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Factor Models in Panels with Cross-sectional Dependence: An Application to the Extended SIPRI Military Expenditure Data

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  • Elisa Cavatorta
  • Ron P. Smith

Abstract

Strategic interactions between countries, such as arms races, alliances and wider economic and political shocks, can induce strong cross-sectional dependence in panel data models of military expenditure. 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-sectional dependence, that the bulk of the effect is regional and there are large gains in fit by allowing for both dynamics and between country heterogeneity in models of the demand for military expenditures.

Suggested Citation

  • Elisa Cavatorta & Ron P. Smith, 2017. "Factor Models in Panels with Cross-sectional Dependence: An Application to the Extended SIPRI Military Expenditure Data," Defence and Peace Economics, Taylor & Francis Journals, vol. 28(4), pages 437-456, July.
    • Handle: RePEc:taf:defpea:v:28:y:2017:i:4:p:437-456
    DOI: 10.1080/10242694.2016.1261428
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    Cited by:

    1. J. Paul Dunne & Nan Tian, 2019. "Military Expenditures and Economic Growth," School of Economics Macroeconomic Discussion Paper Series 2019-05, School of Economics, University of Cape Town.
    2. J. Paul Dunne & Ron P. Smith, 2020. "Military Expenditure, Investment and Growth," Defence and Peace Economics, Taylor & Francis Journals, vol. 31(6), pages 601-614, August.
    3. Langlotz, Sarah & Potrafke, Niklas, 2019. "Does development aid increase military expenditure?," Journal of Comparative Economics, Elsevier, vol. 47(3), pages 735-757.
    4. Krieger, Tim & Meierrieks, Daniel, 2020. "Population size and the size of government," European Journal of Political Economy, Elsevier, vol. 61(C).
    5. Kyriakos Emmanouilidis & Christos Karpetis, 2022. "Cross–Country Dependence, Heterogeneity and the Growth Effects of Military Spending," Defence and Peace Economics, Taylor & Francis Journals, vol. 33(7), pages 842-856, October.
    6. repec:awi:wpaper:0618 is not listed on IDEAS
    7. Herzer, Dierk, 2020. "How does mortality affect innovative activity in the long run?," World Development, Elsevier, vol. 125(C).
    8. Dierk Herzer, 2019. "The long-run effect of aid on health: evidence from panel cointegration analysis," Applied Economics, Taylor & Francis Journals, vol. 51(12), pages 1319-1338, March.
    9. Christos Kollias & Suzanna Maria Paleologou & Panayiotis Tzeremes & Nickolaos Tzeremes, 2018. "The demand for military spending in Latin American countries," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 27(1), pages 1-17, December.
    10. Christos Kollias & Suzanna-Maria Paleologou, 2019. "Military spending, economic growth and investment: a disaggregated analysis by income group," Empirical Economics, Springer, vol. 56(3), pages 935-958, March.
    11. Abdul Rehman & Hengyun Ma & Rafael Alvarado & Fayyaz Ahmad, 2023. "The nexus of military, final consumption expenditures, total reserves, and economic development of Pakistan," Economic Change and Restructuring, Springer, vol. 56(3), pages 1753-1776, June.

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    More about this item

    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

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