IDEAS home Printed from https://ideas.repec.org/a/taf/recsxx/v23y2020i1p329-348.html
   My bibliography  Save this article

Testing the hysteresis effect in the US state-level unemployment series

Author

Listed:
  • Tolga Omay
  • Burcu Ozcan
  • Muhammed Shahbaz

Abstract

This paper re-examines the stochastic time series behaviour of the monthly unemployment rate in 50 states of the United States (US) for the period 1976–2017 using a number of state-of-the-art unit root tests. The new developments incorporate structural break, nonlinearity, asymmetry, and cross-sectional correlation within panel-data estimation including the use of a sequential panel selection method. While not previously considered, sequential panel selection enabled us to determine and separate the stationary and nonstationary series in the sample. The empirical findings are in support of the stationarity of unemployment rate in 47 states. The findings confirm a natural rate hypothesis for the labour markets in the most US states, indicating that labour market shocks have solely temporary effects on state-level unemployment. This empirical study provides significant state-specific policy implications.

Suggested Citation

  • Tolga Omay & Burcu Ozcan & Muhammed Shahbaz, 2020. "Testing the hysteresis effect in the US state-level unemployment series," Journal of Applied Economics, Taylor & Francis Journals, vol. 23(1), pages 329-348, January.
    • Handle: RePEc:taf:recsxx:v:23:y:2020:i:1:p:329-348
    DOI: 10.1080/15140326.2020.1759865
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/15140326.2020.1759865
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/15140326.2020.1759865?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Furkan Emirmahmutoglu & Tolga Omay & Syed Jawad Hussain Shahzad & Safwan Mohd Nor, 2021. "Smooth Break Detection and De-Trending in Unit Root Testing," Mathematics, MDPI, vol. 9(4), pages 1-25, February.
    2. Iman Cheratian & Saleh Goltabar & Luis A. Gil-Alaña, 2023. "The unemployment hysteresis by territory, gender, and age groups in Iran," SN Business & Economics, Springer, vol. 3(2), pages 1-18, February.
    3. Kassouri, Yacouba, 2022. "Boom-bust cycles in oil consumption: The role of explosive bubbles and asymmetric adjustments," Energy Economics, Elsevier, vol. 111(C).

    More about this item

    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:taf:recsxx:v:23:y:2020:i:1:p:329-348. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/recs .

    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.