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Investigating the Dimensions of Youth Wellbeing: An Exploratory Structural Equation Modelling Approach Applied to Palestine

Abstract

This paper illustrates the “Sen-Nussbaum-type” capability approach to the measurement of youth wellbeing using the newly developed Exploratory Structural Equation Modelling (ESEM). It offers insights into how the capability to achieve wellbeing can be measured in a conflict-affected and resource-constrained setting. The methodology is applied to nationally representative data taken from the Palestinian Family Survey. The population of interest is youth aged 15 to 29. Three capability dimensions are identified: health awareness, knowledge and living conditions. Results show an interrelation between capability dimensions. It is especially important to note the effect of knowledge capabilities on both health awareness and living conditions indicators. Results also confirm the importance of some (exogenous) factors such as the education of the household head in the conversion of capabilities into achievements. Capabilities are shown to be highest in the West Bank for both knowledge and living conditions compared to the Gaza Strip.

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Notes

  1. 1.

    A notable exception is the study of Krishnakumar and Ballon (2008).

References

  1. Abu-Zaineh, M., Mataria, A., Moatti, J.-P., & Ventelou, B. (2011). Measuring and decomposing socioeconomic inequality in healthcare delivery: a microsimulation approach with application to the palestinian conflict-affected fragile setting. Social Science & Medicine, 72, 133–141.

  2. Alkire, S. (2008). Choosing dimensions: the capability approach and multidimensional poverty. MPRA Paper 8862.

  3. Alkire, S. (2010). Using the capability approach: prospective and evaluative analyses. In F. Comim, M. Qizilbash, S. Alkire (Eds.), The capability approach: concepts, measures and applications (Ch. 1, pp 26-50). Cambridge: Cambridge University Press.

  4. Alkire, S. (2015). The capability approach and wellbeing measurement for public policy. OPHI Working Paper N° 94.

  5. Anand, P. (2005). Capabilities and health. Journal of Medical Ethics, 3, 299–303.

  6. Asparouhov, T. & Muthen, B. (2006). Robust Chi square difference testing with mean and variance adjusted test statistics. 26 May. Accessed 04 19, 2016. https://www.statmodel.com/download/webnotes/webnote10.pdf.

  7. Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16, 397–438.

  8. Ballon, P. (2013). The selection of functionings and capabilities: a survey of empirical studies. Working Papers PMMA 2013–09.

  9. Batniji, R., Rabaia, Y., Nguyen-Cillham, V., Giacaman, R., Sarraj, E., Punamaki, R.-L., Saab, H., & Boyce, W. (2009). Health as human security in the occupied Palestinian territory. The Lancet, 373(9669), 113–1143.

  10. Becker, G. S. (1964). Human capital: a theoretical and empirical analysis, with special reference to education. New York: Columbia University Press.

  11. Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.

  12. Bhattacharya, J., & Banerjee, S. (2012). Women empowerment as multidimensional capability enhancement: an application of structural-equation-modelling. Occassional Paper: Institute of Development Studies Kolkota.

  13. Biggeri, M., & Mehrota, S. (2011). Child poverty as capability deprivation: How to choose domains of child wellbeing and poverty. In M. Biggeri, J. Ballet, & F. Comim (Eds.), Children and the capability approach (pp. 46–75). Hampshire: Palgrave Macmillan.

  14. Bleichrodt, H., & Quiggin, J. (2013). Capabilities as menus: a Non-welfarist basis for QALY evaluation. Journal of Health Economics, 32, 128–137.

  15. Bollen, K. A. (2002). Latent variables in psychology and the social sciences. Annual Review of Psychology, 53, 605–634.

  16. Browne, M. W. (2001). An overview of analytic rotation in exploratory factor analysis. Multivariate Behavioral Research, 36, 111–150.

  17. Bulmer, E. R. (2003). The impact of Israeli border policy on the palestinian labor market. Economic Development and Cultural Change, 51(3), 657–676.

