IDEAS home Printed from https://ideas.repec.org/p/bbk/bbkefp/1602.html
   My bibliography  Save this paper

Factor models in panels with cross-sectional dependence: an application to the extended SIPRI military expenditure data

Author

Listed:
  • Ron Smith

    (Department of Economics, Mathematics & Statistics, Birkbeck)

  • Elisa Cavatorta

    (King’s College London)

Abstract

Strategic interactions between countries, such as arms races, alliances and wider economic and political shocks, can induce strong cross-sectional dependence in models of military expenditures using panel data. If the assumption of cross-sectional independence fails, standard panel estimators such as fixed or random effects can lead to misleading inference. This paper shows how to improve estimation of dynamic, heterogenous, panel models of the demand for military expenditure allowing for cross-sectional dependence in errors using two approaches: Principal Components and Common Correlated Effect estimators. Our results show that it is crucial to allow for cross-section dependence and there are large gains in it by allowing for both dynamics and between country heterogeneity in demand models of military expenditures. Our estimates show that mean group estimation of error correction models using the Common Correlated Effect approach provides an effective modelling framework.

Suggested Citation

  • Ron Smith & Elisa Cavatorta, 2016. "Factor models in panels with cross-sectional dependence: an application to the extended SIPRI military expenditure data," Birkbeck Working Papers in Economics and Finance 1602, Birkbeck, Department of Economics, Mathematics & Statistics.
  • Handle: RePEc:bbk:bbkefp:1602
    as

    Download full text from publisher

    File URL: http://www.bbk.ac.uk/ems/research/wp/2016/PDFs/BWPEF1602.pdf
    File Function: First version, 2016
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    2. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    3. Elisa Cavatorta, 2010. "Unobserved Common Factors In Military Expenditure Interactions Across Mena Countries," Defence and Peace Economics, Taylor & Francis Journals, vol. 21(4), pages 301-316.
    4. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    5. J. Paul Dunne & Sam Perlo-Freeman & Ron Smith, 2008. "The Demand For Military Expenditure In Developing Countries: Hostility Versus Capability," Defence and Peace Economics, Taylor & Francis Journals, vol. 19(4), pages 293-302.
    6. Pesaran, M. Hashem, 2004. "General Diagnostic Tests for Cross Section Dependence in Panels," IZA Discussion Papers 1240, Institute for the Study of Labor (IZA).
    7. Brauner Jennifer, 2012. "Military Spending and Democratisation," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 18(3), pages 1-16, December.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Military expenditure; Panel data; Factor models.;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • H56 - Public Economics - - National Government Expenditures and Related Policies - - - National Security and War

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bbk:bbkefp:1602. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://www.ems.bbk.ac.uk/ .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.