IDEAS home Printed from https://ideas.repec.org/a/spr/chinre/v13y2020i1d10.1007_s12187-019-09715-6.html
   My bibliography  Save this article

Dependence Analysis Between Childhood Social Indicators and Human Development Index Through Canonical Correlation Analysis

Author

Listed:
  • Raquel Lourenço Carvalhal Monteiro

    (Universidade Federal Fluminense)

  • Valdecy Pereira

    (Universidade Federal Fluminense)

  • Helder Gomes Costa

    (Universidade Federal Fluminense)

Abstract

This paper presents a dependence analysis between childhood social indicators (selected from the UNICEF and World Development Indicators) and the Human Development Index (HDI). This analysis, made through a canonical correlation, aimed to measure the relationship between child well-being and the modern standards of sustainable social development. First we have selected variables related to basic needs for children until primary school from the UNICEF database, and to mitigate missing values problem, for each country we have taken the average value per year, and, if missing values problem persists, a proper statistical imputation technique was applied. Then, with all variables having complete cases, the canonical correlation analysis generated a canonical space divided into four quadrants in order to verify the relations between variables and countries. We have found two significant characteristic roots with canonical correlation values of 0.91 and 0.56, each characteristic root was, respectively, labeled as “Health & Primary Schooling” (showing an inverse correlation between neonatal mortality rate and health and primary schooling) and “Primary Education” showing a positive correlation between primary education enrollments and primary education completion. Our approach indicates that the selected child well-being indicators not only are correlated to the HDI, but they also complement this development measure considering child well-being indicators, because considering the health and education variables it could be identified countries from a superior HDI class that are more similar with countries from an inferior HDI class and countries from an inferior HDI class that are more similar with countries from a superior class. Although the selected variables represent the underlying conditions for a child to grow up with dignity, according to United Nations’ Sustainable Development Goals, the data availability for variables with low occurrences of missing cases was scarce, preventing the use of all available variables from the UNICEF database. We have divided the canonical space into four quadrants, each one with dominant characteristics from a specific HDI class. Then, the presented 182 countries were plotted against this space in order to relate the childhood well-being indicator with the HDI classes.

