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From Noise to Turning Points: A New Framework for Seasonal Adjustment in Armenia

Author

Listed:
  • Minasyan , Gevorg

    (Asian Development Bank)

  • Schipper , Stefan

    (Asian Development Bank)

  • Khachatryan , Lusya

    (Statistical Committee of the Republic of Armenia)

  • Movsisyan, Seda

    (Statistical Committee of the Republic of Armenia)

  • Lapitan, Pamela

    (Asian Development Bank)

Abstract

This paper evaluates the transition from X12-ARIMA to X13-ARIMA-SEATS for the seasonal adjustment of Armenia’s quarterly national accounts (QNA). We analyze the methodological advancements and their impact on key economic indicators, focusing on the precision and reliability of seasonally adjusted data. Our findings suggest that the indirect seasonal adjustment method, despite larger revisions, is preferable, given potential variations in seasonal patterns among gross domestic product components and strong user preferences for preserving accounting relationships. Furthermore, a partial concurrent update strategy achieves a better balance between accuracy and revision minimization compared to current or fully concurrent methods. Finally, deriving seasonally adjusted price deflators from seasonally adjusted volume and current price data aligns more closely with the underlying economic structure of Armenian QNA, given that QNA data is available primarily in nominal terms. These results remain consistent across various sensitivity checks, supporting our methodological approach for analyzing Armenia's QNA series

Suggested Citation

  • Minasyan , Gevorg & Schipper , Stefan & Khachatryan , Lusya & Movsisyan, Seda & Lapitan, Pamela, 2025. "From Noise to Turning Points: A New Framework for Seasonal Adjustment in Armenia," ADB Economics Working Paper Series 786, Asian Development Bank.
  • Handle: RePEc:ris:adbewp:0786
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    More about this item

    Keywords

    Armenia; JDemetra+; national accounts; seasonal adjustment; X13-ARIMA-SEATS;
    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
    • 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
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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