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To what extent fuzzy set theory and structural equation modelling can measure functionings? An application to child well being

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  • Tindara Addabbo
  • Maria Laura Di Tommaso
  • Gisella Facchinetti

Abstract

This paper explores the possibilities of using fuzzy inference system and structural equation modelling to measure capabilities both at a theoretical and empirical level. Fuzzy set theory has been already used to measure functionings (Chiappero Martinetti 1996, 2000, Lelli 2001) while structural equation modelling has not been used till now (apart from some preliminary results on children well being in India presented by Di Tommaso 2003). In this paper we outline the major advantages and disadvantages of both the approaches both in terms of the statistical assumptions implied and in terms of their ability to measure functionings. Are the statistical assumptions implied by these approaches compatible with the capability approach? What limitations the statistical assumptions impose to the capability approach? In order to assess to what extent these two statistical techniques work, we will apply them to measure child well being with a capabilities approach. The aim is also how to propose a list of capabilities with reference to children well being in Italy. The applied part of the paper will use a data set based on a ISTAT (Italian National Statistical Office) multipurpose survey on family and on children condition in Italy to recover information on children’s education, the sociodemographic structure of their families, child care provided by relatives and parents according to the type of activities in which the children are involved. In the conclusion of the paper, we outline if and to what extent these statistical and fuzzy techniques can be used to measure functionings with special reference to child well being.

Suggested Citation

  • Tindara Addabbo & Maria Laura Di Tommaso & Gisella Facchinetti, 2004. "To what extent fuzzy set theory and structural equation modelling can measure functionings? An application to child well being," CHILD Working Papers wp30_04, CHILD - Centre for Household, Income, Labour and Demographic economics - ITALY.
  • Handle: RePEc:wpc:wplist:wp30_04
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    1. Raiser, M. & Di Tommaso, M.L. & Weeks, M., 2000. "The Measurement and Determination of Institutional Change: Evidence from Transition Economics," Cambridge Working Papers in Economics 0029, Faculty of Economics, University of Cambridge.
    2. M. Raiser & Melvyn Weeks, 2000. "A Structural Model of Institutional Change: Evidence from Transition Economies," Econometric Society World Congress 2000 Contributed Papers 1689, Econometric Society.
    3. Carlo Alberto Magni & Giovanni Mastroleo & Marina Vignola & Gisella Facchinetti, 2009. "Strategic options and expert systems: a fruitful marriage," Proyecciones Financieras y Valoración 006122, Master Consultores.
    4. Michelle Lalla & Gisella Facchinetti & Giovanni Mastroleo, 2005. "Ordinal scales and fuzzy set systems to measure agreement: An application to the evaluation of teaching activity," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(5), pages 577-601, January.
    5. Aigner, Dennis J. & Hsiao, Cheng & Kapteyn, Arie & Wansbeek, Tom, 1984. "Latent variable models in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 23, pages 1321-1393, Elsevier.
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    Citations

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    Cited by:

    1. Tindara Addabbo & Gisella Facchinetti, 2013. "Fuzzy logic and the capability approach," Center for the Analysis of Public Policies (CAPP) 0106, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    2. Cracolici, M. Francesca & Nijkamp, Peter, 2005. "Attractiveness and Effectiveness of Competing Tourist Areas: A Study on Italian Provinces," Serie Research Memoranda 0009, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    3. Mónica Domínguez-Serrano & Lucía Moral Espín, 2018. "From Relevant Capabilities to Relevant Indicators: Defining an Indicator System for Children’s Well-Being in Spain," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(1), pages 1-25, February.
    4. Kirsten Wüst & Jürgen Volkert, 2012. "Childhood and Capability Deprivation in Germany: A Quantitative Analysis Using German Socio-Economic Panel Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 106(3), pages 439-469, May.
    5. Anna Maccagnan, 2011. "Measuring the interaction between parents and children in Italian families: a structural equation approach," Center for the Analysis of Public Policies (CAPP) 0084, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    6. Anna Maccagnan, 2011. "Measuring the interaction between parents and children in Italian families: a structural equation approach," Department of Economics 0645, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    7. Maria Laura Di Tommaso, 2006. "Measuring the well being of children using a capability approach An application to Indian data," CHILD Working Papers wp05_06, CHILD - Centre for Household, Income, Labour and Demographic economics - ITALY.
    8. Di Tommaso, Maria Laura, 2007. "Children capabilities: A structural equation model for India," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 36(3), pages 436-450, June.
    9. León Tamayo, Dorian Fernando, 2017. "Capability Approach: A Formal Introduction," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 215-218.
    10. Paula Rodríguez-Modroño & Lina Gálvez-Muñoz & Mauricio Matus-López & Mónica Domínguez-Serrano, 2013. "A gender analysis of children’s well-being and capabilities through time use data," Department of Economics (DEMB) 0009, University of Modena and Reggio Emilia, Department of Economics "Marco Biagi".

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    Keywords

    equation; modelling; fuzzy; inference;
    All these keywords.

    JEL classification:

    • J0 - Labor and Demographic Economics - - General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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