Skip to main content
SpringerLink
Log in

Modelling Fuzzy and Multidimensional Poverty Measures in the United Kingdom with Variance Components Panel Regression

  • Chapter
Fuzzy Set Approach to Multidimensional Poverty Measurement

Part of the book series: Economic Studies in Inequality, Social Exclusion and Well-Being ((EIAP,volume 3))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Anderson TW, Hsiao C (1981) Estimation of dynamic models with error components. Journal of the American Statistical Association 76:598–606.

    Article  MATH  MathSciNet  Google Scholar 

  • Anderson TW, Hsiao C (1982) Formulation and Estimation of Dynamic Models Using Panel Data. Journal of Econometrics 18:47–82.

    Article  MATH  MathSciNet  Google Scholar 

  • Bardasi E, Jenkins SP, Rigg J (2004) Documentation for derived current and annual net household income variables. BHPS 1-12, ISER unofficial supplement to BHPS data

    Google Scholar 

  • Betti G, Cheli B, Cambini R (2004) A statistical model for the dynamics between two fuzzy states: theory and an application to poverty analysis. Metron 62:391–411.

    MathSciNet  Google Scholar 

  • Betti G, D’Agostino A, Neri L (2002) Panel regression models for measuring multi-dimensional poverty dynamics. Statistical Methods and Applications 11:359–369.

    Article  MATH  Google Scholar 

  • Betti G, Verma V (1999) Measuring the degree of poverty in a dynamic and comparative context: a multi-dimensional approach using fuzzy set theory. Proceedings of the ICCS-VI, Lahore, Pakistan, August 27–31, 1999, pp 289–301.

    Google Scholar 

  • Betti G, Verma V (2004) A methodology for the study of multi-dimensional and longitudinal aspects of poverty and deprivation. Università di Siena, Dipartimento di Metodi Quantitativi, Working Paper 49

    Google Scholar 

  • Cerioli A, Zani S (1990) A fuzzy approach to the measurement of poverty. In: Dagum C, Zenga M (eds) Income and wealth distribution, inequality and poverty. Springer Verlag, Berlin, pp 272–284.

    Google Scholar 

  • Cheli B (1995) Totally Fuzzy and Relative Measures in Dynamics Context. Metron 53:83–205.

    MathSciNet  Google Scholar 

  • Cheli B, Betti G (1999), Fuzzy Analysis of Poverty Dynamics on an Italian Pseudo Panel, 1985–1994. Metron 57:83–103.

    MATH  MathSciNet  Google Scholar 

  • Cheti B, Lemmi A (1995) A “Totally” Fuzzy and Relative Approach to the Multi-dimensional Analysis of Poverty. Economic Notes 24:115–134.

    Google Scholar 

  • Devicenti F (2001) Poverty persistence in Britain: a multivariate analysis using The BHPS, 1991–1997. In: Moyes P, Seidl C, Shorrocks AF (eds) Inequalities: theory, measurement and applications. Journal of Economics Suppl. 9, pp 1–34.

    Google Scholar 

  • Goldstein H, Healy M JR, Rasbash J (1994) Multilevel time series models with applications to repeated measures data. Statistics in Medicine 13:1643–1655.

    PubMed  CAS  Google Scholar 

  • Jenkins SP (2000) Modelling household income dynamics. Journal of Population Economics 13:529–567.

    Article  Google Scholar 

  • Lillard LA, Willis RJ (1978) Dynamic aspect of earning mobility. Econometrica 46:985–1011.

    Article  MATH  Google Scholar 

  • Littell RC, Milliken GA, Stroup WW, Wolfinger RD (1996) SAS System for Mixed Models. SAS Institute Inc., Cary, NC

    Google Scholar 

  • Mansour H, Norheim EV, Rutledge JJ (1985) Maximum likelihood estimation of variance components in repeated measure designs assuming autoregressive errors. Biometrics 41:287–294.

    Article  MATH  MathSciNet  Google Scholar 

  • McClements LD (1977) Equivalence scales for children. Journal of Public Economics 8:191–210.

    Article  PubMed  CAS  Google Scholar 

  • Modigliani F (1966) The life cycle hypothesis of savings, the demand for wealth and the supply of capital. Social Research 33:160–217.

    Google Scholar 

  • Raghunathan TE, Lepkowski J, Van Voewyk J (2001) A multivariate technique for imputing missing values using a sequence of regression models. Survey Methodology 27:85–95.

    Google Scholar 

  • Stevens AH (1999) Climbing out of poverty, falling back in: measuring the persistence of poverty over multiple spells. Journal of Human Resources 34:557–588.

    Article  Google Scholar 

  • Trivellato U (1998) Il monitoraggio della povertà e della sua dinamica: questioni di misura e evidenze empiriche. Statistica 58:549–575.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento Metodi Quantitativi, University of Siena, Italy

    Gianni Betti & Laura Neri

  2. Dipartimento di Statistica e Matematica per la Ricerca Economica, University of Naples “Parthenope”, France

    Antonella D’Agostino

Authors
  1. Gianni Betti
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonella D’Agostino
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Laura Neri
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Achille Lemmi Gianni Betti

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Betti, G., D’Agostino, A., Neri, L. (2006). Modelling Fuzzy and Multidimensional Poverty Measures in the United Kingdom with Variance Components Panel Regression. In: Lemmi, A., Betti, G. (eds) Fuzzy Set Approach to Multidimensional Poverty Measurement. Economic Studies in Inequality, Social Exclusion and Well-Being, vol 3. Springer, Boston, MA . https://doi.org/10.1007/978-0-387-34251-1_14

Download citation

Publish with us

Policies and ethics

Search

Navigation