  18. Chopra, K., & Duraiappah, A. K. (2008). Operationalizing Capabilities in a Segmented Society: The Role of Insittutions. In F. Comim, M. Qizilbash, S. Alkire (Eds.), The capability approach: concepts, measures and applications (pp. 362–382). Cambridge: Cambridge University Press.

  19. Coast, J., Smith, R., & Lorgelly, P. (2008). Should the capability approach be applied in health economics? Health Economics, 17, 667–670.

  20. Cronbach, L. J. (1951). Coefficient alpha and teh internal structure of tests. Psychometrika, 16(3), 297–334.

  21. Fleurbaey, M. (2005). Health, wealth, and fairness. Journal of Public Economic Theory, Association for Public Economic Theory, 7(2), 253–284.

  22. Giacaman, R., Khatib, R., Shabaneh, L., Ramlawi, A., Sabri, B., Sabatinelli, G., Khawaja, M., & Laurance, T. (2009). Health status and health services in the occupied palestinian territory. The Lancet, 373(9666), 837–849.

  23. Glomm, G., & Ravikumar, B. (1992). Public versus private investment in human capital: engodenous growth and income inequality. Journal of Political Economy, 100, 818–834.

  24. Goldin, N., Patel, P. & Perry, P. (2014). The global youth wellbeing index. Washington DC: The Center for Strategic and International Studies and International Youth Foundation.

  25. Goldmand, R. D. (2013). Caffeinated energy drinks in children. Canadian Family Physician, 59(9), 947–948.

  26. Jöreskog, K. G. (2002). Structural equations modeling with ordial variables using LISREL. http://www.ssicentral.com/lisrel/techdocs/ordinal.pdf. Accessed 2014

  27. Krishnakumar, J. (2007). Going beyond functionings to capabilities: an econometric model to explain and estimate capabilities. Journal of Human Development, 8(1), 39–63.

  28. Krishnakumar, J. & Ballon P. (2008). Estimating basic capabilities: a structural equation model applied to Bolivia. World Development, 36(6), 992–1010.

  29. Kuder, G. F., & Richardson, M. W. (1937). The theory of the estimation of test reliability. Psychometrika, 2(3), 151–160.

  30. Kuklys, W. & Robeyns I. (2004). Sen’s capability approach to welfare economics. Cambridge Working Papers in Economics 0415, Cambridge University.

  31. Lelli, S. (2008). Operationalising Sen’s capability approach: the influence of the selected technique. In F. Comim, M. Qizilbash, S. Alkire (Eds.), The capability approach: concepts, measures and applications (Ch.10: pp 310–361). Cambridge: Cambridge University Press.

  32. Marsh, H. W., & Nagengast, B. (2013). Measurement invariance of Big-five factors overthe life span: ESEM tests of gender, age, plasticity, maturity, and La dolce vita effects. Developmental Psychology, 49(6), 1194–1218.

  33. Marsh, H. W., Muthén, B., Asparouhov, T., Lüdtke, O., Robitzisch, A., Alexandre, J. S., & Trautwein, U. (2009). Exploratory structural equation modeling, integrating CFA and EFA: application to Students’ evaluations of university teaching. Structural Equation Modeling, 16, 439–476.

  34. Marsh, H. W., Lüdtke, O., Muthén, B. O., Asparouhov, T., Morin, A. J. S., & Trautwein, U. (2010). A New look at the Big five factor structure through explanatory structural equation modeling. Psychological Assessment, 22, 471–491.

  35. Marsh, H. W., Vallerand, R. J., Lafrenière, M.-A. K., Parker, P., Morin, A. J. S., Carbonneau, N., Jowett, S., Bureau, J. S., Fernet, C., & Guay, F. (2013). Passion: does one scale fit all? construct validity of two-factor passion scale and psychometric invariance over different activities and languages. Psychological Assessment, 25(3), 796–809.

