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The Dynamics and Determinants of Bullying Victimisation

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  • Chrysanthou, Georgios Marios

    (University of Sheffield)

  • Vasilakis, Chrysovalantis

    (Bangor University)

Abstract

We study the determinants and longitudinal evolution of nine types of adolescent (verbal, physical, indirect) bullying at school and domestically using the Understanding Society dataset during 2009-13. Family support is the most prominent protective factor against bullying. Applying joint maximum likelihood estimation (MLE) for dynamic discrete responses, we investigate potential simultaneous determination of bullying and family support. The estimates indicate that bullying disclosure might be uncommon. The probability of escaping/suffering victimisation is inversely/positively related to previous bullying intensity, respectively. Family income increases domestic indirect aggression but, reduces direct aggression and non-domestic bullying as does living in a high income region.

Suggested Citation

  • Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2018. "The Dynamics and Determinants of Bullying Victimisation," IZA Discussion Papers 11902, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp11902
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    1. Rabe-Hesketh, Sophia & Skrondal, Anders, 2013. "Avoiding biased versions of Wooldridge’s simple solution to the initial conditions problem," Economics Letters, Elsevier, vol. 120(2), pages 346-349.
    2. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    3. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2018. "The Dynamics and Determinants of Bullying Victimisation," IZA Discussion Papers 11902, Institute of Labor Economics (IZA).
    4. Robert Kaestner & Kevin Callison, 2011. "Adolescent Cognitive and Noncognitive Correlates of Adult Health," Journal of Human Capital, University of Chicago Press, vol. 5(1), pages 29-69.
    5. Andrew M. Jones & Nigel Rice & Paul Contoyannis, 2012. "The Dynamics of Health," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 2, Edward Elgar Publishing.
    6. Das, Marcel & van Soest, Arthur, 1999. "A panel data model for subjective information on household income growth," Journal of Economic Behavior & Organization, Elsevier, vol. 40(4), pages 409-426, December.
    7. Alfonso Miranda & Sophia Rabe-Hesketh, 2006. "Maximum likelihood estimation of endogenous switching and sample selection models for binary, ordinal, and count variables," Stata Journal, StataCorp LP, vol. 6(3), pages 285-308, September.
    8. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers 31/17, Institute for Fiscal Studies.
    9. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
    10. James J. Heckman, 2012. "The developmental origins of health," Health Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 24-29, January.
    11. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    12. Doidge, James C & Higgins, Daryl J & Delfabbro, Paul & Edwards, Ben & Vassallo, Suzanne & Toumbourou, John W & Segal, Leonie, 2017. "Economic predictors of child maltreatment in an Australian population-based birth cohort," Children and Youth Services Review, Elsevier, vol. 72(C), pages 14-25.
    13. Wiji Arulampalam & Mark B. Stewart, 2009. "Simplified Implementation of the Heckman Estimator of the Dynamic Probit Model and a Comparison with Alternative Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 659-681, October.
    14. Brown, Sarah & Taylor, Karl, 2008. "Bullying, education and earnings: Evidence from the National Child Development Study," Economics of Education Review, Elsevier, vol. 27(4), pages 387-401, August.
    15. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    16. Gerard J. Berg & Petter Lundborg & Paul Nystedt & Dan-Olof Rooth, 2014. "Critical Periods During Childhood And Adolescence," Journal of the European Economic Association, European Economic Association, vol. 12(6), pages 1521-1557, December.
    17. Chris Muris, 2017. "Estimation in the Fixed-Effects Ordered Logit Model," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 465-477, July.
    18. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2019. "The Impact of Bullying Victimisation on Mental Wellbeing," QM&ET Working Papers 19-1, University of Alicante, D. Quantitative Methods and Economic Theory.
    19. Ada Ferrer-i-Carbonell & Paul Frijters, 2004. "How Important is Methodology for the estimates of the determinants of Happiness?," Economic Journal, Royal Economic Society, vol. 114(497), pages 641-659, July.
    20. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
    21. Wooldridge, Jeffrey M., 2014. "Quasi-maximum likelihood estimation and testing for nonlinear models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 182(1), pages 226-234.
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    1. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2018. "The Dynamics and Determinants of Bullying Victimisation," IZA Discussion Papers 11902, Institute of Labor Economics (IZA).
    2. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2020. "Protecting the mental health of future adults: Disentangling the determinants of adolescent bullying victimisation," Social Science & Medicine, Elsevier, vol. 253(C).
    3. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2019. "The Impact of Bullying Victimisation on Mental Wellbeing," QM&ET Working Papers 19-1, University of Alicante, D. Quantitative Methods and Economic Theory.
    4. Emma Gorman & Colm Harmon & Silvia Mendolia & Anita Staneva & Ian Walker, 2021. "Adolescent School Bullying Victimization and Later Life Outcomes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 1048-1076, August.
    5. Chrysanthou, Georgios Marios & Vasilakis, Chrysovalantis, 2018. "The Dynamics and Determinants of Bullying Victimisation," IZA Discussion Papers 11902, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    bullying; dynamic discrete response; simultaneity; unobserved heterogeneity;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • J12 - Labor and Demographic Economics - - Demographic Economics - - - Marriage; Marital Dissolution; Family Structure
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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