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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
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    File URL: https://eprints.bbk.ac.uk/id/eprint/15262
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    References listed on IDEAS

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    1. Coakley, Jerry & Fuertes, Ana-Maria & Smith, Ron, 2006. "Unobserved heterogeneity in panel time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2361-2380, May.
    2. 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.
    3. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    4. Chudik, Alexander & Pesaran, M. Hashem, 2011. "Infinite-dimensional VARs and factor models," Journal of Econometrics, Elsevier, vol. 163(1), pages 4-22, July.
    5. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.
    6. Brauner Jennifer, 2012. "Military Spending and Democratisation," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 18(3), pages 1-16, December.
    7. Pesaran, M. Hashem & Smith, Ron P., 2014. "Signs of impact effects in time series regression models," Economics Letters, Elsevier, vol. 122(2), pages 150-153.
    8. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    9. Alexander Chudik & M. Hashem Pesaran, 2013. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 592-649, August.
    10. Jennifer Brauner, 2015. "Military spending and democracy," Defence and Peace Economics, Taylor & Francis Journals, vol. 26(4), pages 409-423, August.
    11. Paul Collier & Anke Hoeffler, 2007. "Unintended Consequences: Does Aid Promote Arms Races?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(1), pages 1-27, February.
    12. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    13. Pesaran, M. Hashem, 2015. "Time Series and Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780198759980.
    14. 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.
    15. 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.
    16. 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.
    17. Dunne, J. Paul & Smith, Ron P., 2007. "The Econometrics of Military Arms Races," Handbook of Defense Economics, in: Keith Hartley & Todd Sandler (ed.), Handbook of Defense Economics, edition 1, volume 2, chapter 28, pages 913-940, Elsevier.
    18. Smith, Ron, 1995. "The demand for military expenditure," Handbook of Defense Economics, in: Keith Hartley & Todd Sandler (ed.), Handbook of Defense Economics, edition 1, volume 1, chapter 4, pages 69-87, Elsevier.
    19. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    20. repec:hal:journl:peer-00796743 is not listed on IDEAS
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Langlotz, Sarah & Potrafke, Niklas, 2019. "Does development aid increase military expenditure?," Journal of Comparative Economics, Elsevier, vol. 47(3), pages 735-757.
    6. Krieger, Tim & Meierrieks, Daniel, 2020. "Population size and the size of government," European Journal of Political Economy, Elsevier, vol. 61(C).
    7. 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.
    8. Dmitry Alexandrovich REPNIKOV, 2024. "Defense Expenditures and GDP Growth Rates in the World: Determinants and Interrelationships," Russian Foreign Economic Journal, Russian Foreign Trade Academy Ministry of economic development of the Russian Federation, issue 5, pages 48-58, May.
    9. 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.
    10. Herzer, Dierk, 2020. "How does mortality affect innovative activity in the long run?," World Development, Elsevier, vol. 125(C).
    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

    Keywords

    Military expenditure; Panel data; Factor models.;
    All these keywords.

    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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