  36. Marsh, H. W., Morin, A. J. S., Parker, P. D., & Kaur, G. (2014). Exploratory structural equation modeling: an integration of the best features of exploratory and confirmatory factor analysis. Annual Review of Clinical Psychology, 10, 85–110.

  37. Mataria, A., Giancaman, R., Stefanini, A., Naidoo, N., Kowal, P., & Chatterji, S. (2009). The quality of life of palestinians living in chronic conflict: assessment and determinants. European Journal of Health Economics, 10, 93–101.

  38. Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus User’s Guide. Seventh Edition. Los Angeles, CA: Muthén & Muthén.

  39. Nussbaum, M. (1988). Nature, function and capability: aristotle on political distribution. Oxford studies in ancient philosophy, 6(Supplementary Volume), 145–184.

  40. Nussbaum, M. C. (1999). Sex and social justice. 1e. New York: Oxford University Press.

  41. Nussbaum, M. C. (2000). Women and human development: the capabilities approach. Cambridge: Cambridge University Press.

  42. Nussbaum, M. C. (2003). Capabilities as fundamental entitlements: Sen and social justice. Feminist Economics, 9, 33–59.

  43. Palestinian Central Bureau of Statistics. (2013). Final Report of the Palestinian Family Survey 2010. Ramallah: State of Palestine.

  44. Paulik, E., Ferenc, B., Aranka, K., Sándor, B., & László, N. (2010). Determinants of health-promoting lifestyle behaviour in the rural areas of hungary. Health Promotion International, 25(3), 277–288. doi:10.1093/heapro/daq025.

  45. Robeyns, I. (2003). Sen’s capability approach and gender inequality: selecting relevant capabilities. Feminist Economics, 9(2–3), 61–92.

  46. Robeyns, I. (2005). The capability approach: a theoretical survey. Journal of Human Development, 6(1), 93–117.

  47. Schultz, T. W. (1960). Capital formation by education. Journal of Political Economy, 68(6), 571–583.

  48. Sen, A. (1980). Equality of what? In S. McMurrin (ed.), Tanner Lectures on Human Values, (196–220). Cambridge: Cambridge University Press.

  49. Sen, A. (1985). Commodities and capabilities. Amsterdam: North Holland.

  50. Sen, A. (1992). Inequality re-examined. Oxford: Russell Sage Foundation, New York and Clarendon Press.

  51. Sen, A. (1999). Development as freedom. Oxford: Oxford India paperbacks, Oxford Universtiy Press.

  52. Sen, A. (2004). Capabilities, lists, and public reason. Feminist Economics, 10(3), 77–80.

  53. Siefert, S. M., Schaechter, J, L., Hershorin, E. R. & Lipshultz, S. E. (2011). Health effects of energy drinks on children, adolescents, and young adults. Peadiatrics, 127(3), 511-528.

  54. Strauss, M. E., & Smith, G. T. (2009). Construct validity: advances in theory and methodology. Annual Review of Clinical Psychology, 5, 1–25.

  55. Temple, J., & Johnson, P. A. (1998). Social capability and economic growth. The Quarterly Journal of Economics, 113(3), 965–990.

  56. Tommaso, M. L. D. (2007). Children capabilities: a structural equation model for india. The Journal of Socio-Economics, 36, 436–450.

  57. Tucker, L., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10.

  58. UN. 2016. Sustainable development goals. Avril 13. https://sustainabledevelopment.un.org/?menu=1300.

  59. UNDP. (1990–2013). Human Development Report. Oxford: Oxford University Press.

  60. Wagle, U. (2005). Multidimensional poverty measuremeny with economic wellbeing, capability, and social inclusion: a case from Kathmandu, Nepal. Journal of Human Development, 6(3), 301–328.

  61. WHO. (2016). 100 Core Health Indicators. 04 18. http://www.who.int/healthinfo/indicators/2015/100CoreHealthIndicators_2015_infographic.pdf?ua=1.

  62. Wirth, R. J., & Edwards, M. C. (2007). Item factor analysis: current approaches and future directions. Psychological Methods, 12(1), 58–79.