Suggested Citation

  • Raquel Lourenço Carvalhal Monteiro & Valdecy Pereira & Helder Gomes Costa, 2020. "Dependence Analysis Between Childhood Social Indicators and Human Development Index Through Canonical Correlation Analysis," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 13(1), pages 337-362, February.
  • Handle: RePEc:spr:chinre:v:13:y:2020:i:1:d:10.1007_s12187-019-09715-6
    DOI: 10.1007/s12187-019-09715-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12187-019-09715-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12187-019-09715-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pınar Uyan-Semerci & Emre Erdoğan, 2017. "Child Well-Being Indicators Through the Eyes of Children in Turkey: A Happy Child Would be One Who…," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 10(1), pages 267-295, March.
    2. Liliana Fernandes & Américo Mendes & Aurora Teixeira, 2013. "A Weighted Multidimensional Index of Child Well-Being Which Incorporates Children’s Individual Perceptions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(3), pages 803-829, December.
    3. Mortaza Jamshidian & Siavash Jalal, 2010. "Tests of Homoscedasticity, Normality, and Missing Completely at Random for Incomplete Multivariate Data," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 649-674, December.
    4. Päivi Marjanen & Abigail Ornellas & Laura Mäntynen, 2017. "Determining Holistic Child Well-being: Critical Reflections on Theory and Dominant Models," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 10(3), pages 633-647, September.
    5. Jamshidian, Mortaza & Jalal, Siavash & Jansen, Camden, 2014. "MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR)," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(i06).
    6. Kenneth Land & Vicki Lamb & Sarah Meadows & Ashley Taylor, 2007. "Measuring trends in child well-being: an evidence-based approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 80(1), pages 105-132, January.
    7. Keren Dalyot & Sagi Dalyot, 2018. "Towards the Use of Crowdsourced GIS Data to Georeference Child Well-Being Globally," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(1), pages 185-204, August.
    8. Kyle D. Buck & J. Kevin Summers & Lisa M. Smith & Linda C. Harwell, 2018. "Application of the Human Well-Being Index to Sensitive Population Divisions: a Children’s Well-Being Index Development," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(4), pages 1249-1280, August.
    9. Raquel Lourenço Carvalhal Monteiro & Valdecy Pereira & Helder Gomes Costa, 2019. "Analysis of the Better Life Index Trough a Cluster Algorithm," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(2), pages 477-506, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chassan, Malika & Concordet, Didier, 2023. "How to test the missing data mechanism in a hidden Markov model," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    2. Fernandes, Liliana & Mendes, Américo & Teixeira, Aurora, 2013. "Assessing child well-being through a new multidimensional child-based weighting scheme index: An empirical estimation for Portugal," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 45(C), pages 155-174.
    3. Ke-Hai Yuan & Mortaza Jamshidian & Yutaka Kano, 2018. "Missing Data Mechanisms and Homogeneity of Means and Variances–Covariances," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 425-442, June.
    4. Nathaniel W. Anderson & Anna J. Markowitz & Daniel Eisenberg & Neal Halfon & Kristin Anderson Moore & Frederick J. Zimmerman, 2022. "The Child and Adolescent Thriving Index 1.0: Developing a Measure of the Outcome Indicators of Well-Being for Population Health Assessment," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 15(6), pages 2015-2042, December.
    5. Cho, Esther Yin-Nei & Yu, Fuk-Yuen, 2020. "A review of measurement tools for child wellbeing," Children and Youth Services Review, Elsevier, vol. 119(C).
    6. Frahm, Gabriel & Nordhausen, Klaus & Oja, Hannu, 2020. "M-estimation with incomplete and dependent multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
    7. Forthmann, Boris & Jendryczko, David & Scharfen, Jana & Kleinkorres, Ruben & Benedek, Mathias & Holling, Heinz, 2019. "Creative ideation, broad retrieval ability, and processing speed: A confirmatory study of nested cognitive abilities," Intelligence, Elsevier, vol. 75(C), pages 59-72.
    8. Samy Katumba & Julia Kadt & Mark Orkin & Paul Fatti, 2022. "Construction of a Reflective Quality of Life Index for Gauteng Province in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(1), pages 373-408, November.
    9. Khadija Loudghiri & Abdesselam Fazouane & Nouzha Zaoujal, 2021. "The Well-Being of Children in Morocco: What Barriers?," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(6), pages 2285-2324, December.
    10. Dat Vu Hoang & Laure Pasquier-Doumer, 2016. "Weighting deprivations using subjective well-being: An application to the Multidimensional Child Poverty Index in Vietnam," Working Papers hal-01293233, HAL.
    11. Jun Li & Yao Yu, 2015. "A Nonparametric Test of Missing Completely at Random for Incomplete Multivariate Data," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 707-726, September.
    12. Miroslav Verbič & Nela Kačmarčik-Maduna, 2018. "Child Well-being in Transition Countries as an Intergenerational Investment in the Development of Human Capital," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(4), pages 1077-1105, August.
    13. Bruno Martorano & Luisa Natali & Chris Neubourg & Jonathan Bradshaw, 2014. "Child Well-Being in Advanced Economies in the Late 2000s," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(1), pages 247-283, August.
    14. Mònica González-Carrasco & Ferran Casas & Asher Ben-Arieh & Shazly Savahl & Habib Tiliouine, 2019. "Children’s Perspectives and Evaluations of Safety in Diverse Settings and Their Subjective Well-Being: A Multi-National Approach," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 14(2), pages 309-334, April.
    15. Berasategi Sancho, Naiara & Idoiaga Mondragon, Nahia & Dosil Santamaria, Maria & Eiguren Munitis, Amaia, 2021. "The Well-being of children in lock-down: Physical, emotional, social and academic impact," Children and Youth Services Review, Elsevier, vol. 127(C).
    16. Conti, Gabriella & Heckman, James J., 2012. "The Economics of Child Well-Being," IZA Discussion Papers 6930, Institute of Labor Economics (IZA).
    17. Peter Burton & Shelley Phipps, 2010. "From a Young Teen‟s Perspective: Income and the Happiness of Canadian 12 to 15 Year-Olds," Working Papers daleconwp2010-10, Dalhousie University, Department of Economics.
    18. Xu Jiang & Hanita Kosher & Asher Ben-Arieh & E. Huebner, 2014. "Children’s Rights, School Psychology, and Well-Being Assessments," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 117(1), pages 179-193, May.
    19. Misikhina, Svetlana, "undated". "Impact of Social Policy on the Welfare of Children in OECD Countries and Russia," Published Papers nvg138, Russian Presidential Academy of National Economy and Public Administration.
    20. Wei Liu & Zhiwei Zhang & Lei Nie & Guoxing Soon, 2017. "A Case Study in Personalized Medicine: Rilpivirine Versus Efavirenz for Treatment-Naive HIV Patients," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1381-1392, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:chinre:v:13:y:2020:i:1:d:10.1007_s12187-019-09715-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.