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Regression analysis of country effects using multilevel data: a cautionary tale

  • Bryan, Mark L.
  • Jenkins, Stephen P.

Cross-national differences in outcomes are often analysed using regression analysis of multilevel country datasets, examples of which include the ECHP, ESS, EU-SILC, EVS, ISSP, and SHARE. We review the regression methods applicable to this data structure, pointing out problems with the assessment of country-level factors that appear not to be widely appreciated, and illustrate our arguments using Monte-Carlo simulations and analysis of women’s employment probabilities and work hours using EU SILC data. With large sample sizes of individuals within each country but a small number of countries, analysts can reliably estimate individual-level effects within each country but estimates of parameters summarising country effects are likely to be unreliable. Multilevel (hierarchical) modelling methods are commonly used in this context but they are no panacea.

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File URL: https://www.iser.essex.ac.uk/research/publications/working-papers/iser/2013-14.pdf
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Paper provided by Institute for Social and Economic Research in its series ISER Working Paper Series with number 2013-14.

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Date of creation: 19 Aug 2013
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Publication status: published
Handle: RePEc:ese:iserwp:2013-14
Contact details of provider: Postal: Publications Office, Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ UK
Phone: 44-1206-872957
Fax: 44-1206-873151
Web page: https://www.iser.essex.ac.uk/
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Order Information: Postal: Publications Office, Institute for Social and Economic Research, University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ UK
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  9. James R. Carpenter & Harvey Goldstein & Jon Rasbash, 2003. "A novel bootstrap procedure for assessing the relationship between class size and achievement," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(4), pages 431-443.
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