IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v40y2019i4p573-589.html

Persistence Heterogeneity Testing in Panels with Interactive Fixed Effects

Author

Listed:
  • Yunus Emre Ergemen
  • Carlos Velasco

Abstract

We consider large N,T panel data models with fixed effects, a common factor allowing for cross‐section dependence, and persistent data and shocks, which are assumed fractionally integrated. In a basic setup, the main interest is on the fractional parameter of the idiosyncratic component, which is estimated in first differences after factor removal by projection on the cross‐section average. The pooled conditional‐sum‐of‐squares estimate is NT consistent but the normal asymptotic distribution might not be centred, requiring the time series dimension to grow faster than the cross‐section size for correction. We develop tests of homogeneity of dynamics, including the degree of integration, that have no trivial power under local departures from the null hypothesis of a non‐negligible fraction of cross‐section units. A simulation study shows that our estimates and tests have good performance even in moderately small panels.

Suggested Citation

  • Yunus Emre Ergemen & Carlos Velasco, 2019. "Persistence Heterogeneity Testing in Panels with Interactive Fixed Effects," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(4), pages 573-589, July.
  • Handle: RePEc:bla:jtsera:v:40:y:2019:i:4:p:573-589
    DOI: 10.1111/jtsa.12436
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/jtsa.12436
    Download Restriction: no

    File URL: https://libkey.io/10.1111/jtsa.12436?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

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:bla:jtsera:v:40:y:2019:i:4:p:573-589. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.