theory, Cambridge University Press, vol. 35(6), pages 1234-1270, December.
    6. Hecq Alain & Sun Li, 2021. "Selecting between causal and noncausal models with quantile autoregressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(5), pages 393-416, December.
    7. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.
    8. Cleiton Guollo Taufemback, 2023. "Non‐parametric short‐ and long‐run Granger causality testing in the frequency domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(1), pages 69-92, January.
    9. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    10. Alain Hecq & Daniel Velasquez-Gaviria, 2022. "Spectral estimation for mixed causal-noncausal autoregressive models," Papers 2211.13830, arXiv.org.

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    More about this item

    Keywords

    seasonality; inflation; seasonal adjustment filters; mixed causal-noncausal models; autoregessive; noncausality; expectations;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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