  63. Woode, M. E. & Abu-Zaineh, M. (2015). A cross-country analysis of gender disparities in early childhood deprivation. AHEAD Working Paper Series N° 01/2015.

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Author information

Correspondence to Maame Esi Woode.

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Funding

This work has been carried out thanks to the support of the A*MIDEX project (no. ANR-11-IDEX-0001-02) funded by the “Investissements d’Avenir” French Government program, managed by the French National Research Agency (ANR).

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Fig. S1

(DOCX 115 kb)

Fig. S2

(DOCX 76 kb)

Table S1

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Table S2

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Appendices

Appendix 1

Fig. 1
figure1

ESEM in MIMIC model

Table 6 Item correlation
Table 7 Factor loadings with correlations

Appendix 2: Generalised ESEM

Following Asparouhov and Muthén (2009), assume there exists p dependent underlying unobserved variables, Y*, one for each categorical variable, Y and q independent variables X with m latent variables η. In addition, assume that there exists a set of parameters, τ, for each categorical variable such that Y = k if τ k  < Y* < τ k + 1. Then the generalised ESEM (GESEM) model is specified using the following two equations,

$$ \boldsymbol{Y}=\boldsymbol{\nu} +\boldsymbol{\varLambda} \boldsymbol{\eta} +\mathbf{K}\mathbf{X}+\varepsilon $$
(1)
$$ \boldsymbol{\eta} =\alpha +\mathbf{B}\boldsymbol{\eta } +\varGamma \mathbf{X}+\zeta $$
(2)

Equation (1) represents the measurement part – also referred to as the Qualitative Response Model (QRM). The QRM specifies how the latent variables are related to the observed responses. ν is the vector of intercepts. Equation (2) represents the latent variable model or the structural simultaneous equation model (SEM), with Γ and B being the respective coefficient matrices and α a vector if intercepts. The latent variables, η, are made up of both explanatory factors and item factors (confirmatory). The respective error terms of the SEM and QRM vectors (ε and ζ) are assumed to be (i) with zero expectations, (ii) uncorrelated with each other (ζ uncorrelated with ε), but (iii) correlated within each. Formally,

$$ \boldsymbol{E}\left({\boldsymbol{\varepsilon}}_{\boldsymbol{i}}\right)=0,\ \boldsymbol{E}\left({\boldsymbol{\zeta}}_{\boldsymbol{i}}\right)=0;\ \boldsymbol{V}\left({\boldsymbol{\varepsilon}}_{\boldsymbol{i}}\right)=\boldsymbol{E}\left({\boldsymbol{\varepsilon}}_{\boldsymbol{i}},\ {\overset{\prime }{\boldsymbol{\varepsilon}}}_{\boldsymbol{i}}\right)=\boldsymbol{\varPhi};\ \boldsymbol{V}\left({\boldsymbol{\zeta}}_{\boldsymbol{i}}\right)=\boldsymbol{E}\left({\boldsymbol{\zeta}}_{\boldsymbol{i}},\ \overset{^{\prime }}{{\boldsymbol{\zeta}}_{\boldsymbol{i}}}\right)=\boldsymbol{\varPsi} $$
(5)

where Ф and Ψ are the covariance matrices for the residuals in the QRM and the SEM equations, respectively; Ψ is assumed to be diagonal and Λ non-singular. Please see Figure S1 for a graphical representation of the GESEM model.

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Abu-Zaineh, M., Woode, M.E. Investigating the Dimensions of Youth Wellbeing: An Exploratory Structural Equation Modelling Approach Applied to Palestine. Child Ind Res 11, 57–78 (2018). https://doi.org/10.1007/s12187-016-9420-0

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Keywords

  • Capability approach
  • Exploratory structural equation model
  • Health awareness
  • Knowledge
  • Wealth
  • Wellbeing
  • Developing countries
  • The occupied Palestinian territories

JEL Classifications

  • I31
  • I32
  • C35
  • C38
  • 053