IDEAS home Printed from https://ideas.repec.org/a/vrs/offsta/v38y2022i2p399-428n11.html

Assessing Residual Seasonality in the U.S. National Income and Product Accounts Aggregates

Author

Listed:
  • Chen Baoline

    (U.S. Bureau of Economic Analysis, 4600 Silver Hill Road, Washington DC 20233, U.S.A.)

  • McElroy Tucker S.

    (U.S. Census Bureau, 4600 Silver Hill Road, Washington DC 20233-9100, U.S.A.)

  • Pang Osbert C.

    (U.S. Census Bureau, 4600 Silver Hill Road, Washington DC 20233-9100, U.S.A.)

Abstract

There is an ongoing debate on whether residual seasonality is present in the estimates of real Gross Domestic Product (GDP) in U.S. national accounts and whether it explains the slower quarter-one GDP growth rate in the recent years. This article aims to bring clarity to this topic by (1) summarizing the techniques and methodologies used in these studies; (2) arguing for a sound methodological framework for evaluating claims of residual seasonality; and (3) proposing three diagnostic tests for detecting residual seasonality, applying them to different vintages and different sample spans of data on real GDP and its major components from the U.S. national accounts and making comparisons with results from the previous studies.

Suggested Citation

  • Chen Baoline & McElroy Tucker S. & Pang Osbert C., 2022. "Assessing Residual Seasonality in the U.S. National Income and Product Accounts Aggregates," Journal of Official Statistics, Sciendo, vol. 38(2), pages 399-428, June.
    • Handle: RePEc:vrs:offsta:v:38:y:2022:i:2:p:399-428:n:11
    DOI: 10.2478/jos-2022-0020
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/jos-2022-0020
    Download Restriction: no
    File URL: https://libkey.io/10.2478/jos-2022-0020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    More about this item

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:offsta:v:38:y:2022:i:2:p:399-428:n:11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.